ppxscal/embedding_network huggingface dataset:
Mining Temporal Association Patterns under a Similarity Constraint
Authors: Jin Soung Yoo, Shashi Shekhar
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

We study the problem of mining all associated itemsets whose prevalence variations are similar to a given reference sequence from temporal databases. The discovered temporal association patterns can reveal interesting relationships of itemsets which co-occur with a particular event over time. A user-defined subset specification which consists of a reference sequence, a similarity function, and a dissimiliarty threshold is used for defining interesting temporal patterns and guiding the similarity search. We develop algorithms with exploring interesting properties for efficiently finding the similar temporal association patterns. Experimental results show that the proposed algorithms are efficient than a naive approach.
Using the Sensor Web to Detect and Monitor the Spread of Vegetation Fires in Southern Africa
Authors: Andrew Terhorst, Deshendran Moodley, Ingo Simonis, Philip Frost, Graeme Mcferren, Stacey Roos, Frans Bergh
Venue: GeoSensor Networks: Second International Conference, GSN 2006, Boston, MA, USA, October 1-3, 2006, Revised Selected and Invited Papers (2008)

Key concepts in disaster response are level of preparedness, response times, sustaining the response and coordinating the response. Effective disaster response requires a well-developed command and control framework that promotes the flow of information. The Sensor Web is an emerging technology concept that can enhance the tempo of disaster response. We describe how a satellite-based system for regional vegetation fire detection is being evolved into a fully-fledged Sensor Web application.
A Context-Free Process as a Pushdown Automaton
Authors: J. C. Baeten, P. J. Cuijpers, P. J. Tilburg
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

A well-known theorem in automata theory states that every context-free language is accepted by a pushdown automaton. We investigate this theorem in the setting of processes, using the rooted branching bisimulation and contrasimulation equivalences instead of language equivalence. In process theory, different from automata theory, interaction is explicit, so we realize a pushdown automaton as a regular process communicating with a stack.
Compressed Hierarchical Mining of Frequent Closed Patterns from Dense Data Sets
Authors: Liping Ji, Kian-Lee Tan, Anthony Tung
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

This paper addresses the problem of finding frequent closed patterns (FCPs) from very dense datasets. We introduce two compressed hierarchical FCP mining algorithms C-Miner and B-Miner. The two algorithms compress the original mining space, hierarchically partition the whole mining task into independent subtasks and mine each subtask progressively. The two algorithms adopt different task-partitioning strategies: CMiner partitions the mining task based on Compact Matrix Division whereas B-Miner partitions the task based on Base Rows Projection. The compressed hierarchical mining algorithms enhance the mining efficiency and facilitate a progressive refinement of results. Moreover, because the subtasks can be mined independently, C-Miner and B-Miner can be readily parallelized without incurring significant communication overhead. We have implemented C-Miner and B-Miner, and our performance study on synthetic datasets and real dense microarray datasets shows their effectiveness over existing schemes. We also report experimental results on parallel versions of these two methods.
Strategy Construction for Parity Games with Imperfect Information
Authors: Dietmar Berwanger, Krishnendu Chatterjee, Laurent Doyen, Thomas A. Henzinger, Sangram Raje
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

We consider imperfect-information parity games in which strategies rely on observations that provide imperfect information about the history of a play. To solve such games, i.e. to determine the winning regions of players and corresponding winning strategies, one can use the subset construction to build an equivalent perfect-information game. Recently, an algorithm that avoids the inefficient subset construction has been proposed. The algorithm performs a fixed-point computation in a lattice of antichains, thus maintaining a succinct representation of state sets. However, this representation does not allow to recover winning strategies.In this paper, we build on the antichain approach to develop an algorithm for constructing the winning strategies in parity games of imperfect information. We have implemented this algorithm as a prototype. To our knowledge, this is the first implementation of a procedure for solving imperfect-information parity games on graphs.
Enterprise mobile product strategy using scenario planning
Authors: Sami Muneer, Chetan Sharma
Venue: Information-Knowledge-Systems Management (2008)

The Mobile industry is changing at a rapid pace and so is the behavior of enterprise workforce which uses mobile technologies. When planning for a long-term product roadmap, one has to consider a myriad of evolution trends and forecasts to determine the probable list of product functionality and their introduction timing in the lifecycle of the product. One has to look at the technology trends by market, the competitive landscape, and the mobile worker adoption trends. However, one can only come up with a prioritized list of capabilities by taking into context the company's own core competencies, skill sets, and overall mission. This paper looks at how mobile product companies can use scenario-planning methodology to formulate their product strategy and roadmap.
Reversibility analysis for Petri nets by using T-invariants
Authors: Hanife Apayd n Ozkan, Ayd n. Aybar
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

