ppxscal/embedding_network huggingface dataset:
Linguistic symbiosis between event loop actors and threads
Authors: Tom Van Cutsem, Stijn Mostinckx, Wolfgang De Meuter
Venue: Computer Languages, Systems and Structures (2009)

In modern programming languages, concurrency control can be traced back to one of two different schools: actor-based message passing concurrency and thread-based shared-state concurrency. This paper describes a linguistic symbiosis between two programming languages with such different concurrency models. More specifically, we describe a novel symbiosis between actors represented as event loops on the one hand and threads on the other. This symbiosis ensures that the invariants of the actor-based concurrency model are not violated by engaging in symbiosis with multithreaded programs. The proposed mapping is validated by means of a concrete symbiosis between AmbientTalk, a flexible, domain-specific language for writing distributed programs and Java, a conventional object-oriented language. This symbiosis allows the domain-specific language to reuse existing software components written in a multithreaded language without sacrificing the beneficial event-driven properties of the actor concurrency model.
Narrative Structure of Mathematical Texts
Authors: Fairouz Kamareddine, Manuel Maarek, Krzysztof Retel, J. B. Wells
Venue: Proceedings of the 14th symposium on Towards Mechanized Mathematical Assistants: 6th International Conference (2007)

There are many styles for the narrative structure of a mathematical document. Each mathematician has its own conventions and traditions about labeling portions of texts (e.g., chapter, section, theorem or proof ) and identifying statements according to their logical importance (e.g., theorem is more important than lemma). Such narrative/structuring labels guide the reader's navigation of the text and form the key components in the reasoning structure of the theory reflected in the text.We present in this paper a method to computerise the narrative structure of a text which includes the relationships between labeled text entities. These labels and relations are input by the user on top of their natural language text. This narrative structure is then automatically analysed to check its consistency. This automatic analysis consists of two phases: (1) checking the correct usage of labels and relations (i.e., that a "proof" justifies a "theorem" but cannot justify an "axiom") and (2) checking that the logical precedences in the document are self-consistent.The development of this method was driven by the experience of computerising a number of mathematical documents (covering different authoring styles). We illustrate how such computerised narrative structure could be used for further manipulations, i.e. to build a skeleton of a formal document in a formal system like Mizar, Coq or Isabelle.
Improving Mobile Web-IR Using Access Concentration Sites in Search Results
Authors: Masaya Murata, Hiroyuki Toda, Yumiko Matsuura, Ryoji Kataoka
Venue: Proceedings of the 9th international conference on Web Information Systems Engineering (2008)

Effective ranking algorithms for mobile web search are being actively pursued. Due to the peculiar and troublesome properties of mobile contents such as scant text, few outward links, and few input keywords, conventional web search techniques using bag-of-words ranking functions or link-based algorithms are not good enough for mobile web search. Our solution is to use click logs; the aim is to extract only access concentrated search results from among the many search results. Users typically click a search result after seeing its title and snippet, so the titles and snippets of the access concentrated sites must be good relevance feedback sources that will greatly improve mobile web search performance. In this paper, we introduce a new measure that is capable of estimating the degree of access concentration and present a method that uses the measure to precisely extract the access concentration sites from many search results. Query expansion with terms extracted from the access concentration sites is then performed. The effectiveness of our proposal is verified in an experiment that uses click logs and data from a real mobile web search site.
Integration of SCTP in the OMNeT++ simulation environment
Authors: Irene Rüngeler, Michael Tüxen, Erwin P. Rathgeb
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

The INET framework for the widely used OMNeT++ simulation environment supports discrete event simulation for IP-based networks. This paper describes an implementation of the Stream Control Transmission Protocol (SCTP) within this framework. SCTP is a new transport protocol originally designed for signaling transport in telephony networks. The simulation model and parameters of the SCTP implementation in INET are discussed in detail. The INET framework has also been extended to support external interfaces. These interfaces allow to set up hybrid scenarios where simulated nodes communicate with real external IP-based nodes. This new feature was used to test the simulation against multiple SCTP implementations at the last SCTP Interoperability tests. Other methods that were used to verify the SCTP simulation are finally discussed.
A Hybrid Approach for Safe Memory Management in C
Authors: Syrine Tlili, Zhenrong Yang, Hai Zhou Ling, Mourad Debbabi
Venue: Proceedings of the 12th international conference on Algebraic Methodology and Software Technology (2008)

