ppxscal/embedding_network huggingface dataset:
Anomalous Taint Detection
Authors: Lorenzo Cavallaro, R. Sekar
Venue: Proceedings of the 11th international symposium on Recent Advances in Intrusion Detection (2008)

We propose anomalous taint detection, an approach that combines fine-grained taint tracking with learning-based anomaly detection. Anomaly detection is used to identify behavioral deviations that manifest when vulnerabilities are exercised. Fine-grained taint-tracking is used to target the anomaly detector on those aspects of program behavior that can be controlled by an attacker. Our preliminary results indicate that the combination increases detection accuracy over either technique, and promises to offer better resistance to mimicry attacks.
Filtering Algorithm for Agent-Based Incident Communication Support in Mobile Human Surveillance
Authors: Duco N. Ferro, Catholijn M. Jonker
Venue: Proceedings of the 6th German conference on Multiagent System Technologies (2008)

This paper presents an ontology and a filtering algorithm used in an agent-based system to support communication in case of incidents in the mobile human surveillance domain. In that domain reaching the right people as soon as possible is of the essence when incidents occur. The main goal of our efforts is to significantly reduce the response time in case of incidents by proposing and setting up the communication to the right people. Experimental results show that this can reduce the response time by more than 50%, e.g., from 40 to 20 minutes. To continuously improve the accuracy of the proposed communications, the agent-based system uses feedback mechanisms. An implementation of this system, ASK-ASSIST, has been deployed at a mobile human surveillance company.
Resolution-Like Theorem Proving for High-Level Conditions
Authors: Karl-Heinz Pennemann
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

The tautology problem is the problem to prove the validity of statements. In this paper, we present a calculus for this undecidable problem on graphical conditions, prove its soundness, investigate the necessity of each deduction rule, and discuss practical aspects concerning an implementation. As we use the framework of weak adhesive HLR categories, the calculus is applicable to a number of replacement capable structures, such as Petri-Nets, graphs or hypergraphs.
Getting mod: a look at modularity in mobile systems
Authors: Evan Barba
Venue: Proceedings of the 9th workshop on Mobile computing systems and applications (2008)

Current methods of conceiving, engineering and using mobile technology typically embody a single integrated design philosophy. This integrated design approach seeks to combine as many features and functions into a single device as possible. In this manner it can be said that it hides the complexity of the system from the user. However, this design philosophy is by no means ubiquitous. In fact, it is the antithesis of one of the major design philosophies that characterizes modern thinking and underlies other areas of computing: modularity. The modular design approach attempts to create simplicity, not by combining multiple functions into one integrated whole, but by separating them out into distinct functional units. This work examines aspects of modular design that are relevant to computing in general, and what they might offer to the design and use of mobile systems.
Execution coordination in mobile agent-based distributed job workflow execution
Authors: Yuhong Feng, Wentong Cai
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

Mobile agent-based distributed job workflow execution requires the use of execution coordination techniques to ensure that an agent executing a subjob can locate its predecessors' execution results. This paper describes the classification, implementation, and evaluation of execution coordination techniques in the mobile agent-based distributed job workflow execution system. First, a classification of the existing execution coordination techniques is developed for mobile agent systems. Second, to put the discussion into perspective, our framework for mobile agent-based distributed job workflow execution over the Grid (that is, MCCF: Mobile Code Collaboration Framework) is described. How the existing coordination techniques can be applied in the MCCF is also discussed. Finally, a performance study has been conducted to evaluate three coordination techniques using real and simulated job workflows. The results are presented and discussed in the paper.
Readable Representations for Large-Scale Bipartite Graphs
Authors: Shuji Sato, Kazuo Misue, Jiro Tanaka
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

Bipartite graphs appear in various scenes in the real world, and visualizing these graphs helps improve our understanding of network structures. The amount of information that is available to us has increased dramatically in recent years, and it is therefore necessary to develop a drawing technique that corresponds to large-scale graphs. In this paper, we describe drawing methods to make large-scale bipartite graphs easy to read. We propose two techniques: "node contraction drawing," which involves collecting similar nodes and drawing them as one node, and "isosimilarity contour drawing," which puts clusters into an outlined area. We developed interactive user interfaces for the drawing methods and conducted an evaluation experiment to demonstrate the effectiveness of the proposed techniques.
Expediting RL by using graphical structures
Authors: Peng Dai, Alexander L. Strehl, Judy Goldsmith
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

