Generalized sparse metric learning with relative comparisons

The objective of sparse metric learning is to learn a distance measure from a set of data in addition to finding a low-dimensional representation. Despite demonstrated success, the performance of existing sparse metric learning approaches is usually limited because the methods assumes certain problem relaxations or they target the SML objective indirectly. In this paper, we propose a Generalized Sparse Metric Learning method. This novel framework offers a unified view for understanding many existing sparse metric learning algorithms including the Sparse Metric Learning framework proposed in (Rosales and Fung ACM International conference on knowledge discovery and data mining (KDD), pp 367–373, 2006), the Large Margin Nearest Neighbor (Weinberger et al. in Advances in neural information processing systems (NIPS), 2006; Weinberger and Saul in Proceedings of the twenty-fifth international conference on machine learning (ICML-2008), 2008), and the D-ranking Vector Machine (D-ranking VM) (Ouyang and Gray in Proceedings of the twenty-fifth international conference on machine learning (ICML-2008), 2008). Moreover, GSML also establishes a close relationship with the Pairwise Support Vector Machine (Vert et al. in BMC Bioinform, 8, 2007). Furthermore, the proposed framework is capable of extending many current non-sparse metric learning models to their sparse versions including Relevant Component Analysis (Bar-Hillel et al. in J Mach Learn Res, 6:937–965, 2005) and a state-of-the-art method proposed in (Xing et al. Advances in neural information processing systems (NIPS), 2002). We present the detailed framework, provide theoretical justifications, build various connections with other models, and propose an iterative optimization method, making the framework both theoretically important and practically scalable for medium or large datasets. Experimental results show that this generalized framework outperforms six state-of-the-art methods with higher accuracy and significantly smaller dimensionality for seven publicly available datasets.     

Petri nets as a framework for the reconstruction and analysis of signal transduction pathways and regulatory networks

Petri nets are directed, weighted bipartite graphs that have successfully been applied to the systems biology of metabolic and signal transduction pathways in modeling both stochastic (discrete) and deterministic (continuous) processes. Here we exemplify how molecular mechanisms, biochemical or genetic, can be consistently respresented in the form of place/transition Petri nets. We then describe the application of Petri nets to the reconstruction of molecular and genetic networks from experimental data and their power to represent biological processes with arbitrary degree of resolution of the subprocesses at the cellular and the molecular level. Petri nets are executable formal language models that permit the unambiguous visualization of regulatory mechanisms, and they can be used to encode the results of mathematical algorithms for the reconstruction of causal interaction networks from experimental time series data.     

Petri net models for the semi-automatic construction of large scale biological networks

For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. During the last 15 years, Petri nets have attracted more and more attention to help to solve this key problem. Regarding the published papers, it seems clear that hybrid functional Petri nets are the adequate method to model complex biological networks. Today, a Petri net model of biological networks is built manually by drawing places, transitions and arcs with mouse events. Therefore, based on relevant molecular database and information systems biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the application of Petri nets for modeling and simulation of biological networks. Furthermore, we will present a type of access to relevant metabolic databases such as KEGG, BRENDA, etc. Based on this integration process, the system supports semi-automatic generation of the correlated hybrid Petri net model. A case study of the cardio-disease related gene-regulated biological network is also presented. MoVisPP is available at .     

Automatic construction of systems of distributed components from nested Petri nets models

Multi-level multi-agent systems (MASs) with dynamic structure are widely used in solving important applied problems in telecommunication, transportation, social, and other systems. Therefore, ensuring correct behavior of such systems is an actual and important task. One of the most error-prone stages of system development in the framework of model-oriented approach is the implementation stage, in the course of which a program code is constructed based on the model developed. This paper presents an algorithm for automated translation of MAS models represented as nested Petri nets into systems of distributed components. Nested Petri nets are the extension of Petri nets in the framework of the nets-within-nets approach, which assumes that tokens in a Petri net may themselves be Petri nets, possess autonomous behavior, and interact with other tokens of the net. This makes it possible to model MASs with dynamic structure in a natural way. The translation presented in this paper preserves distribution level and important behavioral properties (safety, liveness, and conditional liveness) of the original model and ensures fairness of the target system execution. The use of such translation makes it possible to automate construction of distributed MASs by models of nested Petri nets. As a test example, translation of nested Petri nets into systems of distributed components was implemented on the basis of the EJB component technology.     

