ppxscal/embedding_network huggingface dataset:
The Research and Implementation of Decision Support System for Oil Production Based on SOA
Authors: Bao rong Zhong, Hong Du, Hua yun Yu
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

The decision support system for oil production based on service-oriented architecture (SOA) uses B/S structure of the three levels design pattern. It integrates the application of modern communications, graphics and image processing, remote transmission control, data mining technology and so on. It uses OLAP to analysis the field condition timely, and it plays role in production decision-making and control. This paper discusses the architecture and the physical structure of the decision support system (DSS), emphatically describes the system structure of oil production command DDS. This system not only performs in oil engineering management system (OMS), but also has great advantages in the integration of office automation system (OA) of oil industry and enterprise resource planning system (ERP).
From Domain to Requirements
Authors: Dines Bjørner
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

We first present a summary of essentials of domain engineering, its motivation, and its modelling of abstractions of domains through the modelling of the intrinsics, support technologies, management and organisation, rules and regulations, scripts, and human behaviour of whichever domain is being described.Then we present the essence of two (of three) aspects of requirements: the domain requirements and the interface requirements prescriptions as they relate to domain descriptions and we survey the basic operations that "turn" a domain description into a domain requirements prescription: projection, instantiation, determination, extension and fitting. An essence of interface requirements is also presented: the "merging" of shared entities, operations, events and behaviours of the domain with those of the machine (i.e., the hardware and software to be designed).
A Peer-to-Peer Hybrid Multicast Infrastructure for Remote Learning
Authors: Xiao-bin Huang, Jian-ping Wei, Wan-yu Lu, Yong Fan, Zhi-qiang Tan
Venue: Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 02 (2008)

Multicast has been intensively studied over the past decade. Existing multicast services come in two flavors, IP multicast and application level multicast, depending on which layer the service is implemented on. After investigating the pros and cons of both approaches, as well as the characteristics of interactive distance learning, we find it an imperative to combine these two multicast approaches for this kind of applications. In this paper, we present a peer-to-peer hybrid multicast infrastructure (P2HMI) for interactive distance learning. Apart from blending IP multicast and application level multicast, P2HMI automatically builds and maintains a tree structure upon which transport functionalities are implemented, including a differentiated error recovery service, flow and congestion control and global ordering.
Heuristics Core Mapping in On-Chip Networks for Parallel Stream-Based Applications
Authors: Piotr Dziurzanski, Tomasz Maka
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

A novel approach for implementation of multimedia streaming applications into mesh Networks on Chips structure is proposed. We provide a new multi-path routing algorithm together with heuristic algorithms for core mapping so that minimize the total transfer in the hardware implementation. The proposed approach has been tested with two popular stream-based video decompression algorithms. The experimental results confirming the proposed approach are provided.
Integrating Performance Analysis in the Model Driven Development of Software Product Lines
Authors: Rasha Tawhid, Dorina Petriu
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

The paper proposes to integrate performance analysis in the early phases of the model-driven development process for Software Product Lines (SPL). We start by adding generic performance annotations to the UML model representing the set of core reusable SPL assets. The annotations are generic and use the MARTE Profile recently adopted by OMG. A first model transformation realized in the Atlas Transformation Language (ATL), which is the focus of this paper, derives the UML model of a specific product with concrete MARTE performance annotations from the SPL model. A second transformation generates a Layered Queueing Network performance model for the given product by applying an existing transformation approach named PUMA, developed in previous work. The proposed technique is illustrated with an e-commerce case study that models the commonality and variability in both structural and behavioural SPL views. A product is derived and the performance of two design alternatives is compared.
Workshops and Symposia at MODELS 2007
Authors: Holger Giese
Venue: Proceedings of the 10th international conference on Model Driven Engineering Languages and Systems (2007)

Following the tradition of previous instances of the MODELS conference series, also in 2007 a number of workshops and symposia were hosted. 11 workshops and two symposia complemented the main conference by providing room for important subject areas and enabling a high degree of interactivity.
Towards Effective Visual Data Mining with Cooperative Approaches
Authors: François Poulet
Venue: Visual Data Mining: Theory, Techniques and Tools for Visual Analytics (2008)

