Optimization-Based Approaches to Control of Probabilistic Boolean Networks
Directory of Open Access Journals (Sweden)
Koichi Kobayashi
2017-02-01
Full Text Available Control of gene regulatory networks is one of the fundamental topics in systems biology. In the last decade, control theory of Boolean networks (BNs, which is well known as a model of gene regulatory networks, has been widely studied. In this review paper, our previously proposed methods on optimal control of probabilistic Boolean networks (PBNs are introduced. First, the outline of PBNs is explained. Next, an optimal control method using polynomial optimization is explained. The finite-time optimal control problem is reduced to a polynomial optimization problem. Furthermore, another finite-time optimal control problem, which can be reduced to an integer programming problem, is also explained.
Caglar, Mehmet Umut; Pal, Ranadip
2011-03-01
Central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid''. However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of cell level data and probabilistic - nonlinear nature of interactions. Several models widely used to analyze and simulate these types of nonlinear interactions. Stochastic Master Equation (SME) models give probabilistic nature of the interactions in a detailed manner, with a high calculation cost. On the other hand Probabilistic Boolean Network (PBN) models give a coarse scale picture of the stochastic processes, with a less calculation cost. Differential Equation (DE) models give the time evolution of mean values of processes in a highly cost effective way. The understanding of the relations between the predictions of these models is important to understand the reliability of the simulations of genetic regulatory networks. In this work the success of the mapping between SME, PBN and DE models is analyzed and the accuracy and affectivity of the control policies generated by using PBN and DE models is compared.
Computing preimages of Boolean networks.
Klotz, Johannes; Bossert, Martin; Schober, Steffen
2013-01-01
In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network. Our probabilistic method runs in linear time with respect to the number of nodes in the network. We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases.
Goodstein, R L
2007-01-01
This elementary treatment by a distinguished mathematician employs Boolean algebra as a simple medium for introducing important concepts of modern algebra. Numerous examples appear throughout the text, plus full solutions.
Boolean reasoning the logic of boolean equations
Brown, Frank Markham
2012-01-01
A systematic treatment of Boolean reasoning, this concise, newly revised edition combines the works of early logicians with recent investigations, including previously unpublished research results. Brown begins with an overview of elementary mathematical concepts and outlines the theory of Boolean algebras. Two concluding chapters deal with applications. 1990 edition.
Free Boolean Topological Groups
Directory of Open Access Journals (Sweden)
Ol’ga Sipacheva
2015-11-01
Full Text Available Known and new results on free Boolean topological groups are collected. An account of the properties that these groups share with free or free Abelian topological groups and properties specific to free Boolean groups is given. Special emphasis is placed on the application of set-theoretic methods to the study of Boolean topological groups.
Solomon, Alan D
2012-01-01
REA's Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Boolean Algebra includes set theory, sentential calculus, fundamental ideas of Boolean algebras, lattices, rings and Boolean algebras, the structure of a Boolean algebra, and Boolean
International Nuclear Information System (INIS)
Korshunov, A D
2003-01-01
Monotone Boolean functions are an important object in discrete mathematics and mathematical cybernetics. Topics related to these functions have been actively studied for several decades. Many results have been obtained, and many papers published. However, until now there has been no sufficiently complete monograph or survey of results of investigations concerning monotone Boolean functions. The object of this survey is to present the main results on monotone Boolean functions obtained during the last 50 years
Tucker, Jerry H.; Tapia, Moiez A.; Bennett, A. Wayne
1988-01-01
The concept of Boolean integration is developed, and different Boolean integral operators are introduced. Given the changes in a desired function in terms of the changes in its arguments, the ways of 'integrating' (i.e. realizing) such a function, if it exists, are presented. The necessary and sufficient conditions for integrating, in different senses, the expression specifying the changes are obtained. Boolean calculus has applications in the design of logic circuits and in fault analysis.
Interpolative Boolean Networks
Directory of Open Access Journals (Sweden)
Vladimir Dobrić
2017-01-01
Full Text Available Boolean networks are used for modeling and analysis of complex systems of interacting entities. Classical Boolean networks are binary and they are relevant for modeling systems with complex switch-like causal interactions. More descriptive power can be provided by the introduction of gradation in this model. If this is accomplished by using conventional fuzzy logics, the generalized model cannot secure the Boolean frame. Consequently, the validity of the model’s dynamics is not secured. The aim of this paper is to present the Boolean consistent generalization of Boolean networks, interpolative Boolean networks. The generalization is based on interpolative Boolean algebra, the [0,1]-valued realization of Boolean algebra. The proposed model is adaptive with respect to the nature of input variables and it offers greater descriptive power as compared with traditional models. For illustrative purposes, IBN is compared to the models based on existing real-valued approaches. Due to the complexity of the most systems to be analyzed and the characteristics of interpolative Boolean algebra, the software support is developed to provide graphical and numerical tools for complex system modeling and analysis.
Properties of Boolean orthoposets
Tkadlec, Josef
1993-10-01
A Boolean orthoposet is the orthoposet P fulfilling the following condition: If a, b ∈ P and a ∧ b = 0, then a ⊥ b. This condition seems to be a sound generalization of distributivity in orthoposets. Also, the class of (orthomodular) Boolean orthoposets may play an interesting role in quantum logic theory. This class is wide enough and, on the other hand, enjoys some properties of Boolean algebras. In this paper we summarize results on Boolean orthoposets involving distributivity, set representation, properties of the state space, existence of Jauch-Piron states, and results concerning orthocompleteness and completion.
Hildreth, Charles R.
1983-01-01
This editorial addresses the issue of whether or not to provide free-text, keyword/boolean search capabilities in the information retrieval mechanisms of online public access catalogs and discusses online catalogs developed prior to 1980--keyword searching, phrase searching, and precoordination and postcoordination. (EJS)
Algebraic partial Boolean algebras
International Nuclear Information System (INIS)
Smith, Derek
2003-01-01
Partial Boolean algebras, first studied by Kochen and Specker in the 1960s, provide the structure for Bell-Kochen-Specker theorems which deny the existence of non-contextual hidden variable theories. In this paper, we study partial Boolean algebras which are 'algebraic' in the sense that their elements have coordinates in an algebraic number field. Several of these algebras have been discussed recently in a debate on the validity of Bell-Kochen-Specker theorems in the context of finite precision measurements. The main result of this paper is that every algebraic finitely-generated partial Boolean algebra B(T) is finite when the underlying space H is three-dimensional, answering a question of Kochen and showing that Conway and Kochen's infinite algebraic partial Boolean algebra has minimum dimension. This result contrasts the existence of an infinite (non-algebraic) B(T) generated by eight elements in an abstract orthomodular lattice of height 3. We then initiate a study of higher-dimensional algebraic partial Boolean algebras. First, we describe a restriction on the determinants of the elements of B(T) that are generated by a given set T. We then show that when the generating set T consists of the rays spanning the minimal vectors in a real irreducible root lattice, B(T) is infinite just if that root lattice has an A 5 sublattice. Finally, we characterize the rays of B(T) when T consists of the rays spanning the minimal vectors of the root lattice E 8
Institute of Scientific and Technical Information of China (English)
Antonio AIZPURU; Antonio GUTI(E)RREZ-D(A)VILA
2004-01-01
In this paper we will study some families and subalgebras ( ) of ( )(N) that let us characterize the unconditional convergence of series through the weak convergence of subseries ∑i∈A xi, A ∈ ( ).As a consequence, we obtain a new version of the Orlicz-Pettis theorem, for Banach spaces. We also study some relationships between algebraic properties of Boolean algebras and topological properties of the corresponding Stone spaces.