In this paper, we present a novel approach that establishes a synergy between static and dynamic analyses for detecting memory errors in C code. We extend the standard C type system with effect, region, and host annotations that are relevant to memory management. We define static memory checks to detect memory errors using these annotations. The statically undecidable checks are delegated to dynamic code instrumentation to secure program executions. The static analysis guides its dynamic counterpart by locating instrumentation points and their execution paths. Our dynamic analysis instruments programs with in-lined monitors that observe program executions and ensure safe-fail when encountering memory errors. We prototype our approach by extending the GCC compiler with our type system, a dynamic monitoring library, and code instrumentation capabilities.
A layered architecture for the model-driven development of distributed simulators
Authors: Daniele Gianni, Andrea D'Ambrogio, Giuseppe Iazeolla
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

The development of a distributed simulator requires knowledge and skills that might be unavailable or difficult to acquire. Bringing model-driven approaches to the development of distributed simulators contributes to reduce both the need for specific skills and the development effort. To support this innovative development methodology, we introduce a layered simulation architecture named SimArch that allows to define simulation models that can be transparently transformed into simulation programs ready to be executed in a distributed (or local) mode. SimArch defines layers of services at increasing levels of abstraction on top of the execution environment, thus allowing developers to build distributed simulators without explicit knowledge about the execution environment (local/distributed) and the specific distributed simulation infrastructure (e.g., HLA). In order to show the effectiveness of the proposed approach, SimArch has been provided with an Extended Queueing Network (EQN) simulation language, which has been applied to the development of an example distributed simulator in the computer network domain.
Using Multiple Detectors to Detect the Backoff Time of the Selfish Node in Wireless Mesh Network
Authors: Furong Wang, Yipeng Qu, Baoming Bai, Fan Zhang, Chen Huang
Venue: Proceedings of the 5th international conference on Autonomic and Trusted Computing (2008)

The security of wireless mesh network has been more and more important these days. Although many works have been done to analyze the MAC layer misbehavior such as the selfish node which changes its backoff time to make itself more profits in 802.11 DCF mechanisms, most of them are under the assumption that the backoff time of the sender can be correctly detected. However because of the hidden node problem, misdiagnosing occurs fre-quently. In this paper, we propose a method to detect the backoff time of the sender using multiple detectors. It can avoid the misdiagnosing due to the hidden node problem. We also propose an algorithm to calculate the detection results using weighting parameters get by the probability that the detect nodes will suffer from the hidden node problems. The simulation result shows that the proposed method has a better performance in detecting the backoff time.
Computer Assisted Transcription for Ancient Text Images
Authors: Verónica Romero, Alejandro H. Toselli, Luis Rodríguez, Enrique Vidal
Venue: Proceedings of the 4th international conference on Image Analysis and Recognition (2007)

Paleography experts spend many hours transcribing ancient documents and state-of-the-art handwritten text recognition systems are not suitable for performing this task automatically. We propose here a new interactive, on-line framework which, rather than full automation, aims at assisting the experts in the proper recognition-transcription process; that is, facilitate and speed up the transcription of old documents. This framework combines the efficiency of automatic handwriting recognition systems with the accuracy of the experts, leading to a cost-effective perfect transcription of ancient manuscripts.
Bridging the Sense-Reasoning Gap Using DyKnow: A Knowledge Processing Middleware Framework
Authors: Fredrik Heintz, Piotr Rudol, Patrick Doherty
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

To achieve complex missions an autonomous unmanned aerial vehicle (UAV) operating in dynamic environments must have and maintain situational awareness. This can be achieved by continually gathering information from many sources, selecting the relevant information for current tasks, and deriving models about the environment and the UAV itself. It is often the case models suitable for traditional control, are not sufficient for deliberation. The need for more abstract models creates a sense-reasoning gap. This paper presents DyKnow, a knowledge processing middleware framework, and shows how it supports bridging the gap in a concrete UAV traffic monitoring application. In the example, sequences of color and thermal images are used to construct and maintain qualitative object structures. They model the parts of the environment necessary to recognize traffic behavior of tracked vehicles in real-time. The system has been implemented and tested in simulation and on data collected during flight tests.
Hidden markov model based animal acoustic censusing: learning from speech processing technology
Authors: Michael T. Johnson
Venue:  (2008)