In this work, we propose a method, based on T-invariants, to analyse reversibility of Petri nets. Proposed method determines all possible transition sequences, corresponding to minimal T-invariants. Then a reversible set is constructed by using these sequences. A corresponding pseudo-code algorithm of the method is written and it is implemented by using Matlab.
Encoding the Program Correctness Proofs as Programs in PCC Technology
Authors: Heidar Pirzadeh, Danny Dubé
Venue: Proceedings of the 2008 Sixth Annual Conference on Privacy, Security and Trust (2008)

One of the key issues with the practical applicability of Proof-Carrying Code (PCC) and its related methods is the difficulty in communicating and storing the proofs which are inherently large. The approaches proposed to alleviate this, suffer from drawbacks of their own especially the enlargement of the Trusted Computing Base, in which any bug may cause an unsafe program to be accepted. We propose a generic extended PCC framework (EPCC) in which, instead of the proof, a proof generator for the program in question is transmitted. This framework enables the execution of the proof generator and the recovery of the proof on the consumer side in a secure manner.
Trajectories of goods in distributed allocation
Authors: Yann Chevaleyre, Ulle Endriss, Nicolas Maudet
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

Distributed allocation mechanisms rely on the agents' autonomous (and supposedly rational) behaviour: states evolve as a result of agents contracting deals and exchanging resources. It is no surprise that restrictions on potential deals also restrict the reachability of some desirable states, for instance states where goods are efficiently allocated. In particular topological restrictions make any attempt to guarantee asymptotic convergence to an optimal allocation impossible in most cases. In this paper, we concentrate on the dynamics of such systems; more precisely we study the trajectories of goods in such iterative reallocative processes. Our first contribution is to propose an upper bound on the length of the trajectories of goods, when agent utility functions are modular. The second innovative aspect of the paper is then to discuss how this affects, on average, the quality of the states that are reached. Finally, a preliminary study of the non-modular case is proposed, examining how synergetic effects between items can affect their trajectories.
Tableaux with Dynamic Filtration for Layered Modal Logics
Authors: Olivier Gasquet, Bilal Said
Venue: Proceedings of the 16th international conference on Automated Reasoning with Analytic Tableaux and Related Methods (2007)

In this paper we prove that the satisfiability problem for the class of what we call layered modal logics (LML) is in NEXPTIME, and hence, is decidable. Roughly, LML are logics characterized by semantical properties only stating the existence of possible worlds that are in some sense "further" than the other. Typically, they include various confluence-like properties, while they do not include density-like properties. Such properties are of interest for formalizing the interaction between dynamic and epistemic modalities for rational agents for example. That these logics are decidable may be not very surprising, but we show that they are all in NEXPTIME, some of them being known to be NEXPTIME-complete. For this, we give a sound and complete tableau calculus and prove that open tableaux are of exponential size. This cannot be done by using usual filtration which cannot cope with confluence. We introduce here a new technique we call dynamic filtration that allows to filtrate worlds one layer at a time keeping the total number of nodes within an exponential bound.
Configurable editing of XML-based variable-data documents
Authors: John Lumley, Roger Gimson, Owen Rees
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

Variable data documents can be considered as functions of their bindings to values, and this function could be arbitrarily complex to build strongly-customised but high-value documents. We outline an approach for editing such documents from example instances, which is highly configurable in terms of controlling exactly what is editable and how, capable of being used with a wide variety of XML-based document formats and processing pipelines, if certain reasonable properties are supported and can generate appropriate editors automatically, including web-service deployment.
3D LIDAR Data Application for Urban Morphogenesis Multi-agent Vector Based Geosimulation
Authors: Vitor Silva, Corinne Plazanet, Cláudio Carneiro, François Golay
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

In this paper we present an application of airborne light detection and ranging (LIDAR) data analysis for computation of buildings visibility and sunshine in the context of urban morphogenesis geosimulation. The interdisciplinary project between architects and geomaticians aims to provide a simulation model based upon dynamic computation of building agents' satisfaction degree, incorporating visibility and sunshine analysis results derived from raw LIDAR data. For the buildings in study, the visibility and sunshine analysis are undertaken at different heights along its façades, in order to obtain a classification as input for the multi-agent vector urban modelling system.
Real time flexible manufacturing system: analytical description
Authors: Medel José de Jesú, Hernández Gabriel, Guevara Pedro
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

