ppxscal/embedding_network huggingface dataset:
Learning dependency relations of Japanese compound functional expressions
Authors: Takehito Utsuro, Takao Shime, Masatoshi Tsuchiya, Suguru Matsuyoshi, Satoshi Sato
Venue: Proceedings of the Workshop on a Broader Perspective on Multiword Expressions (2007)

This paper proposes an approach of processing Japanese compound functional expressions by identifying them and analyzing their dependency relations through a machine learning technique. First, we formalize the task of identifying Japanese compound functional expressions in a text as a machine learning based chunking problem. Next, against the results of identifying compound functional expressions, we apply the method of dependency analysis based on the cascaded chunking model. The results of experimental evaluation show that, the dependency analysis model achieves improvements when applied after identifying compound functional expressions, compared with the case where it is applied without identifying compound functional expressions.
A General Approach to the Verification of Cryptographic Protocols Using Answer Set Programming
Authors: James P. Delgrande, Torsten Grote, Aaron Hunter
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

We introduce a general approach to cryptographic protocol verification based on answer set programming. In our approach, cryptographic protocols are represented as extended logic programs where the answer sets correspond to traces of protocol runs. Using queries, we can find attacks on a protocol by finding the answer sets for the corresponding logic program. Our encoding is modular, with different modules representing the message passing environment, the protocol structure and the intruder model. We can easily tailor each module to suit a specific application, while keeping the rest of the encoding constant. As such, our approach is more flexible and elaboration tolerant than related formalizations. The present system is intended as a first step towards the development of a compiler from protocol specifications to executable programs; such a compiler would make verification a completely automated process. This work is also part of a larger project in which we are exploring the advantages of explicit, declarative representations of protocol verification problems.
Adaptive traitor tracing with Bayesian networks
Authors: Philip Zigoris, Hongxia Jin
Venue: Proceedings of the 19th national conference on Innovative applications of artificial intelligence - Volume 2 (2007)

The practical success of broadcast encryption hinges on the ability to (1) revoke the access of compromised keys and (2) determine which keys have been compromised. In this work we focus on the latter, the so-called traitor tracing problem. We present an adaptive tracing algorithm that selects forensic tests according to the information gain criteria. The results of the tests refine an explicit, Bayesian model of our beliefs that certain keys are compromised. In choosing tests based on this criteria, we significantly reduce the number of tests, as compared to the state-of-the-art techniques, required to identify compromised keys. As part of the work we developed an efficient, distributable inference algorithm that is suitable for our application and also give an efficient heuristic for choosing the optimal test.
Geometric Tolerances Information Modeling for Integrated Manufacturing Processes
Authors: Chao Yan, Xu Ruifeng, Wu Liqun
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Tolerance information plays a critical role in manysteps of the product life cycle and especially important due tothe advances in Internet technologies and increasingintegration requirements from industry. In this paper,geometric tolerances information in manufacturing process(IMP) is studied, and the layered conformance level ofgeometric tolerances is established according to ASME Y14.5-1994, STEP and DMIS. An EXPRESS-G data model ofgeometric tolerance information in IMP is established. TheXML language is used to represent and program the geometrictolerances information in IMP.
Context-Aware Data and IT Services Collaboration in E-Business
Authors: Khouloud Boukadi, Chirine Ghedira, Zakaria Maamar, Djamal Benslimane, Lucien Vincent
Venue: Transactions on Large-Scale Data- and Knowledge-Centered Systems I (2009)

This paper discusses the use of services in the design and development of adaptable business processes, which should let organizations quickly react to changes in regulations and needs. Two types of services are adopted namely Data and Information Technology. A data service is primarily used to hide the complexity of accessing distributed and heterogeneous data sources, while an information technology service is primarily used to hide the complexity of running requests that cross organizational boundaries. The combination of both services takes place under the control of another service, which is denoted by service domain. A service domain orchestrates and manages data and information technology services in response to the events that arise and changes that occur. This happens because service domains are sensible to context. Policies and aspect-oriented programming principles support the exercise of packaging data and information technology services into service domains as well as making service domains adapt to business changes.
Time-BPMN
Authors: Denis Gagne, André Trudel
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

