Graph Formalism Research Articles

Application Process Approach to Graphic Formalization of Standard and Legal Documents in Educational Institutions

Application Process Approach to Graphic Formalization of Standard and Legal Documents in Educational Institutions

Argumentation graphs with constraint-based reasoning for collaborative expertise

Collaborative processes are very important in telemedicine domain since they allow for making right decisions in complex situations with multidisciplinary staff. When modelling these collaborative processes, some inconsistencies can appear. In semantic modelling (conceptual graphs), these inconsistencies are verified using constraints. In this work, collaborative processes are represented using an argumentation system modelled in a conceptual graph formalism where inconsistencies could be particular bad attack relation between arguments. To overcome these inconsistencies, two solutions are proposed. The first one is to weight the arguments evolving in the argumentation system on the basis of the competencies of the health professionals and the credibility of the sources justifying their advice (arguments), and the second one is to model some law concepts as constraints in order to check their compliance of the collaborative process.

Causality and Temporal Dependencies in the Design of Fault Management Systems

Reasoning about causes and effects naturally arises in the engineering of safety-critical systems. A classical example is Fault Tree Analysis, a deductive technique used for system safety assessment, whereby an undesired state is reduced to the set of its immediate causes. The design of fault management systems also requires reasoning on causality relationships. In particular, a fail-operational system needs to ensure timely detection and identification of faults, i.e. recognize the occurrence of run-time faults through their observable effects on the system. Even more complex scenarios arise when multiple faults are involved and may interact in subtle ways. In this work, we propose a formal approach to fault management for complex systems. We first introduce the notions of fault tree and minimal cut sets. We then present a formal framework for the specification and analysis of diagnosability, and for the design of fault detection and identification (FDI) components. Finally, we review recent advances in fault propagation analysis, based on the Timed Failure Propagation Graphs (TFPG) formalism.

Checking dynamic consistency of conditional hyper temporal networks via mean payoff games: Hardness and (pseudo) singly-exponential time algorithm

Conditional Simple Temporal Network (CSTN ) is a constraint-based graph formalism for conditional temporal planning, which may be viewed as an extension of Simple Temporal Networks. Recently, STN s have been generalized into Hyper Temporal Networks (HyTN s), by considering weighted directed hypergraphs where each hyperarc models a disjunctive temporal constraint. We introduce the Conditional Hyper Temporal Network (CHyTN) model, a natural extension and generalization of both CSTN s and HyTN s, obtained by blending them together. We show that deciding whether a given CSTN is dynamically-consistent is coNP-hard, and that deciding whether a given CHyTN is dynamically-consistent is PSPACE-hard. Next, we offer the first deterministic (pseudo) singly-exponential time algorithm for checking DC in CHyTNs and CSTN s. To analyze the computational complexity of the proposed algorithm, we introduce a refined notion of DC, named ϵ-DC, presenting a sharp lower bounding analysis on the critical value of the reaction time where a conditional temporal network transits from being, to not being, dynamically-consistent.

Dynamic model for 3D motions of a horizontal oilwell BHA with wellbore stick-slip whirl interaction

Failure of horizontal oilwell drilling equipment, in particular the bottom-hole-assembly, is very costly. Vibration causes tool joint failure, twist-off, and bit-damage, and has motivated extensive research on understanding and predicting the dynamic shock-loading response of the bottom-hole-assembly. This paper presents a model to analyze the dynamics of a horizontal oilwell bottom-hole-assembly. A nonlinear three-dimensional multibody shaft model has been verified and extended to include stick-slip whirl phenomena due to the contact between the rotating bottom-hole-assembly and wellbore. The model has been verified with a dynamic finite element analysis through comparisons of the response of an enclosed shaft under axially compressive load rotating inside the wellbore. Finally, a complete deviated drillstring has been simulated by combining the bottom-hole assembly model with a model of the drill pipe and collars. The pipe and collars are modeled using a lumped-segment approach that predicts axial and torsional motions. The model can predict how axial and torsional bit-rock reactions are propagated to the surface, and the role that lateral vibrations near the bit play in exciting those vibrations and stressing components in the bottom-hole-assembly. The proposed model includes the mutual dependence of these vibrations, which arises due to bit-rock interaction and friction dynamics between the drillstring and wellbore wall. A force excitation source, which simulates an axially-vibrating downhole tool, has been implemented in the horizontal section of the virtual drillstring. Simulations show a better weight transfer to the bit due to the tool, with a low frequency and high amplitude force excitation giving best performance but potentially increasing the severity of lateral shock. The model, implemented using the bond graph formalism, is a useful tool for design and sensitivity analysis due to its physically meaningful parameters and low simulation times on a personal computer.