Individually distinct acoustic features have been observed in a wide range of vocally active animal species and have been used to study animals for decades. Only a few studies, however, have attempted to examine the use of acoustic identification of individuals to assess population, either for evaluating the population structure, population abundance and density, or for assessing animal seasonal distribution and trends. This dissertation presents an improved method to acoustically assess animal population. The integrated framework combines the advantages of supervised classification (repertoire recognition and individual animal identification), unsupervised classification (repertoire clustering and individual clustering) and the mark-recapture approach of abundance estimation, either for population structure assessment or population abundance estimate. The underlying algorithm is based on clustering of Hidden Markov Models (HMMs), commonly used in the signal processing and automatic speech recognition community for speaker identification, also referred to as voiceprinting. A comparative study of wild and captive beluga, Delphinapterus leucas, repertoires shows the reliability of the approach to assess the acoustic characteristics (similarity, dissimilarity) of the established social groups. The results demonstrate the feasibility of the method to assess, to track, and to monitor the beluga whale population for potential conservation use. For the censusing task, the method is able to estimate animal population using three possible scenarios. Scenario 1, assuming availability of training data from a specific species with call-type labels and speaker labels, the method estimates total population. Scenario 2, with availability of training data with only call-type labels but no individual identities, the proposed method is able to perform local population estimation. Scenario 3 with availability of a few call-type examples, but no full training set on individual identities, the method is able to perform local population estimation. The experiments performed over the Norwegian ortolan bunting, Emberiza hortulana, data set show the feasibility and effectiveness of the method in estimating ortolan bunting population abundance.
Classification Using Multi-valued Pulse Coupled Neural Network
Authors: Xiaodong Gu
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

This paper introduces how to use multi-valued PCNN (Pulse Coupled Neural Network) proposed in this paper to do classification. 2-dimensional data can be projected onto two-dimensional PCNN locally laterally linked. Different pulse waves generated by training data label different regions corresponding to different classes. The same pulse wave labels the region corresponding to the same class. Meeting of different pulse waves obtains the separatrixes of different classes. In order to differentiate different pulse waves, outputs of neurons in PCNN should be multi-valued. We call networks composed of these neurons multi-valued PCNNs. The number of classes determines the number of output value of each neuron. N-valued PCNN can be used to classify N-1 different classes. Experimental results of the 2-dimensional salmon-weever classification show that the correct recognition rate of test set is 98.11% (3477/3544) when training samples are only 10% of all samples.
Reasoning for Incomplete Authorizations
Authors: Yun Bai
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Authorization plays an important role to control access to the system resources. It enforces security mechanism in compliance with the polices and rules specified by the security strategies. However, the security rules may not be always complete. In certain situations, we need to evaluate and reason about an incomplete security domain. In this paper, we propose an approach to reason under incomplete security domain by extended logic programs, discuss properties of unknown and conflict queries, and solve these problems by defining a procedure of evaluating the logic programs.
Large-Scale Clustering through Functional Embedding
Authors: Frédéric Ratle, Jason Weston, Matthew L. Miller
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent. Compared to methods like spectral clustering our approach solves a single optimization problem, rather than an ad-hoc two-stage optimization approach, does not require a matrix inversion, can easily encode prior knowledge in the set of implementable functions, and does not have an "out-of-sample" problem. Experimental results on both artificial and real-world datasets show the usefulness of our approach.
An Evaluation of Visual Interfaces for Teleoperated Control of Kinematically Redundant Manipulators
Authors: Shantell R. Hinton, Randy C. Hoover, Anthony A. Maciejewski
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

The utilization of robots in hazardous environments for tasks that require high safety and/or precision is significantly increasing. In this work, we consider scenarios where kinematically redundant manipulators are teleoperated to complete tasks specified by point-to-point motion. Teleoperator performance is evaluated based on several different criteria. We build upon previous work on the performance of human/robotic systems by studying the effects of two different visual interfaces. Namely, we compare a world view with an eye-in-hand view and evaluate how these two different visual interfaces affect human performance and task completion.
Improving Recall for Hindi, Telugu, Oromo to English CLIR
Authors: Prasad Pingali, Kula Kekeba Tune, Vasudeva Varma
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper presents the Cross Language Information Retrieval (CLIR) experiments of the Language Technologies Research Centre (LTRC, IIIT-Hyderabad) as part of our participation in the ad-hoc track of CLEF 2007. We present approaches to improve recall of query translation by handling morphological and spelling variations in source language keywords. We also present experiments using query expansion in CLIR using a source language monolingual corpus for Hindi, Telugu and English. We also present the effect of using an Oromo stemmer in Oromo-English CLIR system and report results using the CLEF 2007 dataset.
Methodology for classification of municipalities in the state of Hidalgo, Mexico
Authors: Amaury Caballero, Miriam Alvarez, Jose Luis Abreu, Eduardo Caballero
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

