ppxscal/embedding_network huggingface dataset:
Managing the diffusion of organizational learning behavior
Authors: Gary F. Templeton, Mark B. Schmidt, G. Stephen Taylor
Venue: Information Systems Frontiers (2009)

This paper addresses the need for organizations to manage the transformation from traditional hierarchical models to `learning organizations.' We propose a five-stage methodology useful in the diffusion of behaviors associated with organizational learning (OL) theory. The stages of OL diffusion are (1) agenda-setting, (2) matching, (3) restructuring, (4) clarifying, and (5) routinizing. Each stage involves both managerial (structural) or member (cultural) influences on organizational memory (OM). Salient definitions are provided and the OM aspects and deliverables associated with each OL diffusion stage are discussed. This research provides a theoretically-driven approach to help change agents diffuse and realize the potential of OL behavior in the firm.
A Remark on Natural Language Processing from the Biolinguistic Perspective
Authors: Anna Maria Di Sciullo
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

In this paper, I discuss basic elements of the biolinguistic approach to language and language processing. First, I provide evidence that linguistic expressions have hierarchical structure where asymmetric relations hold. Second, I relate biolinguistics to language processing, and I discuss central aspects of natural language processing based on the properties of natural languages. Third, I identify some connections between biology, language, and information processing.
Service Interaction: Patterns, Formalization, and Analysis
Authors: Wil M. Aalst, Arjan J. Mooij, Christian Stahl, Karsten Wolf
Venue: Formal Methods for Web Services: 9th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2009, Bertinoro, Italy, June 1-6, 2009, Advanced Lectures (2009)

As systems become more service oriented and processes increasingly cross organizational boundaries, interaction becomes more important. New technologies support the development of such systems. However, the paradigm shift towards service orientation, requires a fundamentally different way of looking at processes. This survey aims to provide some foundational notions related to service interaction. A set of service interaction patterns is given to illustrate the challenges in this domain. Moreover, key results are given for three of these challenges: (1) How to expose a service?, (2) How to replace and refine services?, and (3) How to generate service adapters? These challenges will be addressed in a Petri net setting. However, the results extend to other languages used in this domain.
Identification of the de-synchronization, synchronization and forced oscillation phenomenon of a nonlinear system
Authors: Marius-Constantin Popescu, Onisifor Olaru, Valentina Balas
Venue: WSEAS Transactions on Systems and Control (2009)

The phenomena of de-synchronization, synchronization, and forced oscillation has been investigation using describing function theory for a two input and two output nonlinear system containing saturation-type nonlinearities and subjected to high-frequency deterministic signal for the purpose of limit cycle quenching. The analytical results have been compared with the results of digital simulation Matlab-Simulink for a typical example varying the nonlinear element.
Statistical Mechanics of On-line Learning
Authors: Michael Biehl, Nestor Caticha, Peter Riegler
Venue: Similarity-Based Clustering: Recent Developments and Biomedical Applications (2009)

We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large systems allows to perfom averages over the randomness contained in the sequence of training data. It yields an exact mathematical description of the training dynamics in model scenarios. We present the basic concepts and results of the approach in terms of several examples, including the learning of linear separable rules, the training of multilayer neural networks, and Learning Vector Quantization.
The Development and Evaluation of the Term Paper Grading Assistance Map Visualizing Contents and its Scores
Authors: Mio Tsubakimoto, Masayoshi Yanagisawa, Kanji Akahori
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

The authors have developed and evaluated a term paper-grading assistance map. The map was designed to visualize scores graded for term papers assigned to a class at the university level and their similarities. Initially, the authors have reviewed some visualization techniques for text information in this paper by utilizing real term papers written by the university students. Then, the authors have selected Deerwester et al's technique and developed the term paper-grading assistance map. The map is a new visualization technique to show the amount of words and word use. The authors have investigated the effectiveness of the map for human raters from a questionnaire survey. The findings have showed that raters were motivated to grade the term papers by referring to other term papers which were graded in advance, and felt the assistance usefulness.
Fundamentals of Session Types
Authors: Vasco T. Vasconcelos
Venue: Formal Methods for Web Services: 9th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2009, Bertinoro, Italy, June 1-6, 2009, Advanced Lectures (2009)

We present a reconstruction of session types in a linear pi calculus where types are qualified as linear or unrestricted. Linearly qualified communication channels are guaranteed to occur in exactly one thread, possibly multiple times. In our language each channel is characterised by two distinct variables, one used for reading, the other for writing; scope restriction binds together two variables, thus establishing the correspondence between the two ends of a same channel. This mechanism allows a precise control of resources via a linear type system. We build the language gradually, starting from simple input/output, then adding choice, recursive types, replication and finally subtyping. We also present an algorithmic type checking system.
Note: Domination in a digraph and in its reverse
Authors: L'udovít Niepel, Martin Knor
Venue: Discrete Applied Mathematics (2009)