We present Time-BPMN which is an extension to the current version of the Business Process Modeling Notation (BPMN). Time-BPMN captures the temporal perspective of business processes. This extension deals with the various temporal constraints and dependencies that may occur while characterizing real world business processes. Time-BPMN allows for the specification and depiction of temporal constraints and dependencies within a BPMN diagram. It not only extends, but also simplifies certain existing temporal BPMN constructs. With our extension, BPMN becomes expressive enough to account for a very large set of real world business processes that are time dependent.
On the construction of analytic solutions for a diffusion-reaction equation with a discontinuous switch mechanism
Authors: F. J. Vermolen, E. Javierre
Venue: Journal of Computational and Applied Mathematics (2009)

The existence of waiting times, before boundary motion sets in, for a diffusion-diffusion reaction equation with a discontinuous switch mechanism, is demonstrated. Limit cases of the waiting times are discussed in mathematical rigor. Further, analytic solutions for planar and circular wounds are derived. The waiting times, as predicted using these analytic solutions, are perfectly between the derived bounds. Furthermore, it is demonstrated by both physical reasoning and mathematical rigor that the movement of the boundary can be delayed once it starts moving. The proof of this assertion resides on continuity and monotonicity arguments. The theory sustains the construction of analytic solutions. The model is applied to simulation of biological processes with a threshold behavior, such as wound healing or tumor growth.
Social Knowledge-Driven Music Hit Prediction
Authors: Kerstin Bischoff, Claudiu S. Firan, Mihai Georgescu, Wolfgang Nejdl, Raluca Paiu
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

What makes a song to a chart hit? Many people are trying to find the answer to this question. Previous attempts to identify hit songs have mostly focused on the intrinsic characteristics of the songs, such as lyrics and audio features. As social networks become more and more popular and some specialize on certain topics, information about users' music tastes becomes available and easy to exploit. In the present paper we introduce a new method for predicting the potential of music tracks for becoming hits, which instead of relying on intrinsic characteristics of the tracks directly uses data mined from a music social network and the relationships between tracks, artists and albums. We evaluate the performance of our algorithms through a set of experiments and the results indicate good accuracy in correctly identifying music hits, as well as significant improvement over existing approaches.
Intrusion Detection in Circular Frustrated Systems: An Eminently Parallel Processing Algorithm
Authors: Patricia Mostardinha, Fernão Vistulo Abreu
Venue: Proceedings of the 8th International Conference on Unconventional Computation (2009)

The cellular frustration framework (CFF) is a new approach capable of performing single intrusion detections in large populations of very diverse agents[1]. A classical approach in the literature consists in defining a set of detectors where each one surveys a sub-domain of the space of patterns that characterize non-self agents. The intrusion detection task is computationally demanding because it requires matching every new agent against all possible detectors. Also the set of detectors has to be carefully selected to avoid false positive and false negative detections. In these approaches the outcome of detection events depends only on the two agents that interact and is essentially a serial processing computation.Cellular frustration uses a different conceptual approach to solve intrusion detection tasks. First it is assumed that any agent can interact and potentially react with any other agent in the system. However, instead of instantaneous reactions, agents perform time lasting decisions, during which they interact with other agents and can change pair to optimize their previous choices. Reactions, (i.e. the triggering of detection events) only take place if agents form stable interactions that last longer than a characteristic time. False positive detections, which lead to elimination of self agents, can thus be avoided in populations that are organized in a highly frustrated dynamics where all agents never establish sufficiently long interactions. Furthermore, the population should be maximally frustrated so that intruders will always produce more stable interactions that are used to signal detection events.In this presentation we discuss this general framework. In particular we discuss how it is possible to organize a large population (e.g. with 1000 different agents) so that any intruder will always be detected because it will always perform longer interactions than self agents. We also show that even if an intruder copies exactly another self agent, then it cannot spread in the population, as its outgrowth would change the dynamical interactions and lower its frustration. This corresponds to a form of homeostatic response.As detection events in the CFF are triggered as a result of an emergent property of the dynamical system, intrusion detection becomes a whole system property that requires an inherently parallel processed computation.
On the decidability of role mappings between modular ontologies
Authors: Jie Bao, George Voutsadakis, Giora Slutzki, Vasant Honavar
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

Many semantic web applications require support for mappings between roles (or properties) defined in multiple independently developed ontology modules. Distributed Description Logics (DDL) and Package-based Description Logics (P-DL) offer two alternative logical formalisms that support such mappings. We prove that (a) variants of DDL that allow negated roles or cardinality restrictions in bridge rules or inverse bridge rules that connect ALC ontologies are undecidable; (b) a variant of P-DL ALCHIO(¬)P that supports role mappings between ontology modules expressed in ALCHIO(¬) is decidable.
End-of-life impact reduction through analysis and redistribution of disassembly depth: A case study in electronic device redesign
Authors: Fabio Giudice, Mohamad Kassem
Venue: Computers and Industrial Engineering (2009)

