ppxscal/embedding_network huggingface dataset:
Building Policies for Scrabble
Authors: Alejandro Gonzalez Romero, René Alquezar
Venue: Proceeding of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence (2008)

Research to learn policies using Evolutionary Algorithms along with training examples has been done for the domains of the Blocks World and the KRKa2 chess ending in our previous work [1,2]. Although the results have been positive, we believe that a more challenging domain is necessary to test the performance of this technique. The game of Scrabble, played in Spanish, in its competitive form (one vs. one) intends to be used and studied to test how good evolutionary techniques perform in building policies that produce a plan. To conduct proper research for Scrabble a Spanish lexicon was built and a heuristic function mainly based on probabilistic leaves was developed recently [3]. Despite the good results obtained with this heuristic function, the experimental games played showed that there is much room for improvement. In this paper a sketch of how can policies be built for the domain of Scrabble is presented; these policies are constructed using attributes (concepts and actions) given by a Scrabble expert player and using the heuristic function presented in [3] as one of the actions. Then to evaluate the policies a set of training examples given by a Scrabble expert is used along with the evolutionary learning algorithm presented in [2]. The final result of the process is an ordered set of rules (a policy) which denotes a plan that can be followed by a Scrabble engine to play Scrabble. This plan would also give useful information to construct plans that can be followed by humans when playing Scrabble. Most of this work is still under construction and just a sketch is presented. We believe that the domain of games is well-suited for testing these ideas in planning.
Exploiting cross-linguistic similarities in Zulu and Xhosa computational morphology
Authors: Laurette Pretorius, Sonja Bosch
Venue: Proceedings of the First Workshop on Language Technologies for African Languages (2009)

This paper investigates the possibilities that cross-linguistic similarities and dissimilarities between related languages offer in terms of bootstrapping a morphological analyser. In this case an existing Zulu morphological analyser prototype (ZulMorph) serves as basis for a Xhosa analyser. The investigation is structured around the morphotactics and the morphophonological alternations of the languages involved. Special attention is given to the so-called "open" class, which represents the word root lexicons for specifically nouns and verbs. The acquisition and coverage of these lexicons prove to be crucial for the success of the analysers under development. The bootstrapped morphological analyser is applied to parallel test corpora and the results are discussed. A variety of cross-linguistic effects is illustrated with examples from the corpora. It is found that bootstrapping morphological analysers for languages that exhibit significant structural and lexical similarities may be fruitfully exploited for developing analysers for lesser-resourced languages.
An OFDM-based transmission scheme for underwater acoustic multimedia
Authors: Chin-Feng Lin, Chen-Hsiang Shih, Cheng-Pin Chen, Shao-Wei Leu, Jiing-Kae Wu, Ching-Hsiang Tseng, Hsien-Sen Hung, Fu-Sheng Lu, Ivan A. Parinov, Shun-Hsyung Chang
Venue: WSEAS TRANSACTIONS on COMMUNICATIONS (2009)

In this paper, we propose an orthogonal frequency division multiplexing-based (OFDM-based) underwater acoustic multimedia system. An essential feature of this system is that it offers greater power and schemes with significant error protection for the transmission of sensor data information requiring a higher quality of service (QoS). To realize maximum resource utilization or minimum total transmission power, we also include an adaptive modulation strategy into the system. The proposed underwater acoustic multimedia system employs high power, low speed modulation, and schemes providing significant error protection for the transmission of sensor data messages requiring a stringent bit-error rate (BER). In contrast, low power, high speed modulation, and less capable error protection schemes are provided for messages that can tolerate a high BER. A simulation was carried out to verify the functionality of the proposed system in a practical underwater acoustic multimedia scenario.
Unconditionally Secure Blind Authentication Codes: The Model, Constructions, and Links to Commitment
Authors: Yuki Hara, Taiki Ishiwata, Junji Shikata, Tsutomu Matsumoto
Venue: Formal to Practical Security: Papers Issued from the 2005-2008 French-Japanese Collaboration (2009)

In this paper, as a fundamental cryptographic protocol with information-theoretic security, we propose an unconditionally secure blind authentication code (BA-code for short) which is an unconditionally secure authentication code with anonymity of messages. As we will see, the BA-code is a simple model of an authentication code with the function similar to that of the unconditionally secure blind signature (USBS for short). The relationship between BA-codes and USBS is similar to the one between traditional authentication codes and unconditionally secure signature schemes as well as the one between group authentication codes and group signature schemes. In addition, we provide two kinds of constructions of BA-codes: direct constructions based on polynomials over finite fields, and a generic construction by using unconditionally secure encryption and A2-codes. Furthermore, as application we show a link between BA-codes and commitment in unconditional security setting: starting from BA-codes, unconditionally secure commitment schemes can be constructed in a black-box way.
On Convergence-sensitive Bisimulation and the Embedding of CCS in Timed CCS
Authors: Roberto M. Amadio
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