Let D be a digraph. By @c(D) we denote the domintaion number of D and by D^- we denote a digraph obtained by reversing all the arcs of D. In this paper we prove that for every @d>=3 and k>=1 there exists a simple strongly connected @d-regular digraph D"@d","k such that @c(D"@d","k^-)-@c(D"@d","k)=k. Analogous theorem is obtained for total domination number provided that @d>=4.
Three Stages for the Scenarisation of Learning Objects
Authors: Sofiane Aouag
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)

The main focus of current discussions within the standardization process of Learning technology is on technical aspects of so called learning objects. The purpose of this paper is to show the three stages of a learning object scenarisation, starting with the instantiation of contents parameters. The second stage is related to the pedagogical instruments, which represent the supports of these contents and finally the adaptation of a scenario for each pedagogical instrument.
Affordable, entropy-consistent Euler flux functions II: Entropy production at shocks
Authors: Farzad Ismail, Philip L. Roe
Venue: Journal of Computational Physics (2009)

In this paper, an entropy-consistent flux is developed, continuing from the work of the previous paper. To achieve entropy consistency, a second and third-order differential terms are added to the entropy-conservative flux. This new flux function is tested on several one dimensional problems and compared with the original Roe flux. The new flux function exactly preserves the stationary contact discontinuity and does not capture the unphysical rarefaction shock. For steady shock problems, the new flux predicts a slightly more diffused profile whereas for unsteady cases, the captured shock is very similar to those produced by the Roe- flux. The shock stability is also studied in one dimension. Unlike the original Roe flux, the new flux is completely stable which will provide as a candidate to combat multidimensional shock instability, particularly the carbuncle phenomenon.
3D Game Programming for Teens, 2nd edition
Authors: Maneesh Sethi
Venue:  (2009)

Do you love video games? Do you want to learn how to make them yourself? Welcome to 3D Game Programming for Teens, Second Edition, a how-to resource for anyone interested in creating a video game. Written specifically for beginners in an easy-to-follow way, the book teaches you basic programming, graphic design, and 3D modeling so that you can design and develop your very own games. Youll begin with an introduction to some simple programming concepts using the Blitz3D language. Then youll learn about graphics creation for games using CorelDRAW and PHOTOPAINT. Finally youll explore basic 3D modeling with Autodesk 3ds Max, and youll learn how to enhance your games with sound effects, collisions, and more. 3D Game Programming for Teens, Second Edition walks you through the game programming process step-by-step, with each new technique building upon the previous ones. The final chapter of the book shows you how to put all your new knowledge together and build your own full game! All you need to get started are some basic computer skills and a love of games. No previous programming experience required!
Static Coarse Grain Task Scheduling with Cache Optimization Using OpenMP
Authors: Hirofumi Nakano, Kazuhisa Ishizaka, Motoki Obata, Keiji Kimura, Hironori Kasahara
Venue: Proceedings of the 4th International Symposium on High Performance Computing (2009)

Effective use of cache memory is getting more important with increasing gap between the processor speed and memory access speed. Also, use of multigrain parallelism is getting more important to improve effective performance beyond the limitation of loop iteration level parallelism. Considering these factors, this paper proposes a coarse grain task static scheduling scheme considering cache optimization. The proposed scheme schedules coarse grain tasks to threads so that shared data among coarse grain tasks can be passed via cache after task and data decomposition considering cache size at compile time. It is implemented on OSCAR Fortran multigrain parallelizing compiler and evaluated on Sun Ultra80 four-processor SMP workstation, using Swim and Tomcatv from the SPEC fp 95. As the results, the proposed scheme gives us 4.56 times speedup for Swim and 2.37 times on 4 processors for Tomcatv respectively against the Sun Forte HPC 6 loop parallelizing compiler.
Inconsistency tolerance in weighted argument systems
Authors: Paul E. Dunne, Anthony Hunter, Peter McBurney, Simon Parsons, Michael Wooldridge
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We introduce and investigate a natural extension of Dung's well-known model of argument systems in which attacks are associated with a weight, indicating the relative strength of the attack. A key concept in our framework is the notion of an inconsistency budget, which characterises how much inconsistency we are prepared to tolerate: given an inconsistency budget &beta;, we would be prepared to disregard attacks up to a total cost of &beta;. The key advantage of this approach is that it permits a much finer grained level of analysis of argument systems than unweighted systems, and gives useful solutions when conventional (unweighted) argument systems have none. We begin by reviewing Dung's abstract argument systems, and present the model of weighted argument systems. We then investigate solutions to weighted argument systems and the associated complexity of computing these solutions, focussing in particular on weighted variations of grounded extensions.
Special session on Advances in software technologies and cognitive systems
Authors: Nancy Alonistioti
Venue: Proceeding of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering (2008)