Battery dynamic energy model for use in electric vehicle simulation

The majority of work carried out around battery models is partly motivated by vehicle simulation. Specifically, for electric vehicle simulation, some characteristics of the battery require more attention while others can be simplified, thus distinguishing dynamic models for battery system simulation slightly and requiring different tools. In this paper, we propose a dynamic battery model that accounts for changes in temperature and can be integrated in electric vehicle simulation for testing purposes by computer simulation. Possibilities shown open the door for extensions of the model according to the needs, using the bond graph formalism and Matlab/Simulink. Comparison with other literature data and experiment made on electric vehicle show the accuracy and the efficiency of this approach.

A comparative study of energetic model-based fault detection using HBG and COG formalisms

Summary The problem of modeling and fault detection in an electromechanical system having a graphical representation is considered. For this system's dynamics, motivated by a desire to provide a precise fault detection procedure using a unified energy-based framework, 2 energy-based graphical formalisms are presented and compared: the Hamiltonian Bond Graph and the Causal Ordering Graph. Firstly, easily calculated from the Hamiltonian Bond Graph representation covering the causal energetic paths, the energetic residual generators are systematically deduced by comparing the energy quantity in both normal and faulty situations. Secondly, the causal and structural properties of the Causal Ordering Graph tool can be used to design an observer devoted to fault detection so as to derive directly energy-based residual generators in terms of faults. To highlight the effectiveness and applicability of 2 proposed approaches, simulation results on DC motor are provided and discussed. The performances of these fault detection schemes are compared and discussed in detail with respect to existing methods.

Dynamic and multiphysic PEM electrolysis system modelling: A bond graph approach

Proton exchange membrane (PEM) electrolysis technology appears as a key technology in the development of hydrogen-energy market applications such as energy storage or fuel for mobility. Its coupling with renewable electrical sources involves some issues related to the intermittent operation of PEM electrolysis systems. Within this framework, modelling is an essential tool to understand these issues, provide a thorough analysis and suggest some design optimization. A bibliographic analysis was carried out to identify existing models. State of the art highlighted that, although it is critical for the conception of such systems, only a few models take into account the dynamic of the whole system including balance of plant. Therefore, in this paper a new dynamic and multiphysic model of a proton exchange membrane electrolysis system is presented. It was first developed under a graphical modelling formalism: the bond graphs (BG). Regarding dynamic and multiphysic modelling of complex systems, the BG have many advantages: it involves four levels of modelling using only one tool; it is a unified multiphysic approach; the parameters used have a physical meaning; the BG model can be refined very easily by adding new elements without having to start again the modelling process. Finally, because of its causal and structural properties, BG is suitable for modelling but also for control, sizing and diagnosis analysis. The model was then transcribed systematically into block diagrams in modular fashion for reutilisability of model libraries components. After a validation process, the model was proved to describe accurately the dynamic behaviour of a semi-industrial PEM electrolysis system (25 kW). The dynamic model can now be used to achieve some analyses through BG structural properties and simulations. Thus, it is a powerful tool to improve the design of PEM electrolysis systems powered by intermittent electrical sources.