The present paper introduces a structured method for the analysis and reconfiguration of the disassembly depth distribution of components making up a constructional system, with the aim of obtaining a generalized improvement in ease of disassembly in relation to the requirements of recovery at end-of-life. As evidenced in the report of the case study proposed, the method and associated tools provide information regarding the criticality of a system and make it possible to direct an intervention modifying the principal design parameters (characteristics of layout, shapes of components, and types of junction systems) in a way that improves the efficiency of disassembly. This comes off through a reasoned redistribution of the disassembly depth of components, searching for concordance between the ease of disassembly and the real need for it, and favoring the disassemblability of those parts of the system with higher environmental impact content, to recoup it at end-of-life.
Investigation of DCSK Application in L-PLC Based on Channel Chaotic Characteristic
Authors: Zhenchao Wang, Shibing Zhang, Huiran Hou
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

This paper studies the performance of differential chaos shift keying (DCSK) in L-PLC based on the investigation results of channel chaotic characteristic. Firstly, the correlation dimension, largest Lyapunov exponent and Kolmogorov entropy of noise series measured from the L-PLC channel are calculated under various operating conditions. The results prove that L-PLC channel is a chaotic system. Then the theoretical anti-noise performance of DCSK is analyzed based on the correlation between measured noise and chaotic carrier. Thirdly, the simulation is carried out in the AWGN, Rayleigh fading and chaotic noise measured from L-PLC networks channel models respectively. The simulation results show that the BER performance of DCSK is superior to the traditional scheme, and the DCSK scheme has a good capacity to restrain the chaotic noise and distortion of the L-PLC channel
The Evaluation Model of College Students' News Sensitivity Based on the Unascertained Measure
Authors: Yanming Qi, Wang Chang-long
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

In order to bring up college students’ news sensitivity at present,it has become increasingly important to establish evaluation index system of college students’ news sensitivity. A new method of quantitative and qualitative combining has been put forward to evaluate college students’ news sensitivity,establish the evaluation model based on the unascertained measure and index categorization weight withinformation entropy . The example shows that it has high theoretical and practical value with the method of unascertained measure to evaluate college students’ news sensitivity.
Samuel meets Amarel: automating value function approximation using global state space analysis
Authors: Sridhar Mahadevan
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

Most work on value function approximation adheres to Samuel's original design: agents learn a task-specific value function using parameter estimation, where the approximation architecture (e.g, polynomials) is specified by a human designer. This paper proposes a novel framework generalizing Samuel's paradigm using a coordinate-free approach to value function approximation. Agents learn both representations and value functions by constructing geometrically customized task-independent basis functions that form an orthonormal set for the Hilbert space of smooth functions on the underlying state space manifold. The approach rests on a technical result showing that the space of smooth functions on a (compact) Riemanian manifold has a discrete spectrum associated with the Laplace-Beltrami operator. In the discrete setting, spectral analysis of the graph Laplacian yields a set of geometrically customized basis functions for approximating and decomposing value functions. The proposed framework generalizes Samuel's value function approximation paradigm by combining it with a formalization of Saul Amarel's paradigm of representation learning through global state space analysis.
Learning a lexicalized grammar for German
Authors: Sandra Kübler
Venue: Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning (1998)

In syntax, the trend nowadays is towards lexicalized grammar formalisms. It is now widely accepted that dividing words into wordclasses may serve as a labor-saving mechanism - but at the same time, it discards all detailed information on the idiosyncratic behavior of words. And that is exactly the type of information that may be necessary in order to parse a sentence. For learning approaches, however, lexicalized grammars represent a challenge for the very reason that they include so much detailed and specific information, which is difficult to learn. This paper will present an algorithm for learning a link grammar of German. The problem of data sparseness is tackled by using all the available information from partial parses as well as from an existing grammar fragment and a tagger. This is a report about work in progress so there are no representative results available yet.
A Secure Framework for Location Verification in Pervasive Computing
Authors: Dawei Liu, Moon-Chuen Lee, Dan Wu
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