The goal of Reinforcement learning (RL) is to maximize reward (minimize cost) in a Markov decision process (MDP) without knowing the underlying model a priori. RL algorithms tend to be much slower than planning algorithms, which require the model as input. Recent results demonstrate that MDP planning can be expedited, by exploiting the graphical structure of the MDP. We present extensions to two popular RL algorithms, Q-learning and RMax, that learn and exploit the graphical structure of problems to improve overall learning speed. Use of the graphical structure of the underlying MDP can greatly improve the speed of planning algorithms, if the underlying MDP has a nontrivial topological structure. Our experiments show that use of the apparent topological structure of an MDP speeds up reinforcement learning, even if the MDP is simply connected.
Linguistic Analysis of Users' Queries: Towards an Adaptive Information Retrieval System
Authors: Josiane Mothe, Ludovic Tanguy
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Most of Information Retrieval Systems transform natural language users' queries into bags of words that are matched to documents, also represented as bags of words. Through such process, the richness of the query is lost. In this paper we show that linguistic features of a query are good indicators to predict systems failure to answer it. The experiments described here are based on 42 systems or system variants and 50 TREC topics that consist of a descriptive part expressed in natural language
Fast and Small Short Vector SIMD Matrix Multiplication Kernels for the Synergistic Processing Element of the CELL Processor
Authors: Wesley Alvaro, Jakub Kurzak, Jack Dongarra
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Matrix multiplication is one of the most common numerical operations, especially in the area of dense linear algebra, where it forms the core of many important algorithms, including solvers of linear systems of equations, least square problems, and singular and eigenvalue computations. The STI CELL processor exceeds the capabilities of any other processor available today in terms of peak single precision, floating point performance. In order to fully exploit the potential of the CELL processor for a wide range of numerical algorithms, fast implementation of the matrix multiplication operation is essential. The crutial component is the matrix multiplication kernel crafted for the short vector Single Instruction Multiple Data architecture of the Synergistic Processing Element of the CELL processor. In this paper, single precision matrix multiplication kernels are presented implementing the C = C ¿ A ×B T operation and the C = C ¿ A ×B operation for matrices of size 64 ×64 elements. For the latter case, the performance of 25.55 Gflop/s is reported, or 99.80 percent of the peak, using as little as 5.9 KB of storage for code and auxiliary data structures.
Evolutionary tuning of SVM parameter values in multiclass problems
Authors: Ana Carolina Lorena, André C. P. L. F. de Carvalho
Venue: Neurocomputing (2008)

Support vector machines (SVMs) were originally formulated for the solution of binary classification problems. In multiclass problems, a decomposition approach is often employed, in which the multiclass problem is divided into multiple binary subproblems, whose results are combined. Generally, the performance of SVM classifiers is affected by the selection of values for their parameters. This paper investigates the use of genetic algorithms (GAs) to tune the parameters of the binary SVMs in common multiclass decompositions. The developed GA may search for a set of parameter values common to all binary classifiers or for differentiated values for each binary classifier.
The Agent Modeling Language (AMOLA)
Authors: Nikolaos Spanoudakis, Pavlos Moraitis
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

This paper presents the Agent MOdeling LAnguage (AMOLA). This language provides the syntax and semantics for creating models of multi-agent systems covering the analysis and design phases of the software development process. It supports a modular agent design approach and introduces the concepts of intra-and inter-agent control. The first defines the agent's lifecycle by coordinating the different modules that implement his capabilities, while the latter defines the protocols that govern the coordination of the society of the agents. The modeling of the intra and inter-agent control is based on statecharts. The analysis phase builds on the concepts of capability and functionality. AMOLA deals with both the individual and societal aspect of the agents. However, in this paper we focus in presenting only the individual agent development process. AMOLA is used by ASEME, a general agent systems development methodology.
Rules for query rewrite in native XML databases
Authors: Andreas M. Weiner, Christian Mathis, Theo Härder
Venue: Proceedings of the 2008 EDBT workshop on Database technologies for handling XML information on the web (2008)