Computational complexity of Boolean functions
Energy Technology Data Exchange (ETDEWEB)
Korshunov, Aleksei D [Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk (Russian Federation)
2012-02-28
Boolean functions are among the fundamental objects of discrete mathematics, especially in those of its subdisciplines which fall under mathematical logic and mathematical cybernetics. The language of Boolean functions is convenient for describing the operation of many discrete systems such as contact networks, Boolean circuits, branching programs, and some others. An important parameter of discrete systems of this kind is their complexity. This characteristic has been actively investigated starting from Shannon's works. There is a large body of scientific literature presenting many fundamental results. The purpose of this survey is to give an account of the main results over the last sixty years related to the complexity of computation (realization) of Boolean functions by contact networks, Boolean circuits, and Boolean circuits without branching. Bibliography: 165 titles.
Cryptographic Boolean functions and applications
Cusick, Thomas W
2009-01-01
Boolean functions are the building blocks of symmetric cryptographic systems. Symmetrical cryptographic algorithms are fundamental tools in the design of all types of digital security systems (i.e. communications, financial and e-commerce).Cryptographic Boolean Functions and Applications is a concise reference that shows how Boolean functions are used in cryptography. Currently, practitioners who need to apply Boolean functions in the design of cryptographic algorithms and protocols need to patch together needed information from a variety of resources (books, journal articles and other sources). This book compiles the key essential information in one easy to use, step-by-step reference. Beginning with the basics of the necessary theory the book goes on to examine more technical topics, some of which are at the frontier of current research.-Serves as a complete resource for the successful design or implementation of cryptographic algorithms or protocols using Boolean functions -Provides engineers and scient...
Geometric Operators on Boolean Functions
DEFF Research Database (Denmark)
Frisvad, Jeppe Revall; Falster, Peter
In truth-functional propositional logic, any propositional formula represents a Boolean function (according to some valuation of the formula). We describe operators based on Decartes' concept of constructing coordinate systems, for translation of a propositional formula to the image of a Boolean...... function. With this image of a Boolean function corresponding to a propositional formula, we prove that the orthogonal projection operator leads to a theorem describing all rules of inference in propositional reasoning. In other words, we can capture all kinds of inference in propositional logic by means...... of a few geometric operators working on the images of Boolean functions. The operators we describe, arise from the niche area of array-based logic and have previously been tightly bound to an array-based representation of Boolean functions. We redefine the operators in an abstract form to make them...
Sound Probabilistic #SAT with Projection
Directory of Open Access Journals (Sweden)
Vladimir Klebanov
2016-10-01
Full Text Available We present an improved method for a sound probabilistic estimation of the model count of a boolean formula under projection. The problem solved can be used to encode a variety of quantitative program analyses, such as concerning security of resource consumption. We implement the technique and discuss its application to quantifying information flow in programs.
Boolean-Valued Belief Functions
Czech Academy of Sciences Publication Activity Database
Kramosil, Ivan
2002-01-01
Roč. 31, č. 2 (2002), s. 153-181 ISSN 0308-1079 R&D Projects: GA AV ČR IAA1030803 Institutional research plan: AV0Z1030915 Keywords : Dempster-Schafer theory * Boolean algebra Subject RIV: BA - General Mathematics Impact factor: 0.241, year: 2002
SETS, Boolean Manipulation for Network Analysis and Fault Tree Analysis
International Nuclear Information System (INIS)
Worrell, R.B.
1985-01-01
Description of problem or function - SETS is used for symbolic manipulation of set (or Boolean) equations, particularly the reduction of set equations by the application of set identities. It is a flexible and efficient tool for performing probabilistic risk analysis (PRA), vital area analysis, and common cause analysis. The equation manipulation capabilities of SETS can also be used to analyze non-coherent fault trees and determine prime implicants of Boolean functions, to verify circuit design implementation, to determine minimum cost fire protection requirements for nuclear reactor plants, to obtain solutions to combinatorial optimization problems with Boolean constraints, and to determine the susceptibility of a facility to unauthorized access through nullification of sensors in its protection system. 4. Method of solution - The SETS program is used to read, interpret, and execute the statements of a SETS user program which is an algorithm that specifies the particular manipulations to be performed and the order in which they are to occur. 5. Restrictions on the complexity of the problem - Any properly formed set equation involving the set operations of union, intersection, and complement is acceptable for processing by the SETS program. Restrictions on the size of a set equation that can be processed are not absolute but rather are related to the number of terms in the disjunctive normal form of the equation, the number of literals in the equation, etc. Nevertheless, set equations involving thousands and even hundreds of thousands of terms can be processed successfully
Optical programmable Boolean logic unit.
Chattopadhyay, Tanay
2011-11-10
Logic units are the building blocks of many important computational operations likes arithmetic, multiplexer-demultiplexer, radix conversion, parity checker cum generator, etc. Multifunctional logic operation is very much essential in this respect. Here a programmable Boolean logic unit is proposed that can perform 16 Boolean logical operations from a single optical input according to the programming input without changing the circuit design. This circuit has two outputs. One output is complementary to the other. Hence no loss of data can occur. The circuit is basically designed by a 2×2 polarization independent optical cross bar switch. Performance of the proposed circuit has been achieved by doing numerical simulations. The binary logical states (0,1) are represented by the absence of light (null) and presence of light, respectively.
Boolean gates on actin filaments
International Nuclear Information System (INIS)
Siccardi, Stefano; Tuszynski, Jack A.; Adamatzky, Andrew
2016-01-01
Actin is a globular protein which forms long polar filaments in the eukaryotic cytoskeleton. Actin networks play a key role in cell mechanics and cell motility. They have also been implicated in information transmission and processing, memory and learning in neuronal cells. The actin filaments have been shown to support propagation of voltage pulses. Here we apply a coupled nonlinear transmission line model of actin filaments to study interactions between voltage pulses. To represent digital information we assign a logical TRUTH value to the presence of a voltage pulse in a given location of the actin filament, and FALSE to the pulse's absence, so that information flows along the filament with pulse transmission. When two pulses, representing Boolean values of input variables, interact, then they can facilitate or inhibit further propagation of each other. We explore this phenomenon to construct Boolean logical gates and a one-bit half-adder with interacting voltage pulses. We discuss implications of these findings on cellular process and technological applications. - Highlights: • We simulate interaction between voltage pulses using on actin filaments. • We use a coupled nonlinear transmission line model. • We design Boolean logical gates via interactions between the voltage pulses. • We construct one-bit half-adder with interacting voltage pulses.