On A Graph Formalism for Ordered Edges

Though graphs are flexible enough to model any kind of data structure in principle, for some structures this results in a rather large overhead. This is for instance true for lists, i.e., edges that are meant to point to an ordered collection of nodes. Such structures are frequently encountered, for instance as ordered associations in UML diagrams. Several options exist to model lists using standard graphs, but all of them need auxiliary structure, and even so their manipulation in graph transformation rules is not trivial. In this paper we propose to enrich graphs with special ordered edges, which more naturally represent the intended structure, and define how lists can be manipulated. We show that the resulting category satisfies sufficient HLR properties to apply standard algebraic graph transformation. We believe that in a context where lists are common, the cost of a more complicated graph formalism is outweighed by the benefit of a smaller, more appropriate model and more straightforward manipulation.

Overcoming the lack of kinetic information in biochemical reactions networks

A main aspect in computational modelling of biological systems is the determination of model structure and model parameters. Due to economical and technical reasons, only part of these details are well characterized, while the rest are unknown. To deal with this difficulty, many reverse engineering and parameter estimation methods have been proposed in the literature, however these methods often need an amount of experimental data not always available. In this paper we propose an alternative approach, which overcomes model indetermination solving an Optimization Problem (OP) with an objective function that, similarly to Flux Balance Analysis, is derived from an empirical biological knowledge and does not require large amounts of data. The system behaviour is described by a set of Ordinary Differential Equations (ODE). Model indetermination is resolved selecting time-varying coefficients that maximize/ minimize the objective function at each ODE integration step. Moreover, to facilitate the modelling phase we provide a graphical formalism, based on Petri Nets, which can be used to derive the corresponding ODEs and OP. Finally, the approach is illustrated on a case study focused on cancer metabolism.

Solving k-Set Agreement Using Failure Detectors in Unknown Dynamic Networks

The failure detector abstraction has been used to solve agreement problems in asynchronous systems prone to crash failures, but so far it has mostly been used in static and complete networks. This paper aims to adapt existing failure detectors in order to solve agreement problems in unknown, dynamic systems. We are specifically interested in the k-set agreement problem. The problem of k-set agreement is a generalization of consensus where processes can decide up to k different values. Although some solutions to this problem have been proposed in dynamic networks, they rely on communication synchrony or make strong assumptions on the number of process failures. In this paper we consider unknown dynamic systems modeled using the formalism of Time-Varying Graphs, and extend the definition of the existing $\Pi \Sigma _{x,y}$ failure detector to obtain the $\Pi \Sigma _{\bot, x,y}$ failure detector, which is sufficient to solve k-set agreement in our model. We then provide an implementation of this new failure detector using connectivity and message pattern assumptions. Finally, we present an algorithm using $\Pi \Sigma _{\bot, x,y}$ to solve k-set agreement.

Using formal methods for content validation of medical procedure documents

ObjectiveWe propose the use of a formal approach to support content validation of a standard operating procedure (SOP) for a therapeutic intervention. Such an approach provides a useful tool to identify ambiguities, omissions and inconsistencies, and improves the applicability and efficacy of documents in the health settings. Materials and methodsWe apply and evaluate a methodology originally proposed for the verification of software specification documents to a specific SOP. The verification methodology uses the graph formalism to model the document. Semi-automatic analysis identifies possible problems in the model and in the original document. The verification is an iterative process that identifies possible faults in the original text that should be revised by its authors and/or specialists. ResultsThe proposed method was able to identify 23 possible issues in the original document (ambiguities, omissions, redundant information, and inaccuracies, among others). The formal verification process aided the specialists to consider a wider range of usage scenarios and to identify which instructions form the kernel of the proposed SOP and which ones represent additional or required knowledge that are mandatory for the correct application of the medical document. ConclusionBy using the proposed verification process, a simpler and yet more complete SOP could be produced. As consequence, during the validation process the experts received a more mature document and could focus on the technical aspects of the procedure itself.