In recent years, the database community has seen many sophisticated Structural Join and Holistic Twig Join algorithms as well as several index structures supporting the evaluation of twig query patterns. Even though almost all XML query evaluation proposals in the literature use one of those evaluation methods, we believe that (1) there is no internal representation that enables a smooth transition between the XQuery language level and physical algebra operators, and (2) there is still no approach that considers the combination of content-and-structure indexes, Structural Join (SJ), and Holistic Twig Join (HTJ) algorithms to speed up the evaluation of twig queries. To overcome this deficit, we propose an enhancement to Starburst's Query Graph Model as an internal representation for XML query languages such as XQuery. This representation permits the usage of SJ and HTJ operators as part of the logical algebra. For twig queries, we define a set of rewrite rules which initiate query graph transformations towards improved processability, e.g., to fuse adjacent binary join operators to an n-way join operator. To enhance the evaluation flexibility of twig queries, we come up with further rewrite rules to prepare query graphs---even before query transformation---for making the most of existing joins and indexes.
Surface-Based Texture and Morphological Analysis Detects Subtle Cortical Dysplasia
Authors: Pierre Besson, Neda Bernasconi, Olivier Colliot, Alan Evans, Andrea Bernasconi
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Focal cortical dysplasia (FCD), a malformation of cortical development, is an important cause of pharmacoresistant epilepsy. Small FCD lesions are difficult to distinguish from normal cortex and remain often overlooked on radiological MRI inspection. This paper presents a method to detect small FCD lesions on T1-MRI relying on surface-based features that model their textural and morphometric characteristics. The automatic detection was performed by a two step classification. First, a vertex-wise classifier based on a neural-network bagging trained on manual labels. Then, a cluster-wise classification designed to remove false positive clusters. The method was tested on 19 patients with small FCD. At the first classification step, 18/19 (95%) lesions were detected. The second classification step kept 13/19 (68%) lesions and decreased efficiently the amount of false positive. This new approach may assist the presurgical evaluation of patients with intractable epilepsy, especially those with unremarkable MRI findings.
Design and Development of Component-Based Embedded Systems for Automotive Applications
Authors: Marco Natale
Venue: Proceedings of the 13th Ada-Europe international conference on Reliable Software Technologies (2008)

Automotive software systems are characterized by increasing complexity, tight safety and performance requirements, and need to be developed subject to substantial time-to-market pressure. Model- and component-based design methodologies can be used to improve the overall quality of software systems and foster reuse. In this work, we discuss challenges in the adoption of model-based development flows, and we review recent advances in component-based methodologies, including existing or upcoming standards, such as the MARTE UML profile, ADL languages and AUTOSAR. Finally, the paper provides a quick glance at results on a methodology based on virtual platforms and timing analysis to perform the exploration and selection of architecture solutions.
Modeling Spatiotemporal Uncertainty in Dynamic Virtual Environments
Authors: S. Vosinakis, G. Anastassakis, T. Panayiotopoulos
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

Current virtual agent [1] control architectures involve representations of the environment that must be adequate for effective deliberative behaviour rather than simple encoding of the environment's state. Hence, they must take into account the element of uncertainty that is inherent to perceptual processes, in the form of predicting the future state of perceivable parts of the environment or the current state of non-perceivable parts. A number of approaches have been proposed to deal with uncertainty. A large proportion introducing uncertainty as a means towards increased perceptual believability [2]. A different group attempts to deal with inherent uncertainty in a variety of ways [3,4]. Although substantial benefits are gained in both cases, prediction over time is rarely addressed, while potential knowledge on targets' intentions remains largely unexploited.
Delineating the Degree of 'Pervasiveness' in Pervasive Information Systems: An Assessment Framework and Design Implications
Authors: Panos E. Kourouthanassis, George M. Giaglis, Dimitrios C. Karaiskos
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

Pervasive Information Systems exemplify a paradigm where Information Technology is embedded in the physical environment, capable of accommodating user needs and wants when desired. Pervasive IS differ from IS that are based on the desktop paradigm in that they encompass a complex, dynamic setting composed of multiple artefacts, capable of perceiving contextual information, diffused in the physical space and supporting ubiquitous interaction with the system resources. Building on the novel properties of pervasive IS, we propose a framework that can be used to assess the level of 'pervasiveness' of any IS instance. Furthermore, we discuss how this framework may be employed to influence the design of pervasive IS.
Certifying a Tree Automata Completion Checker
Authors: Benoît Boyer, Thomas Genet, Thomas Jensen
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

Tree automata completion is a technique for the verification of infinite state systems. It has already been used for the verification of cryptographic protocols and the prototyping of Java static analyzers. However, as for many other verification techniques, the correctness of the associated tool becomes more and more difficult to guarantee. It is due to the size of the implementation that constantly grows and due to optimizations which are necessary to scale up the efficiency of the tool to verify real-size systems. In this paper, we define and develop a checker for tree automata produced by completion. The checker is defined using coq and its implementation is automatically extracted from its formal specification. Using extraction gives a checker that can be run independently of the coq environment. A specific algorithm for tree automata inclusion checking has been defined so as to avoid the exponential blow up. The obtained checker is certified in coq, independent of the implementation of completion, usable with any approximation performed during completion, small and fast. Some benchmarks are given to show how efficient the tool is.
Instance-Dependent Verifiable Random Functions and Their Application to Simultaneous Resettability
Authors: Yi Deng, Dongdai Lin
Venue: Proceedings of the 26th annual international conference on Advances in Cryptology (2007)

