ppxscal/embedding_network huggingface dataset:
Reusable Services and Semi-automatic Service Composition for Automotive Software
Authors: Holger Giese
Venue: Model-Driven Development of Reliable Automotive Services: Second Automotive Software Workshop, ASWSD 2006, San Diego, CA, USA, March 15-17, 2006, Revised Selected Papers (2006)

Automotive software has become an important factor in the development of modern and innovative high-end vehicles. More and more functions can only be realized by the cooperation of different control devices. In addition, not only a single product but a number of basic configurations and a large number of optional functions for each new type series have to be addressed by the software. While product lines are a promising approach to address known variability within a car series, the reuse of functions across type series is not feasible with the current proposals. In this paper, a service-oriented approach is sketched which exploits that functions in automotive systems only have to be recombined in a restricted manner in order to enable reuse across car series. Components are used as basic units which provide localized basis functionality, patterns represent reusable assets which capture the interaction and protocols in between several roles, and services capture complex reusable functionality which requires the interaction of multiple units. It is sketched how all phases of the development process can benefit from a service-oriented approach and that advanced synthesis techniques can be employed to reuse the components, patterns and services and compose them with only minimal manual efforts.
Vortex particle methods in aeroacoustic calculations
Authors: Serge Huberson, Elie Rivoalen, Spyros Voutsinas
Venue: Journal of Computational Physics (2008)

The connection between vortex particle methods and aeroacoustics is considered within the framework of Lighthill's acoustic analogy which allows to decouple the flow from noise propagation. For the flow, techniques such as tree-algorithms and the particle-mesh method are brought together with the aim to achieve the best possible performance in view of analyzing complex problems. The flow results are then input to the acoustic wave equation which is solved in integral form. It will involve monopole, dipole and quadrupole terms which can be successively integrated. The significance of such an approach is first demonstrated in two problems, both related to vortex-solid interactions. The first is a generic one and considers the interaction of a vortex filament interacting with a sphere while the second considers helicopter noise as an example of a complex engineering set-up.
Design Patterns for Self-organising Systems
Authors: Luca Gardelli, Mirko Viroli, Andrea Omicini
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

Natural systems are regarded as rich sources of inspiration for engineering artificial systems, particularly when adopting the multiagent system (MAS) paradigm. To promote a systematic reuse of mechanisms featured in self-organising systems, we analyse a selection of design patterns devised from the self-organisation literature. Starting from our reference MAS metamodel, we propose a pattern scheme that reflects the peculiarities of self-organising systems. Then, we provide a complete characterisation of each pattern, with particular attention to the problem description, the solution with respect to our metamodel, the natural systems which have inspired the pattern and known applications.
Building Theories of the World: Human and Machine Learning Perspectives
Authors: Joshua B. Tenenbaum
Venue: Proceedings of the 18th international conference on Inductive Logic Programming (2008)

Human knowledge of the world is often expressed in the form of intuitive theories: systems of abstract concepts that organize, predict and explain our observations of the world. How are these powerful knowledge structures represented and acquired? I will describe computational frameworks for modeling people's intuitive theories and theory-building processes, and some ways of testing these models experimentally with human learners. Our models of human learning and inference build on core approaches in Bayesian artificial intelligence, statistical relational learning and inductive logic programming, but also suggest new ways to extend these machine learning and reasoning approaches to more human-like capacities.
Towards Knowledge-Based Affective Interaction: Situational Interpretation of Affect
Authors: Abdul Rehman Abbasi, Takeaki Uno, Matthew N. Dailey, Nitin V. Afzulpurkar
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

Human-to-computer interaction in a variety of applications could benefit if systems could accurately analyze and respond to their users' affect. Although a great deal of research has been conducted on affect recognition, very little of this work has considered what is the appropriate information to extract in specific situations. Towards understanding how specific applications such as affective tutoring and affective entertainment could benefit, we present two experiments. In the first experiment, we found that students' facial expressions, together with their body actions, gave little information about their internal emotion per se but they would be useful features for predicting their self-reported "true" mental state. In the second experiment, we found significant differences between the facial expressions and self-reported affective state of viewers watching a movie sequence. Our results suggest that the noisy relationship between observable gestures and underlying affect must be accounted for when designing affective computing applications.
Large independent sets in general random intersection graphs
Authors: S. Nikoletseas, C. Raptopoulos, P. Spirakis
Venue: Theoretical Computer Science (2008)