The digital flexible manufacturing systems generally require scheduling sequence operations, considering in this case the sequence operations respect to each process selected previously. The main problem in this kind system is generally observed between multiple operation sequences; such that, the production process has multiple undesirable breakpoints, decreasing the effectiveness either, then in this case the production requirements hasn't fulfill. In this sense, a novel analysis about the properties and entities respect to digital flexible manufacturing systems without forget its time conditions, gives the last part a good enough elements for to reduce these mistakes into automatic production. In formal sense, we developed a set of theoretical concepts needed into scheduling task-cell operations in base to real time descriptions in the sense of digital flexible manufacturing systems. Allowing integrate both concepts into real time manufacturing systems. Exposing in block schemes in illustrative form, the basic description about this topic. Concluding this paper with basic references that gave the support required to develop this topic.
Quantum-Based Belief Merging
Authors: Laurent Perrussel, Jerusa Marchi, Guilherme Bittencourt
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

Belief merging aims at building a common belief set issued from multiple belief sets. The quality of the resulting set is usually considered in terms of a closeness criterion between the initial belief sets and an integrity constraint with respect to the aim of the merging procedure. The notion of distance between belief sets is thus a crucial issue when we face the merging problem. The aim of this paper is to revisit belief merging operators, notably the majority and the arbitration operators, with the help of a new distance that considers, in a syntactical way, the importance of each symbol in the belief set.
Tailoring and the Efficiency of Information Seeking
Authors: Nathalie Colineau, Cécile Paris
Venue: Proceedings of the 11th international conference on User Modeling (2007)

We present an empirical study assessing the impact of tailoring on information seeking tasks. Our aim was to evaluate whether providing tailored information would help people find the information they need more quickly and more accurately. Our results show that tailored documents have an impact on information seeking, at least when the information to be found is spread over a number of sources and needs to be synthesised.
Molecular Motors: Design, Mechanism, and Control
Authors: Debashish Chowdhury
Venue: Computing in Science and Engineering (2008)

Theoretical modeling and computer simulations of molecular motors provide insight that engineers can exploit to design and control artificial nanomotors.
Declarative Semantics for Revision Programming and Connections to Active Integrity Constraints
Authors: Luciano Caroprese, Mirosław Truszczyński
Venue: Proceedings of the 11th European conference on Logics in Artificial Intelligence (2008)

We investigate revision programming, a formalism to describe constraints on belief sets (databases, knowledge bases), and to specify preferred ways to enforce them. We propose several semantics for revision programs combining ideas from logic programming and active integrity constraints, a formalism to model preferred ways to enforce integrity constraints on databases. We present results on the complexity of the semantics we introduce. We also show that all these semantics are invariant under "shifting". Finally, we prove that from the perspective of a broad semantic landscape of revision programming, there is a direct correspondence between revision programs and active integrity constraints.
Simulation of Multiphysics Multiscale Systems: Introduction to the ICCS'2007 Workshop
Authors: Valeria V. Krzhizhanovskaya, Shuyu Sun
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

Modeling and simulation of multiphysics multiscale systems poses a grand challenge to computational science. To adequately simulate numerous intertwined processes characterized by different spatial and temporal scales (often spanning many orders of magnitude), sophisticated models and advanced computational techniques are required. The aim of the workshop on Simulation of Multiphysics Multiscale Systems (SMMS) is to facilitate the progress in this multidisciplinary research field. We provide an overview of the recent trends and latest developments, with special emphasis on the research projects selected for presentation at the SMMS'2007 workshop.
Best-First AND/OR Search for 0/1 Integer Programming
Authors: Radu Marinescu, Rina Dechter
Venue: Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2007)

AND/OR search spaces are a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sensitivity to the structure of the model, which can translate into exponential time savings for search algorithms. In this paper we introduce an AND/OR search algorithm that explores a context-minimal AND/OR search graph in a best-first manner for solving 0/1 Integer Linear Programs (0/1 ILP). We also extend to the 0/1 ILP domain the depth-first AND/OR Branch-and-Bound search with caching algorithm which was recently proposed by [1] for solving optimization tasks in graphical models. The effectiveness of the best-first AND/OR search approach compared to depth-first AND/OR Branch-and-Bound search is demonstrated on a variety of benchmarks for 0/1 ILPs, including instances from the MIPLIB library, real-world combinatorial auctions, random uncapacitated warehouse location problems and MAX-SAT instances.
Development of a Cascade Processing Method for Microarray Spot Segmentation
Authors: Antonis Daskalakis, Dionisis Cavouras, Panagiotis Bougioukos, Spiros Kostopoulos, Ioannis Kalatzis, George C. Kagadis, George Nikiforidis
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