We introduce a notion of instance-dependent verifiable random functions (InstD-VRFs for short). Informally, an InstD-VRF is, in some sense, a verifiable random function [23] with a special public key, which is generated via a (possibly)interactive protocol and contains an instance y ¿ L ¿ {0,1}* for a specific NP language L, but the security requirements on such a function are relaxed: we only require the pseudorandomness property when y ¿ L and only require the uniqueness property when y ¿ L, instead of requiring both pseudorandomness and uniqueness to hold simultaneously. We show that this notion can be realized under standard assumption.Our motivation is the conjecture posed by Barak et al.[2], which states there exist resettably-sound resettable zero knowledge arguments for NP. The instance-dependent verifiable random functions is a powerful tool to tackle this problem. We first use them to obtain two interesting instance-dependent argument systems from the Barak's public-coin bounded concurrent zero knowledge argument [1], and then, we 1 Construct the first (constant round) zero knowledge arguments for NP enjoying a certain simultaneous resettability under standard hardness assumptions in the plain model, which we call bounded-class resettable ZK arguments with weak resettable-soundness Though the malicious party (prover or verifier) in such system is limited to a kind of bounded resetting attack, We put NO restrictions on the number of the total resets made by malicious party. 1 show that, under standard assumptions, if there exist public-coin concurrent zero knowledge arguments for NP, there exist the resettably-sound resetable zero knowledge arguments for NP.
Improving Parenchyma Segmentation by Simultaneous Estimation of Tissue Property T1 Map and Group-Wise Registration of Inversion Recovery MR Breast Images
Authors: Ye Xing, Zhong Xue, Sarah Englander, Mitchell Schnall, Dinggang Shen
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

The parenchyma tissue in the breast has a strong relation with predictive biomarkers of breast cancer. To better segment parenchyma, we perform segmentation on estimated tissue property T 1 map. To improve the estimation of tissue property (T 1) which is the basis for parenchyma segmentation, we present an integrated algorithm for simultaneous T 1 map estimation, T 1 map based parenchyma segmentation and group-wise registration on series of inversion recovery magnetic resonance (MR) breast images. The advantage of using this integrated algorithm is that the simultaneous T 1 map estimation (E-step) and group-wise registration (R-step) could benefit each other and jointly improve parenchyma segmentation. In particular, in E-step, T 1 map based segmentation could help perform an edge-preserving smoothing on the tentatively estimated noisy T 1 map, and could also help provide tissue probability maps to be robustly registered in R-step. Meanwhile, the improved estimation of T 1 map could help segment parenchyma in a more accurate way. In R-step, for robust registration, the group-wise registration is performed on the tissue probability maps produced in E-step, rather than the original inversion recovery MR images, since tissue probability maps are the intrinsic tissue property which is invariant to the use of different imaging parameters. The better alignment of images achieved in R-step can help improve T 1 map estimation and indirectly the T 1 map based parenchyma segmentation. By iteratively performing E-step and R-step, we can simultaneously obtain better results for T 1 map estimation,T 1 map based segmentation, group-wise registration, and finally parenchyma segmentation.
Driving Load Forecasting Using Cascade Neural Networks
Authors: Zhancheng Wang, Guoqing Xu, Weimin Li, Yangsheng Xu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

This paper presents an approach for solving the driving load forecasting problem based on Cascade Neural Networks with node-decoupled extended Kalman Filtering (CNN-NDEKF). Because of the inherent advantages, hybrid electric vehicles (HEV) are being given more and more attention. The power control strategy of HEVs is the key technology which determines the HEV's efficiency and pollutive emission level. Since the extent of improvement involved with HEV power control strategies greatly depends on the future driving load forecasting, in this paper, we attempt to achieve driving load forecasting using CNN-NDEKF. Instead of forecasting the entire load sequence, we define 5 load levels by a fuzzy logic method and then we forecast the load level. Simulation study is given to illustrate the feasibility of the driving load forecasting approach.
Simulating a Human Cooperative Problem Solving
Authors: Alexandre Pauchet, Amal Fallah Seghrouchni, Nathalie Chaignaud
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

We are interested in understanding and simulating how humans elaborate plans in situations where knowledge is incomplete and how they interact to obtain missing information. Our human interaction model is based on the speech act theory to model the utterances and it uses timed automata to describe the dynamics of the dialogs. Our human planning model is implemented as a hierarchical blackboard architecture which manages opportunistic planning. The system BDIggy we propose, is a concurrent implementation of the planning model and the interaction model through the BDI concept. This system is used to simulate the human processes during cooperative problem solving.