Petri网在生物信息学中的应用

生物信息学是一门正在快速发展的使用数学和计算机技术来构造和分析生物学模型的学科.Petri网是近来被用于生物信息学的有效工具,但是应用的深度和广度还有待深入研究.文中综述了Petri网在生物信息学领域应用的最新研究进展,主要包括三个方面:应用位置/变迁网定性分析生物学对象的结构性质;应用随机Petri网将随机性加入到生物学建模和分析中;应用混合Petri网描述和分析同时具有离散特性和连续特性的生物系统.最后对Petri网在生物信息学领域的应用情况进行总结并展望了未来的研究方向.     

A Petri net representation of Bayesian message flows: importance of Bayesian networks for biological applications

This article combines Bayes’ theorem with flows of probabilities, flows of evidences (likelihoods), and fundamental concepts for learning Bayesian networks as biological models from data. There is a huge amount of biological applications of Bayesian networks. For example in the fields of protein modeling, pathway modeling, gene expression analysis, DNA sequence analysis, protein–protein interaction, or protein–DNA interaction. Usually, the Bayesian networks have to be learned (statistically constructed) from array data. Then they are considered as an executable and analyzable model of the data source. To improve that, this work introduces a Petri net representation for the propagation of probabilities and likelihoods in Bayesian networks. The reason for doing so is to exploit the structural and dynamic properties of Petri nets for increasing the transparency of propagation processes. Consequently the novel Petri nets are called “probability propagation nets”. By means of examples it is shown that the understanding of the Bayesian propagation algorithm is improved. This is of particular importance for an exact visualization of biological systems by Bayesian networks.     

Specifications for decidable hybrid games

We introduce STORMED hybrid games (SHG), a generalization of STORMED hybrid systems, Vladimerou et al. (2008) [33], which have natural specifications that allow rich continuous dynamics and various decidable properties. We solve the control problem for SHG using a reduction to bisimulation on finite game graphs. This generalizes to a greater family of games, which includes o-minimal hybrid games, Bouyer et al. (2006) [6]. We also solve the optimal-cost reachability problem for Weighted SHG and prove decidability of WCTL for Weighted STORMED hybrid systems.     

Petri nets, algebras, morphisms, and compositionality

It is shown how a category of Petri nets can be viewed as a subcategory of two sorted algebras over multisets. This casts Petri nets in a familiar framework and provides a useful idea of morphism on nets different from the conventional definition—the morphisms here respect the behaviour of nets. The categorical constructions which result provide a useful way to synthesise nets and reason about nets in terms of their components; for example, various forms of parallel composition of Petri nets arise naturally from the product in the category. This abstract setting makes plain a useful functor from the category of Petri nets to a category of spaces of invariants and provides insight into the generalisations of the basic definition of Petri nets—for instance, the coloured and higher level nets of Kurt Jensen arise through a simple modification of the sorts of the algebras underlying nets. Further, it provides a smooth formal relation with other models of concurrency such as Milner's calculus of communicating systems (CCS) and Hoare's communicating sequential processes (CSP), though this is only indicated in this paper.     

Realistic Brownian Dynamics simulations of biological molecule separation in nanofluidic devices

We present a Brownian Dynamics model of biological molecule separation in periodic nanofilter arrays. The biological molecules are modeled using the Worm-Like-Chain model with Hydrodynamic Interactions. We focus on short dsDNA molecules; this places the separation process either in the Ogston sieving regime or the transition region between Ogston sieving and entropic trapping. Our simulation results are validated using the experimental results of Fu et al. (Phys Rev Lett 97:018103, 2006); particular attention is paid to the model’s ability to quantitatively capture experimental results using realistic values of all physical parameters. Our simulation results showed that molecule mobility is sensitive to the device geometry. Moreover, our model is used for validating the theoretical prediction of Li et al. (Anal Bioanal Chem 394:427–435, 2009) who proposed a separation process featuring an asymmetric device and an electric field of alternating polarity. Good agreement is found between our simulation results and the predictions of the theoretical model of Li et al.     