Boolean gates on actin filaments
Energy Technology Data Exchange (ETDEWEB)
Siccardi, Stefano, E-mail: ssiccardi@2ssas.it [The Unconventional Computing Centre, University of the West of England, Bristol (United Kingdom); Tuszynski, Jack A., E-mail: jackt@ualberta.ca [Department of Oncology, University of Alberta, Edmonton, Alberta (Canada); Adamatzky, Andrew, E-mail: andrew.adamatzky@uwe.ac.uk [The Unconventional Computing Centre, University of the West of England, Bristol (United Kingdom)
2016-01-08
Actin is a globular protein which forms long polar filaments in the eukaryotic cytoskeleton. Actin networks play a key role in cell mechanics and cell motility. They have also been implicated in information transmission and processing, memory and learning in neuronal cells. The actin filaments have been shown to support propagation of voltage pulses. Here we apply a coupled nonlinear transmission line model of actin filaments to study interactions between voltage pulses. To represent digital information we assign a logical TRUTH value to the presence of a voltage pulse in a given location of the actin filament, and FALSE to the pulse's absence, so that information flows along the filament with pulse transmission. When two pulses, representing Boolean values of input variables, interact, then they can facilitate or inhibit further propagation of each other. We explore this phenomenon to construct Boolean logical gates and a one-bit half-adder with interacting voltage pulses. We discuss implications of these findings on cellular process and technological applications. - Highlights: • We simulate interaction between voltage pulses using on actin filaments. • We use a coupled nonlinear transmission line model. • We design Boolean logical gates via interactions between the voltage pulses. • We construct one-bit half-adder with interacting voltage pulses.
Reliable dynamics in Boolean and continuous networks
International Nuclear Information System (INIS)
Ackermann, Eva; Drossel, Barbara; Peixoto, Tiago P
2012-01-01
We investigate the dynamical behavior of a model of robust gene regulatory networks which possess ‘entirely reliable’ trajectories. In a Boolean representation, these trajectories are characterized by being insensitive to the order in which the nodes are updated, i.e. they always go through the same sequence of states. The Boolean model for gene activity is compared with a continuous description in terms of differential equations for the concentrations of mRNA and proteins. We found that entirely reliable Boolean trajectories can be reproduced perfectly in the continuous model when realistic Hill coefficients are used. We investigate to what extent this high correspondence between Boolean and continuous trajectories depends on the extent of reliability of the Boolean trajectories, and we identify simple criteria that enable the faithful reproduction of the Boolean dynamics in the continuous description. (paper)
Quantum algorithms for testing Boolean functions
Directory of Open Access Journals (Sweden)
Erika Andersson
2010-06-01
Full Text Available We discuss quantum algorithms, based on the Bernstein-Vazirani algorithm, for finding which variables a Boolean function depends on. There are 2^n possible linear Boolean functions of n variables; given a linear Boolean function, the Bernstein-Vazirani quantum algorithm can deterministically identify which one of these Boolean functions we are given using just one single function query. The same quantum algorithm can also be used to learn which input variables other types of Boolean functions depend on, with a success probability that depends on the form of the Boolean function that is tested, but does not depend on the total number of input variables. We also outline a procedure to futher amplify the success probability, based on another quantum algorithm, the Grover search.
GLOBAL CONVERGENCE FOR THE XOR BOOLEAN NETWORKS
Ho, Juei-Ling
2009-01-01
Shih and Ho have proved a global convergent theorem for boolean network: if a map from $\\{0,1\\}^{n}$ to itself defines a boolean network has the conditions: (1) each column of the discrete Jacobian matrix of each element of $\\{0,1\\}^{n}$ is either a unit vector or a zero vector; (2) all the boolean eigenvalues of the discrete Jacobian matrix of this map evaluated at each element of $\\{0,1\\}^{n}$ are zero, then it has a unique fixed point and this boolean network is global convergent to the fi...
Rational Verification in Iterated Electric Boolean Games
Directory of Open Access Journals (Sweden)
Youssouf Oualhadj
2016-07-01
Full Text Available Electric boolean games are compact representations of games where the players have qualitative objectives described by LTL formulae and have limited resources. We study the complexity of several decision problems related to the analysis of rationality in electric boolean games with LTL objectives. In particular, we report that the problem of deciding whether a profile is a Nash equilibrium in an iterated electric boolean game is no harder than in iterated boolean games without resource bounds. We show that it is a PSPACE-complete problem. As a corollary, we obtain that both rational elimination and rational construction of Nash equilibria by a supervising authority are PSPACE-complete problems.
Boolean integral calculus for digital systems
Tucker, J. H.; Tapia, M. A.; Bennett, A. W.
1985-01-01
The concept of Boolean integration is introduced and developed. When the changes in a desired function are specified in terms of changes in its arguments, then ways of 'integrating' (i.e., realizing) the function, if it exists, are presented. Boolean integral calculus has applications in design of logic circuits.
On Boolean functions with generalized cryptographic properties
Braeken, A.; Nikov, V.S.; Nikova, S.I.; Preneel, B.; Canteaut, A.; Viswanathan, K.
2004-01-01
By considering a new metric, we generalize cryptographic properties of Boolean functions such as resiliency and propagation characteristics. These new definitions result in a better understanding of the properties of Boolean functions and provide a better insight in the space defined by this metric.
Probabilistic Relational Structures and Their Applications
Domotor, Zoltan
The principal objects of the investigation reported were, first, to study qualitative probability relations on Boolean algebras, and secondly, to describe applications in the theories of probability logic, information, automata, and probabilistic measurement. The main contribution of this work is stated in 10 definitions and 20 theorems. The basic…
Mining TCGA data using Boolean implications.
Directory of Open Access Journals (Sweden)
Subarna Sinha
Full Text Available Boolean implications (if-then rules provide a conceptually simple, uniform and highly scalable way to find associations between pairs of random variables. In this paper, we propose to use Boolean implications to find relationships between variables of different data types (mutation, copy number alteration, DNA methylation and gene expression from the glioblastoma (GBM and ovarian serous cystadenoma (OV data sets from The Cancer Genome Atlas (TCGA. We find hundreds of thousands of Boolean implications from these data sets. A direct comparison of the relationships found by Boolean implications and those found by commonly used methods for mining associations show that existing methods would miss relationships found by Boolean implications. Furthermore, many relationships exposed by Boolean implications reflect important aspects of cancer biology. Examples of our findings include cis relationships between copy number alteration, DNA methylation and expression of genes, a new hierarchy of mutations and recurrent copy number alterations, loss-of-heterozygosity of well-known tumor suppressors, and the hypermethylation phenotype associated with IDH1 mutations in GBM. The Boolean implication results used in the paper can be accessed at http://crookneck.stanford.edu/microarray/TCGANetworks/.
Stability of Boolean multilevel networks.