Visual data-mining strategy lies in tightly coupling the visualizations and analytical processes into one data-mining tool that takes advantage of the strengths from multiple sources. We present concrete cooperation between automatic algorithms, interactive algorithms and visualization methods. The first kind of cooperation is an interactive decision tree algorithm CIAD. It allows the user to be helped by an automatic algorithm based on a support vector machine (SVM) to optimize the interactive split performed in the current tree node or to compute the best split in an automatic mode. Another effective cooperation is a visualization algorithm used to explain the results of SVM algorithm. The same visualization method can also be used to help the user in the parameters tuning step in input of automatic SVM algorithms. Then we present methods using both automatic and interactive methods to deal with very large datasets. The obtained results let us think it is a promising way to deal with very large datasets.
Verification of scope-dependent hierarchical state machines
Authors: Salvatore La Torre, Margherita Napoli, Mimmo Parente, Gennaro Parlato
Venue: Information and Computation (2008)

A hierarchical state machine (Hsm) is a finite state machine where a vertex can either expand to another hierarchical state machine (box) or be a basic vertex (node). Each node is labeled with atomic propositions. We study an extension of such model which allows atomic propositions to label also boxes (Shsm). We show that Shsms can be exponentially more succinct than Shsms and verification is in general harder by an exponential factor. We carefully establish the computational complexity of reachability, cycle detection, and model checking against general Ltl and Ctl specifications. We also discuss some natural and interesting restrictions of the considered problems for which we can prove that Shsms can be verified as much efficiently as Hsms, still preserving an exponential gap of succinctness.
Preliminary Study on Optimization of Data Distribution in Resource Sharing Systems
Authors: Grzegorz Chmaj, Krzysztof Walkowiak
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

Grid structures are increasingly considered as very convergent with peer-to-peer networks. This paper presents a model of network acting both as grid and peer-to-peer network, used for data computation and distribution. Presented PPLC algorithm is a complete solution for both grid and peer-to-peer points of view. Problem formulation is presented, as well as solution heuristic algorithm and research results.
A Generic Data Level Implementation of ModelGen
Authors: Andrew Smith, Peter Mcbrien
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

The model management operator ModelGen translates a schema expressed in one modelling language into an equivalent schema expressed in another modelling language, and in addition produces a mapping between those two schemas. This paper presents an implementation of ModelGen which in addition allows for the translation of data instances from the source to the target schema, and vice versa. The translation mechanism is distinctive from others in that it takes a generic approach that can be applied to any modelling language.
Abstraction for Stochastic Systems by Erlang's Method of Stages
Authors: Joost-Pieter Katoen, Daniel Klink, Martin Leucker, Verena Wolf
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

This paper proposes a novel abstraction technique based on Erlang's method of stages for continuous-time Markov chains (CTMCs). As abstract models Erlang-k interval processes are proposed where state residence times are governed by Poisson processes and transition probabilities are specified by intervals. We provide a three-valued semantics of CSL (Continuous Stochastic Logic) for Erlang-k interval processes, and show that both affirmative and negative verification results are preserved by our abstraction. The feasibility of our technique is demonstrated by a quantitative analysis of an enzyme-catalyzed substrate conversion, a well-known case study from biochemistry.
Active Learning in Multi-armed Bandits
Authors: András Antos, Varun Grover, Csaba Szepesvári
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which option to generate the next sample from in order to produce estimates with equally good precision for all the distributions. When an algorithm uses sample means to estimate the unknown values then the optimal solution, assuming full knowledge of the distributions, is to sample each option proportional to its variance. In this paper we propose an incremental algorithm that asymptotically achieves the same loss as an optimal rule. We prove that the excess loss suffered by this algorithm, apart from logarithmic factors, scales as n ¿ 3/2, which we conjecture to be the optimal rate. The performance of the algorithm is illustrated in a simple problem.
Performance Evaluation of Binary Negative-Exponential Backoff Algorithm in Presence of a Channel Bit Error Rate
Authors: Bum-Gon Choi, Hyung Joo Ki, Min Young Chung, Tae-Jin Lee
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The IEEE 802.11 standard basically uses a DCF (Distributed Coordination Function) to access a wireless channel. However, the DCF uses wireless resource ineffectively when there are many contending stations and a high bit error rate. To enhance the performance of the wireless LAN, Ki et al. proposed a Binary Negative-Exponential Backoff (BNEB) algorithm. We found that the performance of the BNEB algorithm was better than the conventional DCF. However, erroneous channel environment was not considered. In our work, we propose an analytical model for the BNEB algorithm in the presence of transmission error and compare the performance of the DCF with the BEB algorithm to that with the BNEB algorithm. From the result, the BNEB algorithm yields better performance than the DCF when the bit error rate (BER) ≤ 10¿ 5.
Least Upper Bounds for Probability Measures and Their Applications to Abstractions
Authors: Rohit Chadha, Mahesh Viswanathan, Ramesh Viswanathan
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