The state of Hidalgo, in Mexico, has been looking for a model to classify 84 municipalities according to certain economic and social parameters. The model will permit the development of policies for improving the conditions of those municipalities that are lagging behind. A previous model was created using statistical methods, applying the factorial analysis. Also was created a fuzzy logic model that permit to compare the municipalities characteristics to some pre-established conditions, and rank them as per their compatibility with these previously imposed conditions. In this paper, a fuzzy model is created dividing the municipalities in three groups as per their development. This method avoids the necessity of making the comparisons to some pre-established conditions, giving a more general classification.
Outlier detection using default reasoning
Authors: Fabrizio Angiulli, Rachel Ben-Eliyahu -- Zohary, Luigi Palopoli
Venue: Artificial Intelligence (2008)

Default logics are usually used to describe the regular behavior and normal properties of domain elements. In this paper we suggest, conversely, that the framework of default logics can be exploited for detecting outliers. Outliers are observations expressed by sets of literals that feature unexpected semantical characteristics. These sets of literals are selected among those explicitly embodied in the given knowledge base. Hence, essentially we perceive outlier detection as a knowledge discovery technique. This paper defines the notion of outlier in two related formalisms for specifying defaults: Reiter's default logic and extended disjunctive logic programs. For each of the two formalisms, we show that finding outliers is quite complex. Indeed, we prove that several versions of the outlier detection problem lie over the second level of the polynomial hierarchy. We believe that a thorough complexity analysis, as done here, is a useful preliminary step towards developing effective heuristics and exploring tractable subsets of outlier detection problems.
Optimization of the Compression Parameters of a Phonocardiographic Telediagnosis System Using Genetic Algorithms
Authors: Juan Martínez-Alajarín, Javier Garrigós-Guerrero, Ramón Ruiz-Merino
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

Auscultation of the heart is a medical technique that still today is used to provide a fast diagnosis about the heart condition. Compression of the heart sounds (or phonocardiogram) is very convenient to reduce bandwidth in telediagnosis systems that aid the physician in the evaluation of the cardiovascular state. The compression algorithm used depends on several parameters, which can take a diversity of values. Genetic algorithms have been used to obtain the optimal set of values for the compression parameters that optimize the performance of the compression for a test set of cardiac recordings. The optimized results were obtained very quickly, and optimal values agreed for (almost) all the test records.
Dynamic Data Path Prediction in Network Virtual Environment
Authors: Sun-Hee Song, Seung-Moon Jeong, Gi-Taek Hur, Sang-Dong Ra
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This research studies real time interaction and dynamic data shared through 3D scenes in virtual network environments. In a distributed virtual environment of client-server structure, consistency is maintained by the static information exchange; as jerks occur by packet delay when updating messages of dynamic data exchanges are broadcasted disorderly, the network bottleneck is reduced by predicting the movement path by using the Dead-reckoning algorithm. The shared dynamic data of the 3D virtual environment is implementation using the VRML EAI.
Voronoi Games on Cycle Graphs
Authors: Marios Mavronicolas, Burkhard Monien, Vicky G. Papadopoulou, Florian Schoppmann
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

In a Voronoi game, each of a finite number of players chooses a point in some metric space. The utility of a player is the total measure of all points that are closer to him than to any other player, where points equidistant to several players are split up evenly among the closest players. In a recent paper, Dürr and Thang (2007) considered discrete Voronoi games on graphs, with a particular focus on pure Nash equilibria. They also looked at Voronoi games on cycle graphs with n nodes and k players. In this paper, we prove a new characterization of all Nash equilibria for these games. We then use this result to establish that Nash equilibria exist if and only if $k \leq \frac{2n}3$ or k ¿ n. Finally, we give exact bounds of $\frac 94$ and 1 for the prices of anarchy and stability, respectively.
Design and Optimization of IIR Digital Filters with Non-standard Characteristics Using Continuous Ant Colony Optimization Algorithm
Authors: Adam Slowik, Michal Bialko
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

In this paper method of design and optimization of stable IIR digital filters with non-standard amplitude characteristics using continuous ant colony optimization algorithm ACO R is presented. In proposed method (named ACO-IIRFD) dynamical changes of parameters in designed filters are introduced. Due to these dynamical changes of filter parameters, design of IIR digital filters with small deviations between designed filter characteristics and assumed characteristics is possible. Three IIR digital filters with amplitude characteristics: linearly-falling, linearly-growing, and non-linearly-growing, which can have application in amplitude equalizers, are designed using proposed method.