We propose a notion of convergence-sensitive bisimulation that is built just over the notions of (internal) reduction and of (static) context. In the framework of timed CCS, we characterise this notion of 'contextual' bisimulation via the usual labelled transition system. We also remark that it provides a suitable semantic framework for a fully abstract embedding of untimed processes into timed ones. Finally, we show that the notion can be refined to include sensitivity to divergence.
Tracking multiple interacting subcellular structure by sequential Monte Carlo method
Authors: Quan Wen, Kate Luby-Phelps, Jean Gao
Venue: International Journal of Data Mining and Bioinformatics (2009)

With the wide application of Green Fluorescent Proteins (GFP) in the study of live cells, there is a surging need for computer-aided analysis on the huge amount of image sequence data acquired by the advanced microscopy devices. In this paper, a framework based on Sequential Monte Carlo (SMC) is proposed for multiple interacting object tracking. The distribution of the dimension varying joint state is sampled efficiently by a Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm with a novel height swap move. Experimental results were performed on synthetic and real confocal microscopy image sequences.
Dictionary definitions based homograph identification using a generative hierarchical model
Authors: Anagha Kulkarni, Jamie Callan
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

A solution to the problem of homograph (words with multiple distinct meanings) identification is proposed and evaluated in this paper. It is demonstrated that a mixture model based framework is better suited for this task than the standard classification algorithms - relative improvement of 7% in F1 measure and 14% in Cohen's kappa score is observed.
Information Extraction System Based on Hidden Markov Model
Authors: Dong-Chul Park, Vu Thi Huong, Dong-Min Woo, Duong Ngoc Hieu, Sai Thi Ninh
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

A novel approach using Hidden Markov Model (HMM) for the task of finding prices of products on internet sites is proposed in this paper. The proposed Information Extraction System based on HMM (IESHMM) utilizes HMM for its capability to process temporal information. The proposed IESHMM first processes web pages that are returned from search engines and then extracts specific fields such as prices, descriptions, locations, images of products, and other information of interest. The proposed IESHMM is evaluated with real-world problems and compared with a conventional method. The results show that the proposed IESHMM outperforms the other method by 22.9 % and 37.2% in terms of average recall and average precision, respectively.
Design of an intrusion detection system based on Bayesian networks
Authors: Milan Tuba, Dusan Bulatovic
Venue: WSEAS Transactions on Computers (2009)

This paper describes a structure of a standalone Intrusion Detection System (IDS) based on a large Bayesian network. To implement the IDS we develop the design methodology of large Bayesian networks. A small number of natural templates (idioms) are defined which make the design of Bayesian network easier. They are related to specific fragments of Bayesian networks representing the basic elements in reasoning about uncertain events. The idioms represent the graphical structure, without the probabilistic tables. The use of idioms speeds-up the development of Bayesian networks and improves their quality. Example network is constructed and examined. Such Bayesian network can represent an independent agent in a distributed system. Results are promising since with very limited computation and low sensitivity to the quality of prior knowledge, potentially dangerous situations are successfully detected and classified.
Prediction of periventricular leukomalacia. Part II: Selection of hemodynamic features using computational intelligence
Authors: Biswanath Samanta, Geoffrey L. Bird, Marijn Kuijpers, Robert A. Zimmerman, Gail P. Jarvik, Gil Wernovsky, Robert R. Clancy, Daniel J. Licht, J. William Gaynor, Chandrasekhar Nataraj
Venue: Artificial Intelligence in Medicine (2009)

Objective: The objective of Part II is to analyze the dataset of extracted hemodynamic features (Case 3 of Part I) through computational intelligence (CI) techniques for identification of potential prognostic factors for periventricular leukomalacia (PVL) occurrence in neonates with congenital heart disease. Methods: The extracted features (Case 3 dataset of Part I) were used as inputs to CI based classifiers, namely, multi-layer perceptron (MLP) and probabilistic neural network (PNN) in combination with genetic algorithms (GA) for selection of the most suitable features predicting the occurrence of PVL. The selected features were next used as inputs to a decision tree (DT) algorithm for generating easily interpretable rules of PVL prediction. Results: Prediction performance for two CI based classifiers, MLP and PNN coupled with GA are presented for different number of selected features. The best prediction performances were achieved with 6 and 7 selected features. The prediction success was 100% in training and the best ranges of sensitivity (SN), specificity (SP) and accuracy (AC) in test were 60-73%, 74-84% and 71-74%, respectively. The identified features when used with the DT algorithm gave best SN, SP and AC in the ranges of 87-90% in training and 80-87%, 74-79% and 79-82% in test. Among the variables selected in CI, systolic and diastolic blood pressures, and pCO"2 figured prominently similar to Part I. Decision tree based rules for prediction of PVL occurrence were obtained using the CI selected features. Conclusions: The proposed approach combines the generalization capability of CI based feature selection approach and generation of easily interpretable classification rules of the decision tree. The combination of CI techniques with DT gave substantially better test prediction performance than using CI and DT separately.
OpenRSM: a lightweight integrated open source remote management solution
Authors: Y. Karalis, M. N. Kalochristianakis, P. Kokkinos, E. A. Varvarigos
Venue: International Journal of Network Management (2009)