We investigate the existence and efficient algorithmic construction of close to optimal independent sets in random models of intersection graphs. In particular, (a) we propose a new model for random intersection graphs (G"n","m","p"->) which includes the model of [M. Karonski, E.R. Scheinerman, K.B. Singer-Cohen, On random intersection graphs: The subgraph problem, Combinatorics, Probability and Computing journal 8 (1999), 131-159] (the ''uniform'' random intersection graph models) as an important special case. We also define an interesting variation of the model of random intersection graphs, similar in spirit to random regular graphs. (b) For this model we derive exact formulae for the mean and variance of the number of independent sets of size k (for any k) in the graph. (c) We then propose and analyse three algorithms for the efficient construction of large independent sets in this model. The first two are variations of the greedy technique while the third is a totally new algorithm. Our algorithms are analysed for the special case of uniform random intersection graphs. Our analyses show that these algorithms succeed in finding close to optimal independent sets for an interesting range of graph parameters.
Provenance Querying for End-Users: A Drug Resistance Case Study
Authors: Bartosz Baliś, Marian Bubak, Michal Pelczar, Jakub Wach
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

We present a provenance model based on ontology representation of execution records of in silico experiments. The ontologies describe the execution of experiments, and the semantics of data and computations used during the execution. This model enables query construction in an end-user oriented manner, i.e. by using terms of the scientific domain familiar to researchers, instead of complex query languages. The presented approach is evaluated on a case study Drug Resistance Application exploited in the ViroLab virtual laboratory. We analyze the query capabilities of the presented provenance model. We also describe the process of ontology-based query construction and evaluation.
Advanced Bounded Shortest Multicast Algorithm for Delay Constrained Minimum Cost
Authors: Moonseong Kim, Gunu Jho, Hyunseung Choo
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

The Bounded Shortest Multicast Algorithm (BSMA) is a very well-known one of delay-constrained minimum-cost multicast routing algorithms. Although the algorithm shows excellent performance in terms of generated tree cost, it suffers from high time complexity. For this reason, there is much literature relating to the BSMA. In this paper, the BSMA is analyzed. The algorithms and shortcomings are corrected, and an improved scheme is proposed without changing the main idea of the BSMA.
Dynamic Updating of Profiles for an Immunity-Based Anomaly Detection System
Authors: Takeshi Okamoto, Yoshiteru Ishida
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

Our immunity-based anomaly detection system aims to detect anomalous behavior of users on a computer. To improve the detection accuracy, we introduced the framework of dynamically updating profiles into our system. Our system enables agents to update not only self profiles, but also nonself profiles. Briefly, our system enables agents to adapt to new behavior of the original users and of others. The receiver operating characteristic (ROC) analysis of our system indicated that the updating of both profiles markedly decreased both the false alarm rate and the missed alarm rate.
The Set Connector Problem in Graphs
Authors: Takuro Fukunaga, Hiroshi Nagamochi
Venue: Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization (2007)

Given a graph G = (V,E) with an edge cost and families $\mathcal{V}_i\subseteq 2^V$, i = 1,2,...,m of disjoint subsets, an edge subset F ¿ E is called a set connector if, for each $\mathcal{V}_i$, the graph $(V,F)/\mathcal{V}_i$ obtained from (V,F) by contracting each $X\in \mathcal{V}_i$ into a single vertex x has a property that every two contracted vertices x and x¿ are connected in $(V,F)/\mathcal{V}_i$. In this paper, we introduce a problem of finding a minimum cost set connector, which contains several important network design problems such as the Steiner forest problem, the group Steiner tree problem, and the NA-connectivity augmentation problem as its special cases. We derive an approximate integer decomposition property from a fractional packing theorem of set connectors, and present a strongly polynomial 2¿-approximation algorithm for the set connector problem, where $\alpha=\max_{1 \leq i \leq m}(\sum_{X \in \mathcal{V}_i}|X|)-1$.
Multi-source Video Transmission with Optimum Perceptual Quality over Wireless Ad Hoc Networks
Authors: Pezhman Goudarzi, Mohammad Shahram Moin
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