Cozzo, Emanuele; Arenas, Alex; Moreno, Yamir
2012-09-01
The study of the interplay between the structure and dynamics of complex multilevel systems is a pressing challenge nowadays. In this paper, we use a semiannealed approximation to study the stability properties of random Boolean networks in multiplex (multilayered) graphs. Our main finding is that the multilevel structure provides a mechanism for the stabilization of the dynamics of the whole system even when individual layers work on the chaotic regime, therefore identifying new ways of feedback between the structure and the dynamics of these systems. Our results point out the need for a conceptual transition from the physics of single-layered networks to the physics of multiplex networks. Finally, the fact that the coupling modifies the phase diagram and the critical conditions of the isolated layers suggests that interdependency can be used as a control mechanism.
Totally optimal decision trees for Boolean functions
Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
2016-01-01
We study decision trees which are totally optimal relative to different sets of complexity parameters for Boolean functions. A totally optimal tree is an optimal tree relative to each parameter from the set simultaneously. We consider the parameters
Random networks of Boolean cellular automata
Energy Technology Data Exchange (ETDEWEB)
Miranda, Enrique [Comision Nacional de Energia Atomica, San Carlos de Bariloche (Argentina). Centro Atomico Bariloche
1990-01-01
Some recent results about random networks of Boolean automata -the Kauffman model- are reviewed. The structure of configuration space is explored. Ultrametricity between cycles is analyzed and the effects of noise in the dynamics are studied. (Author).
Random networks of Boolean cellular automata
International Nuclear Information System (INIS)
Miranda, Enrique
1990-01-01
Some recent results about random networks of Boolean automata -the Kauffman model- are reviewed. The structure of configuration space is explored. Ultrametricity between cycles is analyzed and the effects of noise in the dynamics are studied. (Author)
Representing Boolean Functions by Decision Trees
Chikalov, Igor
2011-01-01
A Boolean or discrete function can be represented by a decision tree. A compact form of decision tree named binary decision diagram or branching program is widely known in logic design [2, 40]. This representation is equivalent to other forms
A short Boolean derivation of mean failure frequency for any (also non-coherent) system
International Nuclear Information System (INIS)
Schneeweiss, Winfrid G.
2009-01-01
For stationary repairable systems it is shown that the probabilistic weights for the individual components' mean failure frequencies (MFFs) that can be added to yield the system's MFF are found easily from the first step of the Boolean fault tree function's Shannon decomposition. This way one finds a general theory of a system's MFF and the case of coherence covered in standard textbooks is shown to be a subcase. Unfortunately, elegant rules for calculating system MFF from any polynomial form of the fault tree's Boolean function are only known for the coherent case, but repeated here, because they are not yet found in many textbooks. An example known from literature is treated extensively with great care.
Information encryption systems based on Boolean functions
Directory of Open Access Journals (Sweden)
Aureliu Zgureanu
2011-02-01
Full Text Available An information encryption system based on Boolean functions is proposed. Information processing is done using multidimensional matrices, performing logical operations with these matrices. At the basis of ensuring high level security of the system the complexity of solving the problem of building systems of Boolean functions that depend on many variables (tens and hundreds is set. Such systems represent the private key. It varies both during the encryption and decryption of information, and during the transition from one message to another.
Beyond-CMOS Device Benchmarking for Boolean and Non-Boolean Logic Applications
Pan, Chenyun; Naeemi, Azad
2017-01-01
The latest results of benchmarking research are presented for a variety of beyond-CMOS charge- and spin-based devices. In addition to improving the device-level models, several new device proposals and a few majorly modified devices are investigated. Deep pipelining circuits are employed to boost the throughput of low-power devices. Furthermore, the benchmarking methodology is extended to interconnect-centric analyses and non-Boolean logic applications. In contrast to Boolean circuits, non-Bo...
A complexity theory based on Boolean algebra
DEFF Research Database (Denmark)
Skyum, Sven; Valiant, Leslie
1985-01-01
A projection of a Boolean function is a function obtained by substituting for each of its variables a variable, the negation of a variable, or a constant. Reducibilities among computational problems under this relation of projection are considered. It is shown that much of what is of everyday rel...
Evolutionary Algorithms for Boolean Queries Optimization
Czech Academy of Sciences Publication Activity Database
Húsek, Dušan; Snášel, Václav; Neruda, Roman; Owais, S.S.J.; Krömer, P.
2006-01-01
Roč. 3, č. 1 (2006), s. 15-20 ISSN 1790-0832 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * information retrieval * Boolean query Subject RIV: BA - General Mathematics
Boolean Queries Optimization by Genetic Algorithms
Czech Academy of Sciences Publication Activity Database
Húsek, Dušan; Owais, S.S.J.; Krömer, P.; Snášel, Václav
2005-01-01
Roč. 15, - (2005), s. 395-409 ISSN 1210-0552 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * genetic programming * information retrieval * Boolean query Subject RIV: BB - Applied Statistics, Operational Research
Practical algorithms for linear boolean-width
ten Brinke, C.B.; van Houten, F.J.P.; Bodlaender, H.L.
2015-01-01
In this paper, we give a number of new exact algorithms and heuristics to compute linear boolean decompositions, and experimentally evaluate these algorithms. The experimental evaluation shows that significant improvements can be made with respect to running time without increasing the width of the
Practical algorithms for linear Boolean-width
ten Brinke, C.B.; van Houten, F.J.P.; Bodlaender, H.L.
2015-01-01
In this paper, we give a number of new exact algorithms and heuristics to compute linear boolean decompositions, and experimentally evaluate these algorithms. The experimental evaluation shows that significant improvements can be made with respect to running time without increasing the width of the
Probabilistic logics and probabilistic networks
Haenni, Rolf; Wheeler, Gregory; Williamson, Jon; Andrews, Jill
2014-01-01
Probabilistic Logic and Probabilistic Networks presents a groundbreaking framework within which various approaches to probabilistic logic naturally fit. Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.
Classical Boolean logic gates with quantum systems
International Nuclear Information System (INIS)
Renaud, N; Joachim, C
2011-01-01
An analytical method is proposed to implement any classical Boolean function in a small quantum system by taking the advantage of its electronic transport properties. The logical input, α = {α 1 , ..., α N }, is used to control well-identified parameters of the Hamiltonian of the system noted H 0 (α). The logical output is encoded in the tunneling current intensity passing through the quantum system when connected to conducting electrodes. It is demonstrated how to implement the six symmetric two-input/one-output Boolean functions in a quantum system. This system can be switched from one logic function to another by changing its structural parameters. The stability of the logic gates is discussed, perturbing the Hamiltonian with noise sources and studying the effect of decoherence.
Totally optimal decision trees for Boolean functions
Chikalov, Igor
2016-07-28
We study decision trees which are totally optimal relative to different sets of complexity parameters for Boolean functions. A totally optimal tree is an optimal tree relative to each parameter from the set simultaneously. We consider the parameters characterizing both time (in the worst- and average-case) and space complexity of decision trees, i.e., depth, total path length (average depth), and number of nodes. We have created tools based on extensions of dynamic programming to study totally optimal trees. These tools are applicable to both exact and approximate decision trees, and allow us to make multi-stage optimization of decision trees relative to different parameters and to count the number of optimal trees. Based on the experimental results we have formulated the following hypotheses (and subsequently proved): for almost all Boolean functions there exist totally optimal decision trees (i) relative to the depth and number of nodes, and (ii) relative to the depth and average depth.