The management of the corporate information technology (IT) environment is rapidly increasing in complexity as server logic architecture becomes more distributed and the number of entities deployed increases, forcing enterprises to resort to thick, complex and expensive high-end integrated systems and network management solutions. Investing in such systems can be inefficient for small and medium corporations, since the vast majority of management tasks performed are routine tasks, while personnel specialization requirements and costs are high. At the same time, the open source community has not yet produced a reliable and complete system and network management solution. Even though there are open source initiatives specializing in specific fields of remote management, such as network management, there has been no integrated open source solution yet. This paper introduces the Open Source Remote Systems Management (OpenRSM) platform. OpenRSM is an integrated remote management system created by integrating individual specialized open source management initiatives and significantly augmenting them to support additional functionality, so that a complete lightweight system and network management solution is produced. The system implemented facilitates daily management by providing an efficient, simple and adaptable environment for the majority of management operations.
An Empirical Investigation of the Adversarial Activity Model
Authors: Inon Zuckerman, Sarit Kraus, Jeffrey S. Rosenschein
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Multiagent research provides an extensive literature on formal Belief-Desire-Intention (BDI) based models describing the notions of teamwork and cooperation, but adversarial and competitive relationships have received very little formal BDI treatment. Moreover, one of the main roles of such models is to serve as design guide-lines for the creation of agents, and while there is work illustrating that role in cooperative interaction, there has been no empirical work done to validate competitive BDI models. In this work we use the Adversarial Activity model, a BDI-based model for bounded rational agents that are operating in a general zero-sum environment, as an architectural guideline for building bounded rational agents in two adversarial environments: the Connect-four game (a bilateral environment) and the Risk strategic board game (a multilateral environment). We carry out extensive simulations that illustrate the advantages and limitations of using this model as a design specification.
Strain sensitivity of gate leakage in strained-SOI nMOSFETs: A benefit for the performance trade-off and a novel way to extract the strain-induced band offset
Authors: F. Rochette, X. Garros, G. Reimbold, F. Andrieu, M. Cassé, M. Mouis, G. Ghibaudo, F. Boulanger
Venue: Microelectronic Engineering (2009)

The impact of biaxial stress on gate leakage is investigated on fully-depleted silicon-on-insulator (FD-SOI) nMOS transistors, integrating either a standard gate stack or an advanced high-@k/metal gate stack. It is demonstrated that strained devices exhibit significantly reduced leakage currents (up to -90% at E"o"x=11MV/cm for @s"t"e"n"s"i"l"e=2.5GPa). This specific effect is used to extract the conduction band offset @DEc induced by strain and is shown to be accurate enough to monitor stress in MOSFETs. This new technique is much less sensitive to gate oxide defects than the method based on the threshold voltage shift @DV"T. This accurate experimental extraction allowed us to pick out realistic values for the deformation potentials in silicon (@X"u=8.5eV and @X"d=-5.2eV), among the published values.
Maximum Expected Utility of Markovian Predicted Wealth
Authors: Enrico Angelelli, Sergio Ortobelli Lozza
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

This paper proposes an ex-post comparison of portfolio selection strategies based on the assumption that the portfolio returns evolve as Markov processes. Thus we propose the comparison of the ex-post final wealth obtained with the maximization of the expected negative exponential utility and expected power utility for different risk aversion parameters. In particular, we consider strategies where the investors recalibrate their portfolios at a fixed temporal horizon and we compare the wealth obtained either under the assumption that returns follow a Markov chain or under the assumption we have independent identically distributed data. Thus, we implement an heuristic algorithm for the global optimum in order to overcome the intrinsic computational complexity of the proposed Markovian models.
Positive solutions for a class of boundary-value problems with integral boundary conditions
Authors: Xuemei Zhang, Weigao Ge
Venue: Computers Mathematics with Applications (2009)

This paper investigates the existence and multiplicity of positive solutions for a class of nonlinear boundary-value problems of fourth-order differential equations with integral boundary conditions. The arguments are based upon a specially constructed cone and the fixed-point theory in cone. The nonexistence of positive solutions is also studied.
System proposal for preventing, detecting and avoiding deadlocks in modern operating system
Authors: Zakaria Suliman Zubi, Diaddeen S. Sidoon
Venue: Proceedings of the 10th WSEAS international conference on evolutionary computing (2009)