Ball bearing defect models: A study of simulated and experimental fault signatures

Numerical model based virtual prototype of a system can serve as a tool to generate huge amount of data which replace the dependence on expensive and often difficult to conduct experiments. However, the model must be accurate enough to substitute the experiments. The abstraction level and details considered during model development depend on the purpose for which simulated data should be generated. This article concerns development of simulation models for deep groove ball bearings which are used in a variety of rotating machinery. The purpose of the model is to generate vibration signatures which usually contain features of bearing defects. Three different models with increasing level-of-complexity are considered: a bearing kinematics based planar motion block diagram model developed in MATLAB Simulink which does not explicitly consider cage and traction dynamics, a planar motion model with cage, traction and contact dynamics developed using multi-energy domain bond graph formalism in SYMBOLS software, and a detailed spatial multi-body dynamics model with complex contact and traction mechanics developed using ADAMS software. Experiments are conducted using Spectra Quest machine fault simulator with different prefabricated faulted bearings. The frequency domain characteristics of simulated and experimental vibration signals for different bearing faults are compared and conclusions are drawn regarding usefulness of the developed models.

Behavioral Service Graphs: A formal data-driven approach for prompt investigation of enterprise and internet-wide infections

The task of generating network-based evidence to support network forensic investigation is becoming increasingly prominent. Undoubtedly, such evidence is significantly imperative as it not only can be used to diagnose and respond to various network-related issues (i.e., performance bottlenecks, routing issues, etc.) but more importantly, can be leveraged to infer and further investigate network security intrusions and infections. In this context, this paper proposes a proactive approach that aims at generating accurate and actionable network-based evidence related to groups of compromised network machines (i.e., campaigns). The approach is envisioned to guide investigators to promptly pinpoint such malicious groups for possible immediate mitigation as well as empowering network and digital forensic specialists to further examine those machines using auxiliary collected data or extracted digital artifacts. On one hand, the promptness of the approach is successfully achieved by monitoring and correlating perceived probing activities, which are typically the very first signs of an infection or misdemeanors. On the other hand, the generated evidence is accurate as it is based on an anomaly inference that fuses data behavioral analytics in conjunction with formal graph theoretic concepts. We evaluate the proposed approach in two deployment scenarios, namely, as an enterprise edge engine and as a global capability in a security operations center model. The empirical evaluation that employs 10 GB of real botnet traffic and 80 GB of real darknet traffic indeed demonstrates the accuracy, effectiveness and simplicity of the generated network-based evidence.

GEL: A Platform-Independent Reasoner for Parallel Classification with OWL EL Ontologies Using Graph Representation

In the community of Semantic Web, the state-of-the-art reasoners are all implemented on specific platforms. As the Web Ontology Language (OWL) has been widely used in different real-world applications, it is required that the task of reasoning can be flexibly adapted to different platforms. In this paper, we take the first effort to give a platformindependent approach for parallel classification of the description logic OWL EL, which is a tractable fragment of OWL 2. Classification, which is the task of computing a subsumption hierarchy between concepts, plays an important role in many applications of OWL EL. The current classification methods rely on the specific parallel computation platforms and can hardly achieve a tradeoff between efficiency and scalability. To develop a platform-independent approach for performing classification in OWL EL, we first give a novel and well defined graph formalism GEL for representing EL ontologies and present a group of sound and complete rules for ontology classification on a GEL graph. Based on this formalism, we design a parallel classification algorithm, which can be implemented on different parallel computation platforms, and we also show the correctness of the algorithm. We implement a system, which can easily switch between multi-core and a distributed cluster. Finally, we conduct experiments on several real-world OWL EL ontologies. The experimental results show that our system outperforms two state-of-the-art EL reasoning systems, and has a linear scalability on the extensions of GO ontologies.