Comments on “A Gaussian approximation recursive filter for nonlinear systems with correlated noises” [Automatica 48 (2012) 2290–2297]

This note points out that the framework proposed in (Wang et al., 2012) is equivalent to the conventional de-coupling framework introduced in some textbooks; see e.g. (Bar-Shalom et al., 2001).     

Deadlock-Freeness Analysis of Continuous Mono-T-Semiflow Petri Nets

Most verification techniques for highly populated discrete systems suffer from the state explosion problem. The “fluidification” of discrete systems is a classical relaxation technique that aims to avoid the state explosion problem. Continuous Petri nets are the result of fluidifying traditional discrete Petri nets. In continuous Petri nets the firing of a transition is not constrained to the naturals but to the non-negative reals. Unfortunately, some important properties, as liveness, may not be preserved when the discrete net model is fluidified. Therefore, a thorough study of the properties of continuous Petri nets is required. This paper focuses on the study of deadlock-freeness in the framework of mono-T-semiflow continuous Petri nets, i.e., conservative nets with a single repetitive sequence (T-semiflow). The study is developed both on untimed and timed systems. Topological necessary conditions are extracted for this property. Moreover, a bridge relating deadlock-freeness conditions for untimed and timed systems is established.     

Hardness of equivalence checking for composed finite-state systems

Computational complexity of comparing behaviours of systems composed from interacting finite-state components is considered. The main result shows that the respective problems are EXPTIME-hard for all relations between bisimulation equivalence and trace preorder, as conjectured by Rabinovich (Inf Comput 139(2):111–129, 1997). The result is proved for a specific model of parallel compositions where the components synchronize on shared actions but it can be easily extended to other similar models,   to labelled 1-safe Petri nets. Further hardness results are shown for special cases of acyclic systems.     

SimQPN—A tool and methodology for analyzing queueing Petri net models by means of simulation

The queueing Petri net (QPN) paradigm provides a number of benefits over conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using queueing Petri nets (QPNs), one can integrate both hardware and software aspects of system behavior into the same model. This lends itself very well to modeling distributed component-based systems, such as modern e-business applications. However, currently available tools and techniques for QPN analysis suffer the state space explosion problem, imposing a limit on the size of the models that are tractable. In this paper, we present SimQPN—a simulation tool for QPNs that provides an alternative approach to analyze QPN models, circumventing the state space explosion problem. In doing this, we propose a methodology for analyzing QPN models by means of discrete event simulation. The methodology shows how to simulate QPN models and analyze the output data from simulation runs. We validate our approach by applying it to study several different QPN models, ranging from simple models to models of realistic systems. The performance of point and interval estimators implemented in SimQPN is subjected to a rigorous experimental analysis.     

Petri网的符号ZBDD可达树分析技术

Petri网是一种适合于并发系统建模、分析和控制的图形工具.可达树是Petri网分析的典型技术之一,它通过标识向量集合表征系统的状态空间,组合复杂性严重制约了该分析技术可处理系统问题的规模.零压缩决策图(Zero-Suppressed Binary Decision Diagrams,ZBDD)是一种新型的数据结构,是表示和处理稀疏向量集合的一种有效技术.文章基于Petri网町达标识向量的稀疏特征,给出了Petri网分析的符号ZBDD技术,该技术通过对标识向量(状态)的布尔向量表示、可达标识向最(状态)的符号ZBDD生成,实现Petri网可达状态空间的高效符号操作和紧凑符号表示.实验表明,基于ZBDD的符号可达性分析算法能够有效处理较大规模Petri网问题.     