Many optimization theoretic based rate allocation strategies have been developed for allocating some optimal rates to the competing users in wireless ad hoc networks. By considering different objective functions (such as congestion level, total packet loss and so on), the researchers propose some optimization framework by which the problem can be solved. Due to the rapid increase in the development of different video applications in such environments and the existence of difficulties in satisfying the pre-specified QoS limits, increasing the received video quality can be considered as an important and challenging issue. The quality of the received video stream is inversely proportional to the amount of distortion which is being imposed on the video stream by the network packet loss and the video encoder. The main objective of the current paper is to introduce an optimization framework in which by optimal rate allocation to some competing video sources, the aggregate distortion of the all of the sources be minimized. The simulation results verify the claims.
Efficient Closed Pattern Mining in Strongly Accessible Set Systems (Extended Abstract)
Authors: Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Many problems in data mining can be viewed as a special case of the problem of enumerating the closed elements of an independence system with respect to some specific closure operator. Motivated by real-world applications, e.g., in track mining, we consider a generalization of this problem to strongly accessible set systems and arbitrary closure operators. For this more general problem setting, the closed sets can be enumerated with polynomial delay if deciding membership in the set system and computing the closure operator can be solved in polynomial time. We discuss potential applications in graph mining.
Computability in Amorphous Structures
Authors: Jiří Wiedermann, Lukáš Petru
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

Amorphous computing differs from the classical ideas about computations almost in every aspect. The architecture of amorphous computers is random, since they consist of a plethora of identical computational units spread randomly over a given area. Within a limited radius the units can communicate wirelessly with their neighbors via a single-channel radio. We consider a model whose assumptions on the underlying computing and communication abilities are among the weakest possible: all computational units are finite state probabilistic automata working asynchronously, there is no broadcasting collision detection mechanism and no network addresses. We show that under reasonable probabilistic assumptions non-uniform families of such amorphous computers can possess universal computing power with a high probability. To the best of our knowledge this is the first result showing the universality of such computing systems.
Scalable Feature Selection for Multi-class Problems
Authors: Boris Chidlovskii, Loïc Lecerf
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

Scalable feature selection algorithms should remove irrelevant and redundant features and scale well on very large datasets. We identify that the currently best state-of-art methods perform well on binary classification tasks but often underperform on multi-class tasks. We suggest that they suffer from the so-called accumulative effect which becomes more visible with the growing number of classes and results in removing relevant and unredundant features. To remedy the problem, we propose two new feature filtering methods which are both scalable and well adapted for the multi-class cases. We report the evaluation results on 17 different datasets which include both binary and multi-class cases.
TopGen - internet router-level topology generation based on technology constraints
Authors: Ingo Scholtes, Jean Botev, Markus Esch, Alexander Höhfeld, Hermann Schloss, Benjamin Zech
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

In order to realistically simulate algorithms or evaluate P2P overlay topologies, a detailed model of the underlying router topology is required. Since actively measuring this topology is extremely laborious and furthermore a waste of network resources, traditionally topology generators are used in order to create synthetic router-level graphs. For this, usually graph models are selected that are known to generate graphs which are similar to the actual Internet in respect to a certain metric like e.g. vertex degree distribution. These models are often superseded or adjusted when new metrics are being introduced which better differentiate between graphs. Furthermore it has been shown, that graphs that are similar in respect to e.g. vertex degree distribution can be very different from a structural point of view. In this paper Top-Gen, a generic, extensible and easy-to-use topology generation platform is presented. It contains a topology generation module which bases the generation of router-level graphs on the Internet's underlying principles and the technological constraints of routers rather than trying to effectuate similarity in respect to a certain metric. Apart from describing TopGen's general topology generation approach, graphs created with its Internet topology module are evaluated and found to be encouragingly similar to real-world datasets in various respects.
Fuzzy Directional-Distance Vector Filter
Authors: Samuel Morillas, Valentín Gregori, Julio Riquelme, Beatriz Defez, Guillermo Peris-Fajarnés
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