Boolean representations of simplicial complexes and matroids
Rhodes, John
2015-01-01
This self-contained monograph explores a new theory centered around boolean representations of simplicial complexes leading to a new class of complexes featuring matroids as central to the theory. The book illustrates these new tools to study the classical theory of matroids as well as their important geometric connections. Moreover, many geometric and topological features of the theory of matroids find their counterparts in this extended context. Graduate students and researchers working in the areas of combinatorics, geometry, topology, algebra and lattice theory will find this monograph appealing due to the wide range of new problems raised by the theory. Combinatorialists will find this extension of the theory of matroids useful as it opens new lines of research within and beyond matroids. The geometric features and geometric/topological applications will appeal to geometers. Topologists who desire to perform algebraic topology computations will appreciate the algorithmic potential of boolean represent...
Optimal stabilization of Boolean networks through collective influence
Wang, Jiannan; Pei, Sen; Wei, Wei; Feng, Xiangnan; Zheng, Zhiming
2018-03-01
Boolean networks have attracted much attention due to their wide applications in describing dynamics of biological systems. During past decades, much effort has been invested in unveiling how network structure and update rules affect the stability of Boolean networks. In this paper, we aim to identify and control a minimal set of influential nodes that is capable of stabilizing an unstable Boolean network. For locally treelike Boolean networks with biased truth tables, we propose a greedy algorithm to identify influential nodes in Boolean networks by minimizing the largest eigenvalue of a modified nonbacktracking matrix. We test the performance of the proposed collective influence algorithm on four different networks. Results show that the collective influence algorithm can stabilize each network with a smaller set of nodes compared with other heuristic algorithms. Our work provides a new insight into the mechanism that determines the stability of Boolean networks, which may find applications in identifying virulence genes that lead to serious diseases.
Large Sets in Boolean and Non-Boolean Groups and Topology
Directory of Open Access Journals (Sweden)
Ol’ga V. Sipacheva
2017-10-01
Full Text Available Various notions of large sets in groups, including the classical notions of thick, syndetic, and piecewise syndetic sets and the new notion of vast sets in groups, are studied with emphasis on the interplay between such sets in Boolean groups. Natural topologies closely related to vast sets are considered; as a byproduct, interesting relations between vast sets and ultrafilters are revealed.
Vector Boolean Functions: applications in symmetric cryptography
Álvarez Cubero, José Antonio
2015-01-01
Esta tesis establece los fundamentos teóricos y diseña una colección abierta de clases C++ denominada VBF (Vector Boolean Functions) para analizar funciones booleanas vectoriales (funciones que asocian un vector booleano a otro vector booleano) desde una perspectiva criptográfica. Esta nueva implementación emplea la librería NTL de Victor Shoup, incorporando nuevos módulos que complementan a las funciones de NTL, adecuándolas para el análisis criptográfico. La clase fundamental que representa...
Boolean Factor Analysis by Attractor Neural Network
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.
2007-01-01
Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007
The Boolean algebra and central Galois algebras
Directory of Open Access Journals (Sweden)
George Szeto
2001-01-01
Full Text Available Let B be a Galois algebra with Galois group G, Jg={b∈B∣bx=g(xb for all x∈B} for g∈G, and BJg=Beg for a central idempotent eg. Then a relation is given between the set of elements in the Boolean algebra (Ba,≤ generated by {0,eg∣g∈G} and a set of subgroups of G, and a central Galois algebra Be with a Galois subgroup of G is characterized for an e∈Ba.
Efficient Instantiation of Parameterised Boolean Equation Systems to Parity Games
Kant, Gijs; van de Pol, Jan Cornelis; Wijs, A.J.; Bošnački, D.; Edelkamp, S.
Parameterised Boolean Equation Systems (PBESs) are sequences of Boolean fixed point equations with data variables, used for, e.g., verification of modal μ-calculus formulae for process algebraic specifications with data. Solving a PBES is usually done by instantiation to a Parity Game and then
Boolean orthoposets and two-valued states on them
Tkadlec, Josef
1992-06-01
A Boolean orthoposet (see e.g. [2]) is the orthoposet P fulfilling the following condition: If a, b ∈ P and a ∧ b = 0 then a⊥ b. This condition seems to be a sound generalization of distributivity in orthoposets (see e.g. [8]). Also, the class of (orthomodular) Boolean orthoposets may play an interesting role in quantum logic theory. This class is wide enough (see [4,3]) and on the other hand, enjoys some properties of Boolean algebras [4,8,5]. In quantum logic theory an important role is played by so-called Jauch-Piron states [1,6,7]. In this paper we clarify the connection between Boolean orthoposets and orthoposets with "enough" two-valued Jauch-Piron states. Further, we obtain a characterization of Boolean orthoposets in terms of two-valued states.
An adaptable Boolean net trainable to control a computing robot
International Nuclear Information System (INIS)
Lauria, F. E.; Prevete, R.; Milo, M.; Visco, S.
1999-01-01
We discuss a method to implement in a Boolean neural network a Hebbian rule so to obtain an adaptable universal control system. We start by presenting both the Boolean neural net and the Hebbian rule we have considered. Then we discuss, first, the problems arising when the latter is naively implemented in a Boolean neural net, second, the method consenting us to overcome them and the ensuing adaptable Boolean neural net paradigm. Next, we present the adaptable Boolean neural net as an intelligent control system, actually controlling a writing robot, and discuss how to train it in the execution of the elementary arithmetic operations on operands represented by numerals with an arbitrary number of digits
Wakker, P.P.; Thaler, R.H.; Tversky, A.
1997-01-01
textabstractProbabilistic insurance is an insurance policy involving a small probability that the consumer will not be reimbursed. Survey data suggest that people dislike probabilistic insurance and demand more than a 20% reduction in the premium to compensate for a 1% default risk. While these preferences are intuitively appealing they are difficult to reconcile with expected utility theory. Under highly plausible assumptions about the utility function, willingness to pay for probabilistic i...
Evolutionary Algorithms for Boolean Functions in Diverse Domains of Cryptography.
Picek, Stjepan; Carlet, Claude; Guilley, Sylvain; Miller, Julian F; Jakobovic, Domagoj
2016-01-01
The role of Boolean functions is prominent in several areas including cryptography, sequences, and coding theory. Therefore, various methods for the construction of Boolean functions with desired properties are of direct interest. New motivations on the role of Boolean functions in cryptography with attendant new properties have emerged over the years. There are still many combinations of design criteria left unexplored and in this matter evolutionary computation can play a distinct role. This article concentrates on two scenarios for the use of Boolean functions in cryptography. The first uses Boolean functions as the source of the nonlinearity in filter and combiner generators. Although relatively well explored using evolutionary algorithms, it still presents an interesting goal in terms of the practical sizes of Boolean functions. The second scenario appeared rather recently where the objective is to find Boolean functions that have various orders of the correlation immunity and minimal Hamming weight. In both these scenarios we see that evolutionary algorithms are able to find high-quality solutions where genetic programming performs the best.