The way people use computing devices has been changed in some way by the relatively new pervasive computing paradigm. For example, a person can use a mobile device to obtain its location information at anytime and anywhere. There are several security issues concerning whether this information is reliable in a pervasive environment. For example, a malicious user may disable the localization system by broadcasting a forged location, and it may impersonate other users by eavesdropping their locations. In this paper, we address the verification of location information in a secure manner. We first present the design challenges for location verification, and then propose a two-layer framework VerPer for secure location verification in a pervasive computing environment. Real world GPS-based wireless sensor network experiments confirm the effectiveness of the proposed framework.
On the Spatial Distribution of Local Non-parametric Facial Shape Descriptors
Authors: Olli Lahdenoja, Mika Laiho, Ari Paasio
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

In this paper we present a method to form pattern specific facial shape descriptors called basis-images for non-parametric LBPs (Local Binary Patterns) and some other similar face descriptors such as Modified Census Transform (MCT) and LGBP (Local Gabor Binary Pattern). We examine the distribution of different local descriptors among the facial area from which some useful observations can be made. In addition, we test the discriminative power of the basis-images in a face detection framework for the basic LBPs. The detector is fast to train and uses only a set of strictly frontal faces as inputs, operating without non-faces and bootstrapping. The face detector performance is tested with the full CMU+MIT database.
Delay-interval dependent robust stability criteria for stochastic neural networks with linear fractional uncertainties
Authors: P. Balasubramaniam, S. Lakshmanan, R. Rakkiyappan
Venue: Neurocomputing (2009)

In this paper, we study the delay-interval dependent robust stability criteria for stochastic neural networks with linear fractional uncertainties. The time-varying delay is assumed to belong to an interval and is a fast time-varying function. The uncertainty under consideration includes linear fractional norm-bounded uncertainty. Based on the new Lyapunov-Krasovskii functional, some inequality techniques and stochastic stability theory, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities. Finally, some numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed LMI conditions.
Loci: Simple Thread-Locality for Java
Authors: Tobias Wrigstad, Filip Pizlo, Fadi Meawad, Lei Zhao, Jan Vitek
Venue: Proceedings of the 23rd European Conference on ECOOP 2009 --- Object-Oriented Programming (2009)

This paper presents a simple type system for thread-local data in Java. Classes and types are annotated to express thread-locality and unintended leaks are detected at compile-time. The system, called Loci, is minimal, modular and compatible with legacy code. The only change to the language is the addition of two new metadata annotations. We implemented Loci as an Eclipse plug-in and used it to evaluate our design on a number of benchmarks. We found that Loci is compatible with how Java programs are written and that the annotation overhead is light thanks to a judicious choice of defaults.
John D. Musa
Authors: William Everett, James Cusick, Laurie Williams
Venue: IEEE Software (2009)

This article looks back at the life of John Musa, known for his work in software reliability engineering.
Cognitive Workload as a Predictor of Student Pilot Performance
Authors: Nathan F. Tilton, Ronald Mellado Miller
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

This study examined the relationship between cognitive task load and performance in pilot training in a civilian pilot training program. It was found that the NASA task load index was indicative of training success, with the most successful pilot trainees showing the most cognitive task load and vice versa for those performing poorly. The implications for this finding are discussed as is their relation to possible advantages to military pilot trainees over their civilian counterparts.
Speech summarization without lexical features for Mandarin broadcast news
Authors: Jian Zhang, Pascale Fung
Venue: Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX (2007)

We present the first known empirical study on speech summarization without lexical features for Mandarin broadcast news. We evaluate acoustic, lexical and structural features as predictors of summary sentences. We find that the summarizer yields good performance at the average F-measure of 0.5646 even by using the combination of acoustic and structural features alone, which are independent of lexical features. In addition, we show that structural features are superior to lexical features and our summarizer performs surprisingly well at the average F-measure of 0.3914 by using only acoustic features. These findings enable us to summarize speech without placing a stringent demand on speech recognition accuracy.
Sensor Nodes Localization Algorithm in Noisy Environments
Authors: Antoine Amosse, Ioannis Lambadaris, Jérôme Talim
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

Wireless Sensor Networks are more and more frequently integrated into many civil and military applications. Those applications rely on the system to determine accurately the location of the sensor nodes. Most existing localization algorithms are not efficient in noisy environments and assume that the nodes are already configured appropriately for the local environment. In this paper, we propose a novel method to determine the position of the nodes in a noisy environment. The preliminary step of our solution consists of characterizing the local environment parameters. The localization step implements an iterative procedure to determine the nodes position. The numerical results derived from the simulations show the robustness of our method when compared the Concentric Anchor Beacon (CAB) algorithm, one of the most efficient techniques. We also address the computation time, as a performance metric.