Abstraction is a key technique to combat the state space explosion problem in model checking probabilistic systems. In this paper we present new ways to abstract Discrete Time Markov Chains (DTMCs), Markov Decision Processes (MDPs), and Continuous Time Markov Chains (CTMCs). The main advantage of our abstractions is that they result in abstract models that are purely probabilistic, which maybe more amenable to automatic analysis than models with both nondeterministic and probabilistic steps that typically arise from previously known abstraction techniques. A key technical tool, developed in this paper, is the construction of least upper bounds for any collection of probability measures. This upper bound construction may be of independent interest that could be useful in the abstract interpretation and static analysis of probabilistic programs.
Parallel Quantum Computer Simulation on the CUDA Architecture
Authors: Eladio Gutierrez, Sergio Romero, Maria A. Trenas, Emilio L. Zapata
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Due to their increasing computational power, modern graphics processing architectures are becoming more and more popular for general purpose applications with high performance demands. This is the case of quantum computer simulation, a problem with high computational requirements both in memory and processing power. When dealing with such simulations, multiprocessor architectures are an almost obliged tool. In this paper we explore the use of the new graphics processor architecture NVIDIA CUDA in the simulation of some basic quantum computing operations. This new architecture is oriented towards a more general exploitation of the graphics platform, allowing to use it as a parallel SIMD multiprocessor. In this direction, some implementation strategies are proposed, showing that the effectiveness of the codes is subject to a right exploitation of the underlying memory hierarchy.
E Pluribus Unum: Polyagent and Delegate MAS Architectures
Authors: H. Dyke Parunak, Sven Brueckner, Danny Weyns, Tom Holvoet, Paul Verstraete, Paul Valckenaers
Venue: Multi-Agent-Based Simulation VIII: International Workshop, MABS 2007, Honolulu, HI, USA, May 15, 2007, Revised and Invited Papers (2008)

For the past few years, our research groups have independently been developing systems in which a multi-agent system (typically of lightweight agents) provides some functionality in service of a higher-level system, and often of a higher-level agent in that system. This paper compares our approaches to develop a more generic architecture of which our individual approaches are special cases. We summarize our existing systems, describe this architecture and the characteristics of problems for which it is attractive, and outline an agenda for further research in this area.
Selective Visual Attention System Based on Spatiotemporal Features
Authors: Min-Chul Park, Kyungjoo Cheoi
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

In this paper, a selective visual attention system for motion pictures is proposed. The proposed attention system is new in that it utilizes motion information for the purpose of detecting Region Of Interest (ROI) or Focus Of Attention (FOA) in motion pictures. Typical feature integration model is expanded to incorporate motion stimulus in our suggested model. Suggested model is able to respond to motion stimulus by employing motion fields as one of temporal features to the feature integration model. Analysis of motion field maps and incorporation of the result are distinct from some of the previous studies on spatial feature integration. Comparative experiments with a human subjective evaluation show that correct detection rate of visual attention regions improves by utilizing temporal features compared to the case of using only spatial features.
Combining Rewriting with Noetherian Induction to Reason on Non-orientable Equalities
Authors: Sorin Stratulat
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

We propose a new (Noetherian) induction schema to reason on equalities and show how to integrate it into implicit induction-based inference systems. Non-orientable conjectures of the form lhs = rhs and their instances can be soundly used as induction hypotheses in rewrite operations. It covers the most important rewriting-based induction proof techniques: i)term rewriting induction if lhs = rhs is orientable, ii) enhanced rewriting induction if lhs and rhs are comparable, iii)ordered rewriting induction if the instances of lhs = rhs are orientable, and iv) relaxed rewriting induction if the instances of lhs = rhs are not comparable.In practice, it helps to automatize the (rewrite-based) reasoning on a larger class of non-orientable equalities, like the permutative and associativity equalities.
Solutions to Switched Hamilton-Jacobi Equations and Conservation Laws Using Hybrid Components
Authors: Christian G. Claudel, Alexandre M. Bayen
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

We investigate a class of hybrid systems driven by partial differential equations for which the infinite dimensional state can switch in time and in space at the same time. We consider a particular class of such problems (switched Hamilton-Jacobi equations) and define hybrid components as building blocks of hybrid solutions to such problems, using viability theory. We derive sufficient conditions for well-posedness of such problems, and use a generalized Lax-Hopf formula to compute these solutions. We illustrate the results with three examples: the computation of the hybrid components of a Lighthill-Whitham-Richards equation; a velocity control policy for a highway system; a data assimilation problem using Lagrangian measurements generated from NGSIM traffic data.
A New Concept of Trust Modeling and Management in Complex Networks
Authors: Grzegorz Kołaczek
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