Representing Boolean Functions by Decision Trees
Chikalov, Igor
2011-01-01
A Boolean or discrete function can be represented by a decision tree. A compact form of decision tree named binary decision diagram or branching program is widely known in logic design [2, 40]. This representation is equivalent to other forms, and in some cases it is more compact than values table or even the formula [44]. Representing a function in the form of decision tree allows applying graph algorithms for various transformations [10]. Decision trees and branching programs are used for effective hardware [15] and software [5] implementation of functions. For the implementation to be effective, the function representation should have minimal time and space complexity. The average depth of decision tree characterizes the expected computing time, and the number of nodes in branching program characterizes the number of functional elements required for implementation. Often these two criteria are incompatible, i.e. there is no solution that is optimal on both time and space complexity. © Springer-Verlag Berlin Heidelberg 2011.
Message passing for quantified Boolean formulas
International Nuclear Information System (INIS)
Zhang, Pan; Ramezanpour, Abolfazl; Zecchina, Riccardo; Zdeborová, Lenka
2012-01-01
We introduce two types of message passing algorithms for quantified Boolean formulas (QBF). The first type is a message passing based heuristics that can prove unsatisfiability of the QBF by assigning the universal variables in such a way that the remaining formula is unsatisfiable. In the second type, we use message passing to guide branching heuristics of a Davis–Putnam–Logemann–Loveland (DPLL) complete solver. Numerical experiments show that on random QBFs our branching heuristics give robust exponential efficiency gain with respect to state-of-the-art solvers. We also manage to solve some previously unsolved benchmarks from the QBFLIB library. Apart from this, our study sheds light on using message passing in small systems and as subroutines in complete solvers
Synthesizing biomolecule-based Boolean logic gates.
Miyamoto, Takafumi; Razavi, Shiva; DeRose, Robert; Inoue, Takanari
2013-02-15
One fascinating recent avenue of study in the field of synthetic biology is the creation of biomolecule-based computers. The main components of a computing device consist of an arithmetic logic unit, the control unit, memory, and the input and output devices. Boolean logic gates are at the core of the operational machinery of these parts, and hence to make biocomputers a reality, biomolecular logic gates become a necessity. Indeed, with the advent of more sophisticated biological tools, both nucleic acid- and protein-based logic systems have been generated. These devices function in the context of either test tubes or living cells and yield highly specific outputs given a set of inputs. In this review, we discuss various types of biomolecular logic gates that have been synthesized, with particular emphasis on recent developments that promise increased complexity of logic gate circuitry, improved computational speed, and potential clinical applications.
Multipath Detection Using Boolean Satisfiability Techniques
Directory of Open Access Journals (Sweden)
Fadi A. Aloul
2011-01-01
Full Text Available A new technique for multipath detection in wideband mobile radio systems is presented. The proposed scheme is based on an intelligent search algorithm using Boolean Satisfiability (SAT techniques to search through the uncertainty region of the multipath delays. The SAT-based scheme utilizes the known structure of the transmitted wideband signal, for example, pseudo-random (PN code, to effectively search through the entire space by eliminating subspaces that do not contain a possible solution. The paper presents a framework for modeling the multipath detection problem as a SAT application. It also provides simulation results that demonstrate the effectiveness of the proposed scheme in detecting the multipath components in frequency-selective Rayleigh fading channels.
Synthesizing Biomolecule-based Boolean Logic Gates
Miyamoto, Takafumi; Razavi, Shiva; DeRose, Robert; Inoue, Takanari
2012-01-01
One fascinating recent avenue of study in the field of synthetic biology is the creation of biomolecule-based computers. The main components of a computing device consist of an arithmetic logic unit, the control unit, memory, and the input and output devices. Boolean logic gates are at the core of the operational machinery of these parts, hence to make biocomputers a reality, biomolecular logic gates become a necessity. Indeed, with the advent of more sophisticated biological tools, both nucleic acid- and protein-based logic systems have been generated. These devices function in the context of either test tubes or living cells and yield highly specific outputs given a set of inputs. In this review, we discuss various types of biomolecular logic gates that have been synthesized, with particular emphasis on recent developments that promise increased complexity of logic gate circuitry, improved computational speed, and potential clinical applications. PMID:23526588
The Boolean algebra of Galois algebras
Directory of Open Access Journals (Sweden)
Lianyong Xue
2003-02-01
Full Text Available Let B be a Galois algebra with Galois group G, Jg={bÃ¢ÂˆÂˆB|bx=g(xbÃ¢Â€Â‰for allÃ¢Â€Â‰xÃ¢ÂˆÂˆB} for each gÃ¢ÂˆÂˆG, and BJg=Beg for a central idempotent eg, Ba the Boolean algebra generated by {0,eg|gÃ¢ÂˆÂˆG}, e a nonzero element in Ba, and He={gÃ¢ÂˆÂˆG|eeg=e}. Then, a monomial e is characterized, and the Galois extension Be, generated by e with Galois group He, is investigated.
Optical reversible programmable Boolean logic unit.
Chattopadhyay, Tanay
2012-07-20
Computing with reversibility is the only way to avoid dissipation of energy associated with bit erase. So, a reversible microprocessor is required for future computing. In this paper, a design of a simple all-optical reversible programmable processor is proposed using a polarizing beam splitter, liquid crystal-phase spatial light modulators, a half-wave plate, and plane mirrors. This circuit can perform 16 logical operations according to three programming inputs. Also, inputs can be easily recovered from the outputs. It is named the "reversible programmable Boolean logic unit (RPBLU)." The logic unit is the basic building block of many complex computational operations. Hence the design is important in sense. Two orthogonally polarized lights are defined here as two logical states, respectively.
Boolean Operations with Prism Algebraic Patches
Bajaj, Chandrajit; Paoluzzi, Alberto; Portuesi, Simone; Lei, Na; Zhao, Wenqi
2009-01-01
In this paper we discuss a symbolic-numeric algorithm for Boolean operations, closed in the algebra of curved polyhedra whose boundary is triangulated with algebraic patches (A-patches). This approach uses a linear polyhedron as a first approximation of both the arguments and the result. On each triangle of a boundary representation of such linear approximation, a piecewise cubic algebraic interpolant is built, using a C1-continuous prism algebraic patch (prism A-patch) that interpolates the three triangle vertices, with given normal vectors. The boundary representation only stores the vertices of the initial triangulation and their external vertex normals. In order to represent also flat and/or sharp local features, the corresponding normal-per-face and/or normal-per-edge may be also given, respectively. The topology is described by storing, for each curved triangle, the two triples of pointers to incident vertices and to adjacent triangles. For each triangle, a scaffolding prism is built, produced by its extreme vertices and normals, which provides a containment volume for the curved interpolating A-patch. When looking for the result of a regularized Boolean operation, the 0-set of a tri-variate polynomial within each such prism is generated, and intersected with the analogous 0-sets of the other curved polyhedron, when two prisms have non-empty intersection. The intersection curves of the boundaries are traced and used to decompose each boundary into the 3 standard classes of subpatches, denoted in, out and on. While tracing the intersection curves, the locally refined triangulation of intersecting patches is produced, and added to the boundary representation. PMID:21516262
DEFF Research Database (Denmark)
Jensen, Finn Verner; Lauritzen, Steffen Lilholt
2001-01-01
This article describes the basic ideas and algorithms behind specification and inference in probabilistic networks based on directed acyclic graphs, undirected graphs, and chain graphs.......This article describes the basic ideas and algorithms behind specification and inference in probabilistic networks based on directed acyclic graphs, undirected graphs, and chain graphs....