A new method is proposed for improving microarray spot segmentation for gene quantification. The method introduces a novel combination of three image processing stages, applied locally to each spot image: i/ Fuzzy C-Means unsupervised clustering, for automatic spot background noise estimation, ii/ power spectrum deconvolution filter design, employing background noise information, for spot image restoration, iii/ Gradient-Vector-Flow (GVF-Snake), for spot boundary delineation. Microarray images used in this study comprised a publicly available dataset obtained from the database of the MicroArray Genome Imaging Clustering Tool website. The proposed method performed better than the GVF-Snake algorithm (Kullback-Liebler metric: 0.0305 bits against 0.0194 bits) and the SPOT commercial software (pairwise mean absolute error between replicates: 0.234 against 0.303). Application of efficient adaptive spot-image restoration on cDNA microarray images improves spot segmentation and subsequent gene quantification.
Spam Detection with Complex-Valued Neural Network Using Behavior-Based Characteristics
Authors: Jun Hu, Zhitang Li, Zhengbing Hu, Dezhong Yao, Junfeng Yu
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

The paper proposes the use of the Complex-Valued Neural Network to detect spam. The main contributions of this work are two-fold. First, we present a new model based on the CVNN for classifying personal E-mails. We changed the input of the email into 2-dimensional vector. The Complex-Valued Neural Network is superior for handling 2-dimensional vector data stream, because the input of the complex-valued neural network has real part and imaginary part. Second, the Behavior-based Characteristics are extracted as most important features of the E-mail. The results reveal that the proposed technology is reliable, efficient and scalable.
Call Admission Control Using Neural Network in Wireless Multimedia Networks
Authors: Yufeng Ma, Shenguang Gong
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Scarcity of the spectrum resource and mobility of users make Quality-of-Service (QoS) provision a critical issue in wireless multimedia networks. This paper uses neural network as call admission controller to perform call admission decision. A performance measurement is formed as a weighted linear function of new call and handoff call blocking probabilities of each service class. Simulation compares the neural network with complete sharing policy. Simulation results show that neural network has a better performance in terms of average blocking criterion.
On the Use of Kappa Coefficients to Measure the Reliability of the Annotation of Non-acted Emotions
Authors: Zoraida Callejas, Ramón López-Cózar
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

In this paper we study the impact of three main factors on measuring the reliability of the annotation of non-acted emotions: the annotator biases, the similarity between the classified emotions, and the usage of contextual information during the annotation. We employed a corpus collected from real interactions between users and a spoken dialogue system. The user utterances were classified by nine non-expert annotators into four categories. We discuss the problems that the nature of non-acted emotional corpora impose in evaluating the reliability of the annotations using Kappa coefficients. Although deeply affected by the so-called paradoxes of Kappa coefficients, our study shows how taking into account context information and similarity between emotions helps to obtain values closer to the maximum agreement rates attainable, and allow the detection of emotions which are expressed more subtly by the users.
User Assisted Substructure Extraction in Molecular Data Mining
Authors: Burcu Yılmaz, Mehmet Göktürk, Natalie Shvets
Venue: Proceedings of the 3rd international conference on Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry (2008)

In molecular fragments mining, scientists use both manual techniques and pure computer based methods. In this paper, we propose a novel molecular fragment mining approach that incorporates interactive user assistance to speed up and increase the success rates in traditional fragment mining processes. The proposed approach visualizes 3D molecular data in 2D form that can be easily interpreted by a human expert who evaluates and filters the 2D molecular images manually. The proposed approach differs from others in literature as it does not search substructures including specific atoms like graph mining methods do. Instead, user assisted approach highlights significant substructures with specific properties and topologies graphically. Initial experiments indicate that by the use of user assisted approach, active and inactive fragments of compounds are quickly determined for drug design with high success rates.
Research on Update Service in Learning Resources Management System
Authors: Yongjun Jing, Jie Jian, Shaochun Zhong, Xin Li
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

Resources update service is a pivotal problem in the construction of learning resources and the development of e-learning. Aiming at this problem, this paper presents a Distributed Push System of Learning Resources (DPSLR). The schedule between servers and users is a M ulti-objective Optimization Problem (MOP ) in this system. We discuss the scheduling model of servers and users, and use an Ant Colony Optimization (ACO) to solve the MOP. We have developed a model to estimate the efficiency of the new resources update service.