Robot task plan representation by Petri nets: modelling, identification, analysis and execution

In this paper we introduce a framework to represent robot task plans based on Petri nets. Our approach enables modelling a robot task, analysing its qualitative and quantitative properties and using the Petri net representation for actual plan execution. The overall model is obtained from the composition of simple models, leading to a modular approach. Analysis is applied to a closed loop between the robot controller and the environment Petri net models. We focus here on the quantitative properties, captured by stochastic Petri net models. Furthermore, we introduce a method to identify the environment and action layer parameters of the stochastic Petri net models from real data, improving the significance of the model. The framework building blocks and a single-robot task model are detailed. Results of a case study with simulated soccer robots show the ability of the framework to provide a systematic modelling tool, and of determining, through well-known analysis methods for stochastic Petri nets, relevant properties of the task plan applied to a particular environment.     

On enumerating minimal siphons in Petri nets using CLP and SAT solvers: theoretical and practical complexity

Petri nets are a simple formalism for modeling concurrent computation. They are also an interesting tool for modeling and analysing biochemical reaction systems, bridging the gap between purely qualitative and quantitative models. Biological networks can indeed be complex, large, and with many unknown kinetic parameters, which makes the development of quantitative models difficult. In this paper, we focus on the Petri net representation of biochemical reactions and on two structural properties of Petri nets, siphons and traps, that bring us information about the persistence of some molecular species, independently of the kinetics. We first study the theoretical time complexity of minimal siphon decision problems in general Petri nets, and present three new complexity results: first, we show that the existence of a siphon of a given cardinality is NP-complete; second, we prove that deciding the Siphon-Trap property is co-NP-complete; third, we prove that deciding the existence of a minimal siphon containing a given set of places, deciding the existence of a siphon of a given cardinality and deciding the Siphon-Trap property can be done in linear time in Petri nets of bounded tree-width. Then, we present a Boolean model of siphons and traps, and two method for enumerating all minimal siphons and traps of a Petri net, by using a SAT solver and a Constraint Logic Program (CLP) respectively. On a benchmark of 345 Petri nets of hundreds of places and transitions, extracted from biological models from the BioModels repository, as well as on a benchmark composed of 80 Petri nets from the Petriweb database of industrial processes, we show that both the SAT and CLP methods are overall faster by one or two orders of magnitude compared to the state-of-the-art algorithm from the Petri net community, and are in fact able to solve all the enumeration problems of our practical benchmarks. We investigate why these programs perform so well in practice, and provide some elements of explanation related to our theoretical complexity results.     

Modeling, Simulation and Analysis of Batch Production Systems

After a surveyof some approaches for modeling hybrid systems by means of Petrinets ( t-time Petri nets, colored Petri nets, hybridPetri nets and differential predicate transition nets), thispaper illustrates how these formal models can be used for simulationand validation. It is shown how it was possible to use aggregatedqualitative models concurrently with detailed ones.     

State equation, controllability, and maximal matchings of petri nets

Petri nets are a versatile modeling device for studying the structure and control of concurrent systems. Petri nets and related graph models have been used for modeling a wide variety of systems from computers to social systems. In order to introduce this interesting modeling device to the researcher in control theory, this paper discusses Petri nets in the context of the state equation for a linear discrete-time system. The controllability concept of dynamic systems is applied to Petri nets for the first time. It is also shown that the controllability and reachability of a Petri net are related to maximal matchings of its bipartite graph.     

Petri nets modeling and analysis using extended bag-theoreticrelational algebra

Petri nets are a powerful modeling tool for studying reactive, concurrent systems. Analysis of the nets can reveal important information concerning the behavior of a modeled system. While various means for the analysis of the nets has been developed, a major limitation in the analysis, is explosion of large states space in simulation. An efficient method to manage large states space would overcome such a limitation. This paper proposes a framework for the modeling and analysis of Petri nets using relational database technologies. Formalism of the framework is based on a bag-theoretic relational algebra extended from the conventional, Within the framework, Petri nets are formalized by bag relations, and analysis algorithms are developed based on such formal relations. Properties associated with the nets are formalized by queries described in terms of the bag-theoretic relational algebra. The framework has been realized in a commercial relational database system using a standard SQL.