Wakker, P.P.; Thaler, R.H.; Tversky, A.
1997-01-01
Probabilistic insurance is an insurance policy involving a small probability that the consumer will not be reimbursed. Survey data suggest that people dislike probabilistic insurance and demand more than a 20% reduction in premium to compensate for a 1% default risk. These observations cannot be
P.P. Wakker (Peter); R.H. Thaler (Richard); A. Tversky (Amos)
1997-01-01
textabstractProbabilistic insurance is an insurance policy involving a small probability that the consumer will not be reimbursed. Survey data suggest that people dislike probabilistic insurance and demand more than a 20% reduction in the premium to compensate for a 1% default risk. While these
A transition calculus for Boolean functions. [logic circuit analysis
Tucker, J. H.; Bennett, A. W.
1974-01-01
A transition calculus is presented for analyzing the effect of input changes on the output of logic circuits. The method is closely related to the Boolean difference, but it is more powerful. Both differentiation and integration are considered.
Algebraic model checking for Boolean gene regulatory networks.
Tran, Quoc-Nam
2011-01-01
We present a computational method in which modular and Groebner bases (GB) computation in Boolean rings are used for solving problems in Boolean gene regulatory networks (BN). In contrast to other known algebraic approaches, the degree of intermediate polynomials during the calculation of Groebner bases using our method will never grow resulting in a significant improvement in running time and memory space consumption. We also show how calculation in temporal logic for model checking can be done by means of our direct and efficient Groebner basis computation in Boolean rings. We present our experimental results in finding attractors and control strategies of Boolean networks to illustrate our theoretical arguments. The results are promising. Our algebraic approach is more efficient than the state-of-the-art model checker NuSMV on BNs. More importantly, our approach finds all solutions for the BN problems.
Nonlinear threshold Boolean automata networks and phase transitions
Demongeot, Jacques; Sené, Sylvain
2010-01-01
In this report, we present a formal approach that addresses the problem of emergence of phase transitions in stochastic and attractive nonlinear threshold Boolean automata networks. Nonlinear networks considered are informally defined on the basis of classical stochastic threshold Boolean automata networks in which specific interaction potentials of neighbourhood coalition are taken into account. More precisely, specific nonlinear terms compose local transition functions that define locally t...
Synchronization in an array of coupled Boolean networks
International Nuclear Information System (INIS)
Li, Rui; Chu, Tianguang
2012-01-01
This Letter presents an analytical study of synchronization in an array of coupled deterministic Boolean networks. A necessary and sufficient criterion for synchronization is established based on algebraic representations of logical dynamics in terms of the semi-tensor product of matrices. Some basic properties of a synchronized array of Boolean networks are then derived for the existence of transient states and the upper bound of the number of fixed points. Particularly, an interesting consequence indicates that a “large” mismatch between two coupled Boolean networks in the array may result in loss of synchrony in the entire system. Examples, including the Boolean model of coupled oscillations in the cell cycle, are given to illustrate the present results. -- Highlights: ► We analytically study synchronization in an array of coupled Boolean networks. ► The study is based on the algebraic representations of logical dynamics. ► A necessary and sufficient algebraic criterion for synchronization is established. ► It reveals some basic properties of a synchronized array of Boolean networks. ► A large mismatch between two coupled networks may result in the loss of synchrony.
Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks
Directory of Open Access Journals (Sweden)
Liang Jinghang
2012-08-01
Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a
Patterns of probabilistic evaluation of the maintenance
International Nuclear Information System (INIS)
Torres V, A.; Rivero O, J.J.
2004-01-01
The Boolean equation represented by the minimum sets of court at level of a system or of all one Probabilistic safety analysis (APS) it has been used for to evaluate the output configurations of service of teams during the exploitation. It has been carried out through applications of APS for the optimization of operational regimes. The obtaining of such boolean equations as demands of a process of high mathematical complexity for what exhaustive studies are required, even for the application of their results. The important advantages for the maintenance that they obtain of these applications they require the development of methodologies that bring near these optimization methods to the systems of management of the maintenance, and not facilitate their use for a personnel specialized in the probabilistic topics. The article presents a methodology for the preparation, solution and utilization of the results of the fault tree leaving of technological outlines. This algorithm has been automated through the MOSEG code Win to Ver 1.0 (Author)
Equivalence Checking of Combinational Circuits using Boolean Expression Diagrams
DEFF Research Database (Denmark)
Hulgaard, Henrik; Williams, Poul Frederick; Andersen, Henrik Reif
1999-01-01
The combinational logic-level equivalence problem is to determine whether two given combinational circuits implement the same Boolean function. This problem arises in a number of CAD applications, for example when checking the correctness of incremental design changes (performed either manually...... or by a design automation tool).This paper introduces a data structure called Boolean Expression Diagrams (BEDs) and two algorithms for transforming a BED into a Reduced Ordered Binary Decision Diagram (OBDD). BEDs are capable of representing any Boolean circuit in linear space and can exploit structural...... similarities between the two circuits that are compared. These properties make BEDs suitable for verifying the equivalence of combinational circuits. BEDs can be seen as an intermediate representation between circuits (which are compact) and OBDDs (which are canonical).Based on a large number of combinational...
Exploiting Surroundedness for Saliency Detection: A Boolean Map Approach.
Zhang, Jianming; Sclaroff, Stan
2016-05-01
We demonstrate the usefulness of surroundedness for eye fixation prediction by proposing a Boolean Map based Saliency model (BMS). In our formulation, an image is characterized by a set of binary images, which are generated by randomly thresholding the image's feature maps in a whitened feature space. Based on a Gestalt principle of figure-ground segregation, BMS computes a saliency map by discovering surrounded regions via topological analysis of Boolean maps. Furthermore, we draw a connection between BMS and the Minimum Barrier Distance to provide insight into why and how BMS can properly captures the surroundedness cue via Boolean maps. The strength of BMS is verified by its simplicity, efficiency and superior performance compared with 10 state-of-the-art methods on seven eye tracking benchmark datasets.
Bod, R.; Heine, B.; Narrog, H.
2010-01-01
Probabilistic linguistics takes all linguistic evidence as positive evidence and lets statistics decide. It allows for accurate modelling of gradient phenomena in production and perception, and suggests that rule-like behaviour is no more than a side effect of maximizing probability. This chapter
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Burcharth, H. F.