Failure Prognostics of Locomotive Electro-Pneumatic Brake Based on Bond Graph Modeling

This paper proposes a novel analysis methodology applying bond graph (BG) theory for dynamic systems prognostics, which is realized through the derivation of a mathematical model from physical knowledge using the BG formalism. The graphical formalism allows generating residuals to derive the system degradation model. Moreover, the performance threshold can be determined by stability analysis to predict remain useful life of degraded components. The efficiency of the proposed methodology was demonstrated through a simulation experiment for locomotive electronically controlled pneumatic brake. A leakage fault of relay valve is injected and then predicted. The experimental results show that well performance can be obtained with lower uncertainty, which make the prognostics analysis suitable for engineering application in short of sufficient historic data.

Model proposal for representing a deep coal mine spatial and functional structure

Abstract Underground coal mining usually requires the development of a set of underground corridors (workings). The workings fulfill many different functions. They are used for transportation, ventilation, dewatering and even escape pathways. The proposition of a formal representation of a working's structure for deep coal mining has been presented. The model was developed as a basis for the software system, support management and operational activities for longwall deep mine. The proposed solution is based on graph formalism along with its matrix representation. However, the idea of matrix representation is enhanced. Not only are the topological properties of workings structure considered, but also information about their functions and spatial characteristic. The object model was designed and implemented based upon the matrix idea.

Some Structures of Hemirings

Hemirings appear in a natural manner, in some applications to the theory of automata, the theory of formal languages, graph theory, design theory and combinatorial geometry. Recently, the notions of hemirings with special structures were introduced. But still now there are no complete structural properties of hemirings. In this paper we try to investigate some structures of hemirings. This is done by introducing some examples of hemirings.

Improving the Domain Independence of Data Provenance Ontologies

Provenance is becoming increasingly important as more and more people are using data that they themselves did not generate. In the last decade, significant efforts have been directed toward developing generic, shared data provenance ontologies that support the interoperability of provenance across systems. An issue that is impeding the use of such provenance ontologies is that a generic provenance ontology, no matter how complete it is, is insufficient for capturing the diverse, complex provenance requirements in different domains. In this paper, the authors propose a novel approach to adapting and extending the W7 model, a well-known generic ontology of data provenance. Relying on various knowledge expansion mechanisms provided by the Conceptual Graph formalism, the authors' approach enables us to develop domain ontologies of provenance in a disciplined yet flexible way.

Big Data Behavioral Analytics Meet Graph Theory: On Effective Botnet Takedowns

Cyberspace continues to host highly sophisticated malicious entities that have demonstrated their ability to launch debilitating, intimidating, and disrupting cyber attacks. Recently, such entities have been adopting orchestrated, often botmaster- coordinated, stealthy attack strategies aimed at maximizing their targets' coverage while minimizing redundancy and overlap. The latter entities, which are typically dubbed as bots within botnets, are ominously being leveraged to cause drastic Internet-wide and enterprise impacts by means of severe misdemeanors. While a plethora of literature approaches have devised operational cyber security techniques for the detection of such botnets, very few have tackled the problem of how to promptly and effectively takedown such botnets. In the past three years, we have received 12 GB of daily malicious real darknet data (i.e., Internet traffic destined to half a million routable but unallocated IP addresses or sensors) from more than 12 countries. This article exploits such data to propose a novel Internet-scale cyber security capability that fuses big data behavioral analytics in conjunction with formal graph theoretical concepts to infer and attribute Internet-scale infected bots in a prompt manner and identify the niche of the botnet for effective takedowns. We validate the accuracy of the proposed approach by employing 100 GB of the Carna botnet, which is a very recent real malicious Internet-scale botnet. Since performance is also an imperative metric when dealing with big data for network security, this article further provides a comparison between two trending big data processing architectures: the almost standard Apache Hadoop system, and a more traditional and simplistic multi-threaded programming approach, by employing 1 TB of real darknet data. Several recommendations and possible future research work derived from the previous experiments conclude this article.