This paper presents a system proposal for preventing, detecting and avoiding deadlocks (PDADL), the system applies some common methods to prevent, detect and avoid deadlock on a local operating system. Moreover, the system simulates all the process and resources on a real operating system. The resources and processes can be detected dynamically from different operations running by real application programs through the operating system. We use Matrix-based algorithm for detecting the deadlock, and Banker's algorithm as well. In addition we made some modifications on the use of avoiding deadlocks in term of, eliminating the circular wait condition which is currently used for preventing deadlocks. We implement an application program named as PDADL to simulate real processes and resources from running operations in a local operating system automatically.
Extending cognitive architectures with spatial and visual imagery mechanisms
Authors: John E. Laird
Venue:  (2008)

This research presents a computational synthesis of cognition with spatial and visual imagery processing by extending a symbolic cognitive architecture (Soar) with mechanisms to support reasoning with quantitative spatial and visual depictive representations. Inspired by psychological and neurological evidence of mental imagery, our primary goals are to achieve new functional capability and computational efficiency in a task-independent manner. We describe how our theory and the corresponding architecture derive from behavioral, biological, functional, and computational constraints and demonstrate results from three different domains. Our evaluation reveals that in tasks where reasoning includes many spatial or visual properties, the combination of amodal and perceptual representations provides an agent with additional functional capability and improves its problem-solving quality. We also show that specialized processing units specific to a perceptual representation but independent of task knowledge are likely to be necessary in order to realize computational efficiency in a general manner.The research is significant because past research in cognitive architectures primarily views amodal, symbolic representations as being sufficient for knowledge representation and thought. We expand those ideas with the notion that perceptual-based representations participate directly in the thinking rather than serving simply as a source of sensory information. The new capabilities of the resulting architecture, which includes Soar and its Spatial-Visual Imagery (SVI) component, emerge from its ability to amalgamate symbolic and perceptual representations and use them to inform reasoning. Soar's symbolic memories and processes provide the building blocks necessary for high-level control in the pursuit of goals, learning, and the encoding of amodal, symbolic knowledge for abstract reasoning. SVI encompasses the quantitative spatial and visual depictive representations and processes specialized for efficient construction and extraction of spatial and visual properties.
Topological method for analysis of periodic canards
Authors: A. A. Zhezherun, A. V. Pokrovskii
Venue: Automation and Remote Control (2009)

Singularly perturbed systems of ordinary differential equations are studied. A method for analysis of canard-type trajectories in such systems based on the topological degree theory is suggested. The method does not require smoothness of the right-hand side of the system. A result on the existence of periodic canards in systems with non-smooth perturbations is obtained. The trajectories located in this way are not necessarily Lyapunov stable, and appropriate control algorithms are required to stabilize them, e.g., feedback control.
Finite approximations of data-based decision problems under imprecise probabilities
Authors: Robert Hable
Venue: International Journal of Approximate Reasoning (2009)

In decision theory under imprecise probabilities, discretizations are a crucial topic because many applications involve infinite sets whereas most procedures in the theory of imprecise probabilities can only be calculated for finite sets so far. The present paper develops a method for discretizing sample spaces in data-based decision theory under imprecise probabilities. The proposed method turns an original decision problem into a discretized decision problem. It is shown that any solution of the discretized decision problem approximately solves the original problem. In doing so, it is pointed out that the commonly used method of natural extension can be most instable. A way to avoid this instability is presented which is sufficient for the purpose of the paper.
From Gestalt Theory to Image Analysis: A Probabilistic Approach, 1st edition
Authors: Agns Desolneux, Lionel Moisan, Jean-Michel Morel
Venue:  (2007)

This book introduces the reader to a recent theory in Computer Vision yielding elementary techniques to analyse digital images. These techniques are inspired from and are a mathematical formalization of the Gestalt theory. Gestalt theory, which had never been formalized is a rigorous realm of vision psychology developped between 1923 and 1975. From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis. The authors maintain a public software, MegaWave, containing implementations of most of the image analysis techniques developped in the book. The book is intended for researchers and engineers. It is mathematically self-contained and requires only the basic notions in probability and calculus.
On basic semantics of untyped functional programs
Authors: G. G. Hrachyan
Venue: Programming and Computing Software (2009)

The paper is devoted to untyped functional programs, which are defined as systems of equations with separating variables in the untyped ¿-calculus [1, 2]. Basic semantics of such programs is usually defined by means of the fixed-point combinator Y. A theorem on semantics invariance with respect to the fixed-point combinator is proved.