In the recent years, an interesting blending of computing, software technologies, sensors and even telecommunications concepts has facilitated the emergence of cognitive systems targeting various domains of applications. Artificial systems that can interpret data arising from real-world events and processes (mainly in the form of data-streams from sensors of all types and from visual and/or audio sources); acquire situated knowledge of their environment; act, make or suggest decisions and communicate with people on human terms, thereby supporting them in performing complex tasks. Cognitive radio is a paradigm for wireless communication in which either a network or a wireless node changes its transmission or reception parameters to communicate efficiently avoiding interference with licensed or unlicensed users. This alteration of parameters is based on the active monitoring of several factors in the external and internal radio environment, such as radio frequency spectrum, user behaviour and network state. Cognition can be defined as the act or process of knowing in the broadest sense; specifically, an intellectual or artificial process by which knowledge is gained from perception. Respective concepts have impact in the evolution and emergence of cognitive communications and future internet elements. To this end, advances in various areas are identified towards building the knowledge and mechanisms for cognitive systems operation. 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
Application of DNA Computing by Self-assembly on 0-1 Knapsack Problem
Authors: Guangzhao Cui, Cuiling Li, Xuncai Zhang, Yanfeng Wang, Xinbo Qi, Xiaoguang Li, Haobin Li
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Computation by self-assembly of DNA is an efficient method of executing parallel DNA computing where information is encoded in DNA tiles and a large number of tiles can be self-assembled via sticky-end associations. It presents clear evidence of the ability of molecular computing to perform complicated mathematical operations. We investigate how basic ideas on tiling can be applied to solving knapsack problem. It suggests that these procedures can be realized on the molecular scale through the medium of self-assembled DNA tiles. The potential of DNA computing by self-assembly for the knapsack problem is promising given the operational time complexity of ¿(n).
Intelligent methods for solving inverse problems of backscattering spectra with noise: a comparison between neural networks and simulated annealing
Authors: Michael M. Li, William Guo, Brijesh Verma, Kevin Tickle, John O&#x2019;Connor
Venue: Neural Computing and Applications (2009)

This paper investigates two different intelligent techniques&#x2014;the neural network (NN) method and the simulated annealing (SA) algorithm for solving the inverse problem of Rutherford backscattering (RBS) with noisy data. The RBS inverse problem is to determine the sample structure information from measured spectra, which can be defined as either a function approximation or a non-linear optimization problem. Early studies emphasized on numerical methods and empirical fitting. In this work, we have applied intelligent techniques and compared their performance and effectiveness for spectral data analysis by solving the inverse problem. Since each RBS spectrum may contain up to 512 data points, principal component analysis is used to make the feature extraction so as to ease the complexity of constructing the network. The innovative aspects of our work include introducing dimensionality reduction and noise modeling. Experiments on RBS spectra from SiGe thin films on a silicon substrate show that the SA is more accurate but the NN is faster, though both methods produce satisfactory results. Both methods are resilient to 10% Poisson noise in the input. These new findings indicate that in RBS data analysis the NN approach should be preferred when fast processing is required; whereas the SA method becomes the first choice should the analysis accuracy be targeted.
The Convergence of a Central-Difference Discretization of Rudin-Osher-Fatemi Model for Image Denoising
Authors: Ming-Jun Lai, Bradley Lucier, Jingyue Wang
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

We study the connection between minimizers of the discrete and the continuous Rudin-Osher-Fatemi models. We use a central-difference total variation term in the discrete ROF model and treat the discrete input data as a projection of the continuous input data into the discrete space. We employ a method developed in [13] with slight adaption to the setting of the central-difference total variation ROF model. We obtain an error bound between the discrete and the continuous minimizer in L 2 norm under the assumption that the continuous input data are in W 1, 2.
Computer Recognition Systems 2 (Advances in Soft Computing), 1st edition
Authors: Marek Kurzynski, Marek Kurzynski, Edward Puchala, Michal Wozniak, Andrzej Zolnierek
Venue:  (2007)