The paper presents the novel concept of trust evaluation method for autonoumous multi-agent systems. The method is based on assumption that multi-agent system constitutes social network and so it is an instantiation of the complex network. Several metrics used in description of this type of networks can be used to model trust relation between agents. In the presented model the agent's A trust in an agent's B statements is obtained as the Subjective Logic consensus of modified trust levels of all agents that trust the agent B. The trust level modification is performed in relation to the current position of the agent in the network.
Vector Median M-Type L Filter to Process Multichannel Images
Authors: Antonio Toledo-Lopez, Francisco J. Gallegos-Funes, Volodymyr Ponomaryov
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

The Vector Median M-type L (VMML) -filter to remove impulsive noise from color images and video color sequences is presented. This filter utilizes multichannel image processing by using the vector approach and the Median M-Type L (MML) algorithm. Simulation results indicate that the proposed filter consistently outperforms other color image filters by balancing the tradeoff between noise suppression, detail preservation, and color retention.
Automata can show PSpace results for description logics
Authors: Franz Baader, Jan Hladik, Rafael Peòaloza
Venue: Information and Computation (2008)

In the area of Description Logic (DL), both tableau-based and automata-based algorithms are frequently used to show decidability and complexity results for basic inference problems such as satisfiability of concepts. Whereas tableau-based algorithms usually yield worst-case optimal algorithms in the case of PSpace-complete logics, it is often very hard to design optimal tableau-based algorithms for ExpTime-complete DLs. In contrast, the automata-based approach is usually well-suited to prove ExpTime upper-bounds, but its direct application will usually also yield an ExpTime-algorithm for a PSpace-complete logic since the (tree) automaton constructed for a given concept is usually exponentially large. In the present paper, we formulate conditions under which an on-the-fly construction of such an exponentially large automaton can be used to obtain a PSpace-algorithm. We illustrate the usefulness of this approach by proving a new PSpace upper-bound for satisfiability of concepts with respect to acyclic terminologies in the DL SI, which extends the basic DL ALC with transitive and inverse roles.
Forward chaining in HALO: An implementation strategy for history-based logic pointcuts
Authors: Charlotte Herzeel, Kris Gybels, Pascal Costanza, Coen De Roover, Theo D'Hondt
Venue: Computer Languages, Systems and Structures (2009)

In aspect-oriented programming, pointcuts are formulated as conditions over the context of dynamic events in the execution of a program. Hybrid pointcut languages also allow this context to come from interactions between the pointcut language and the base program. While some pointcut languages only allow conditions on the current execution event, more recent proposals have demonstrated the need for expressing conditions over a history of join points. Such pointcut languages require means to balance the expressiveness of the language with the additional memory and runtime overhead caused by keeping a history of join point context data. In this paper, we introduce a logic-based pointcut language that allows interaction with the base program as well as pointcuts over a history of join points. We introduce forward chaining as an implementation model for this language, and discuss possible optimization strategies for the additional overhead.
Learning at the Speed of Light: A New Type of Optical Neural Network
Authors: Arthur Steven Younger, Emmett Redd
Venue: Proceedings of the 1st international workshop on Optical SuperComputing (2008)

Most, if not all, optical hardware-based neural networks are slow during the neural learning phase. This limitation has been not only a speed bottleneck, but it has contributed to the lack of wide-spread use of optical neural systems. We present a novel solution --- Optical Fixed-Weight Learning Neural Networks. Standard neural networks learn new function mappings by the changing of their synaptic weights. However, the Fixed-Weight Neural Networks learn new mappings by dynamically changing recurrent neural signals. The (fixed) synaptic weights of the FWL-NN implement a learning "algorithm" which adjusts the recurrent signals toward their proper values.
Using Design Patterns in Formal Methods: An Event-B Approach
Authors: J. -R. Abrial, Thai Son Hoang
Venue: Proceedings of the 5th international colloquium on Theoretical Aspects of Computing (2008)

Motivation. Formal Methods users are given sophisticated languages and tools for constructing models of complex systems. But quite often they lack some systematic methodological approaches which could help them. The goal of introducing design patterns within formal methods is precisely to bridge this gap.A design pattern is a general reusable solution to a commonly occurring problem in (software) design . . . It is a description or template for how to solve a problem that can be used in many different situations (Wikipedia on "Design Pattern").