A well-known family of nonlinear multichannel image filters uses the ordering of vectors by means of an appropriate distance or similarity measure between vectors. In this way, the vector median filter (VMF), the vector directional filter (VDF) and the distance directional filter (DDF) use the relative magnitude differences between vectors, the directional vector difference or a combination of both, respectively. In this paper, a novel fuzzy metric is used to measure magnitude and directional fuzzy distances between image vectors. Then, a variant of the DDF using this fuzzy metric is proposed. The proposed variant is computationally cheaper than the classical DDF. In addition, experimental results show that the proposed filter receives better results in impulsive noise suppression in colour images.
New Models for Immune Mechanism Diagnosis
Authors: Calin Ciufudean, Otilia Ciufudean, Constantin Filote
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 this paper we introduce a discrete event system model of immune systems of mammalians using Markov Decision Processes based on Petri Nets Models. Based on immunological principles we propose an approach in order to study the mechanisms that govern the immune system's functionality. A two-module algorithm that launches a specific action against an anomalous situation is developed. The Petri nets tools are assumed in this approach. Also, Markov Decision Processes (MDPs) with a truncated state space to the problem with infinite state space is considered. We also propose a new algorithm to build a large model (e.g., a macro-model) of immune mechanisms of mammalians. We show that an optimal stationary policy exists and we apply the results of [1] to a dynamic scheduling problem of the immunological response to external stimuli.
WE-AMBLE: a Workflow Engine To Manage Awareness in Collaborative Grid Environments
Authors: Pilar Herrero, José Luis Bosque, Manuel Salvadores, María S. Pérez
Venue: International Journal of High Performance Computing Applications (2008)

Grid computing shares heterogeneous resources in dynamic service-based environments. This kind of system has the major advantage of enabling rapid composition of distributed applications. However, equilibrating the amount of work assigned to each of the nodes in a grid environment is a complex problem, even more so than for other kinds of parallel systems. In this paper, we present a new extension and reinterpretation of one of the most successful models of awareness in Computer Supported Cooperative Work (CSCW), called the Spatial Model of Interaction (SMI), which manages awareness of interaction through a set of key concepts, to manage task delivery in collaborative distributed systems. This model, called AMBLE (Awareness Model for Balancing the Load in Collaborative Grid Environments), also applies some theoretical principles and theories of multi-agent systems to create a collaborative and cooperative environment that provides autonomous, efficient and independent management of resources available in a grid environment. WE-AMBLE, a Workflow Engine to manage awareness in collaborative grid environments through the AMBLE concepts, provides a workflow engine to manage different levels of awareness, allowing different virtual organizations to share computational resources based on open protocols and interfaces.
The Collision Intractability of MDC-2 in the Ideal-Cipher Model
Authors: John P. Steinberger
Venue: Proceedings of the 26th annual international conference on Advances in Cryptology (2007)

We provide the first proof of security for MDC-2, the most well-known construction for turning an n-bit blockcipher into a 2n-bit cryptographic hash function. Our result, which is in the ideal-cipher model, shows that MDC-2, when built from a blockcipher having blocklength and keylength n, has security much better than that delivered by any hash function that has an n-bit output. When the blocklength and keylength are n = 128 bits, as with MDC-2 based on AES-128, an adversary that asks fewer than 274.9 queries usually cannot find a collision.
Proceedings of the 2nd workshop on Dependable distributed data management
Venue: European Conference on Computer Systems (2008)

Relational databases have been for a long time the keystone of information systems' dependability. Database management systems (DBMS) offer a uniform approach to data integrity, durability, and availability, using tried and tested techniques based on a set of unanimously accepted and well understood assumptions. However, the expectations on the DBMS itself are changing and there is an unprecedented call for a complete rewrite: The general purpose relational DBMS architecture dating back from the 70's is being convincingly challenged by a number of specialized systems for text indexing, data warehousing, stream processing, and array storage. Most strikingly, the winds of change are felt even within the common enterprise data center, where the widespread need for practical scale-out and near zero downtime translates to an increased appetite for cheap and efficient consistent replication and for shared-nothing clusters built on commodity hardware and software. Novel peer-to-peer applications, grid computing, and the emergence of cloud computing further push the envelope for radically different data management solutions. A major trend in all such emerging proposals, with a profound impact in dependability, is that large scale distribution is a core assumption in their design. This translates in very large number of nodes, wide area geographical distribution, diverse administrative domains, and pervasive heterogeneity. It is thus desirable to reevaluate time tested assumptions that underly the dependability mechanisms in database management systems and explore different performance and functionality tradeoffs. And explore the consequences on complex information systems built on them.