This book presents the results of the 5th International Conference on Computer Recognition Sstems CORES 07 held 22-25 October 2007 in Hotel Tumski, Wroclaw, Poland. It brings together original research results in both methodological issues and different application areas of pattern recognition. The contributions cover all topics in pattern recognition including: Classification and interpretation of text, video, voice; statistical, soft and structural methods of pattern recognition; image processing, analysis and interpretation; machine learning; data and Web mining; knowledge-based decision support systems; advanced signal processing methods or special hardware architecture.
Parallel tabu search for optimizing the OSPF weight setting problem
Authors: Sadiq M. Sait, Mohammed H. Sqalli, Syed Asadullah
Venue: WSEAS TRANSACTIONS on COMMUNICATIONS (2009)

The problem of setting the Open Shortest Path First (OSPF) weights on links such that congestion can be avoided is proved to be NP-hard. Many iterative heuristics have been applied to solve the OSPF weight setting (OSPFWS) problem. As the size of any combinatorial optimization problem increases, it becomes more difficult to find an optimum solution using sequential algorithms. Parallelization of modern iterative heuristics has been proven to produce improved solution precision and timing. In this paper, we investigate the parallelization of Tabu Search and apply two variants of a Parallel Tabu Search (PTS) heuristic on the OSPFWS problem. It is shown through experimental results that both PTS approaches produced better solutions quality compared to the sequential heuristics; specifically for larger topologies. In one approach, we propose a new design for our parallel cooperative search algorithm, which performs better than the conventional parallel heuristic. The purpose of this new design is to induce diversification into the search to explore a larger search space. We also show that the new approach performs better than the conventional parallel heuristic.
Modelling treatment effects in a clinical Bayesian network using Boolean threshold functions
Authors: Stefan Visscher, Peter J. F. Lucas, Carolina A. M. Schurink, Marc J. M. Bonten
Venue: Artificial Intelligence in Medicine (2009)

Objective: Appropriate antimicrobial treatment of infections in critically ill patients should be started as soon as possible, as delay in treatment may reduce a patient's prognostic outlook considerably. Ventilator-associated pneumonia (VAP) occurs in patients in intensive care units who are mechanically ventilated and is almost always preceded by colonisation of the respiratory tract by the causative microorganisms. It is very difficult to clinically diagnose VAP and, therefore, some form of computer-based decision support might be helpful for the clinician. Materials and methods: As diagnosing and treating VAP involves reasoning with uncertainty, we have used a Bayesian network as the primary tool for building a decision-support system. The effects of usage of antibiotics on the colonisation of the respiratory tract by various pathogens and the subsequent antibiotic choices in case of VAP were modelled using the notion of causal independence. In particular, the conditional probability distribution of the random variable that represents the overall coverage of pathogens by antibiotics was modelled in terms of the conjunctive effect of the seven different pathogens, usually referred to as the noisy-AND model. In this paper, we investigate different coverage models, as well as generalisations of the noisy-AND, called noisy-threshold models, and test them on clinical data of intensive care unit (ICU) patients who are mechanically ventilated. Results: Some of the constructed noisy-threshold models offered further improvement of the performance of the Bayesian network in covering present causative pathogens by advising appropriate antimicrobial treatment. Conclusions: By reconsidering the modelling of interactions between the random variables in a Bayesian network using the theory of causal independence, it is possible to refine its performance. This was clearly shown for our Bayesian network concerning VAP, indicating that only specific noisy-threshold models might be appropriate for the modelling of the interaction between pathogens and antimicrobial treatment with respect to susceptibility. The results obtained also provide evidence that the noisy-OR and noisy-AND might not always be the best functions to model interactions among random variables.
How novelty search escapes the deceptive trap of learning to learn
Authors: Sebastian Risi, Sandy D. Vanderbleek, Charles E. Hughes, Kenneth O. Stanley
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

A major goal for researchers in neuroevolution is to evolve artificial neural networks (ANNs) that can learn during their lifetime. Such networks can adapt to changes in their environment that evolution on its own cannot anticipate. However, a profound problem with evolving adaptive systems is that if the impact of learning on the fitness of the agent is only marginal, then evolution is likely to produce individuals that do not exhibit the desired adaptive behavior. Instead, because it is easier at first to improve fitness without evolving the ability to learn, they are likely to exploit domain-dependent static (i.e. non-adaptive) heuristics. This paper proposes a way to escape the deceptive trap of static policies based on the novelty search algorithm, which opens up a new avenue in the evolution of adaptive systems because it can exploit the behavioral difference between learning and non-learning individuals. The main idea in novelty search is to abandon objective-based fitness and instead simply search only for novel behavior, which avoids deception entirely and has shown prior promising results in other domains. This paper shows that novelty search significantly outperforms fitness-based search in a tunably deceptive T-Maze navigation domain because it fosters the emergence of adaptive behavior.