This chapter describes how partial safety factors can be used in design of vertical wall breakwaters and an example of a code format is presented. The partial safety factors are calibrated on a probabilistic basis. The code calibration process used to calibrate some of the partial safety factors...
A Boolean Approach to Airline Business Model Innovation
DEFF Research Database (Denmark)
Hvass, Kristian Anders
Research in business model innovation has identified its significance in creating a sustainable competitive advantage for a firm, yet there are few empirical studies identifying which combination of business model activities lead to success and therefore deserve innovative attention. This study...... analyzes the business models of North America low-cost carriers from 2001 to 2010 using a Boolean minimization algorithm to identify which combinations of business model activities lead to operational profitability. The research aim is threefold: complement airline literature in the realm of business model...... innovation, introduce Boolean minimization methods to the field, and propose alternative business model activities to North American carriers striving for positive operating results....
Refinement monoids, equidecomposability types, and boolean inverse semigroups
Wehrung, Friedrich
2017-01-01
Adopting a new universal algebraic approach, this book explores and consolidates the link between Tarski's classical theory of equidecomposability types monoids, abstract measure theory (in the spirit of Hans Dobbertin's work on monoid-valued measures on Boolean algebras) and the nonstable K-theory of rings. This is done via the study of a monoid invariant, defined on Boolean inverse semigroups, called the type monoid. The new techniques contrast with the currently available topological approaches. Many positive results, but also many counterexamples, are provided.
On Kolmogorov's superpositions and Boolean functions
Energy Technology Data Exchange (ETDEWEB)
Beiu, V.
1998-12-31
The paper overviews results dealing with the approximation capabilities of neural networks, as well as bounds on the size of threshold gate circuits. Based on an explicit numerical (i.e., constructive) algorithm for Kolmogorov's superpositions they will show that for obtaining minimum size neutral networks for implementing any Boolean function, the activation function of the neurons is the identity function. Because classical AND-OR implementations, as well as threshold gate implementations require exponential size (in the worst case), it will follow that size-optimal solutions for implementing arbitrary Boolean functions require analog circuitry. Conclusions and several comments on the required precision are ending the paper.
Probabilistic Logic and Probabilistic Networks
Haenni, R.; Romeijn, J.-W.; Wheeler, G.; Williamson, J.
2009-01-01
While in principle probabilistic logics might be applied to solve a range of problems, in practice they are rarely applied at present. This is perhaps because they seem disparate, complicated, and computationally intractable. However, we shall argue in this programmatic paper that several approaches
Confluence of an extension of combinatory logic by Boolean constants
DEFF Research Database (Denmark)
Czajka, Łukasz
2017-01-01
We show confluence of a conditional term rewriting system CL-pc1, which is an extension of Combinatory Logic by Boolean constants. This solves problem 15 from the RTA list of open problems. The proof has been fully formalized in the Coq proof assistant....
On the Road to Genetic Boolean Matrix Factorization
Czech Academy of Sciences Publication Activity Database
Snášel, V.; Platoš, J.; Krömer, P.; Húsek, Dušan; Frolov, A.
2007-01-01
Roč. 17, č. 6 (2007), s. 675-688 ISSN 1210-0552 Institutional research plan: CEZ:AV0Z10300504 Keywords : data mining * genetic algorithms * Boolean factorization * binary data * machine learning * feature extraction Subject RIV: IN - Informatics, Computer Science Impact factor: 0.280, year: 2007
Document Ranking in E-Extended Boolean Logic
Czech Academy of Sciences Publication Activity Database
Holub, M.; Húsek, Dušan; Pokorný, J.
1996-01-01
Roč. 4, č. 7 (1996), s. 3-17 ISSN 1310-0513. [Annual Colloquium on IR Research /19./. Aberdeen, 08.04.1997-09.04.1997] R&D Projects: GA ČR GA102/94/0728 Keywords : information retrieval * document ranking * extended Boolean logic
Free Boolean algebras over unions of two well orderings
Czech Academy of Sciences Publication Activity Database
Bonnet, R.; Faouzi, L.; Kubiś, Wieslaw
2009-01-01
Roč. 156, č. 7 (2009), s. 1177-1185 ISSN 0166-8641 Institutional research plan: CEZ:AV0Z10190503 Keywords : Well quasi orderings * Poset algebras * Superatomic Boolean algebras * Compact distributive lattices Subject RIV: BA - General Mathematics Impact factor: 0.441, year: 2009
Boolean comparative analysis of qualitative data : a methodological note
Romme, A.G.L.
1995-01-01
This paper explores the use of Boolean logic in the analysis of qualitative data, especially on the basis of so-called process theories. Process theories treat independent variables as necessary conditions which are binary rather than variable in nature, while the dependent variable is a final
Parallel object-oriented term rewriting : the booleans
Rodenburg, P.H.; Vrancken, J.L.M.
As a first case study in parallel object-oriented term rewriting, we give two implementations of term rewriting algorithms for boolean terms, using the parallel object-oriented features of the language Pool-T. The term rewriting systems are specified in the specification formalism
A Construction of Boolean Functions with Good Cryptographic Properties
2014-01-01
be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT...2008, LNCS 5350, Springer–Verlag, 2008, pp. 425–440. [10] C. Carlet and K. Feng, “An Infinite Class of Balanced Vectorial Boolean Functions with Optimum
Boolean network representation of contagion dynamics during a financial crisis
Caetano, Marco Antonio Leonel; Yoneyama, Takashi
2015-01-01
This work presents a network model for representation of the evolution of certain patterns of economic behavior. More specifically, after representing the agents as points in a space in which each dimension associated to a relevant economic variable, their relative "motions" that can be either stationary or discordant, are coded into a boolean network. Patterns with stationary averages indicate the maintenance of status quo, whereas discordant patterns represent aggregation of new agent into the cluster or departure from the former policies. The changing patterns can be embedded into a network representation, particularly using the concept of autocatalytic boolean networks. As a case study, the economic tendencies of the BRIC countries + Argentina were studied. Although Argentina is not included in the cluster formed by BRIC countries, it tends to follow the BRIC members because of strong commercial ties.
Boolean Functions with a Simple Certificate for CNF Complexity
Czech Academy of Sciences Publication Activity Database
Čepek, O.; Kučera, P.; Savický, Petr
2012-01-01
Roč. 160, 4-5 (2012), s. 365-382 ISSN 0166-218X R&D Projects: GA MŠk(CZ) 1M0545 Grant - others:GA ČR(CZ) GP201/07/P168; GA ČR(CZ) GAP202/10/1188 Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean functions * CNF representations Subject RIV: BA - General Mathematics Impact factor: 0.718, year: 2012
Elements of Boolean-Valued Dempster-Shafer Theory
Czech Academy of Sciences Publication Activity Database
Kramosil, Ivan
2000-01-01
Roč. 10, č. 5 (2000), s. 825-835 ISSN 1210-0552. [SOFSEM 2000 Workshop on Soft Computing. Milovy, 27.11.2000-28.11.2000] R&D Projects: GA ČR GA201/00/1489 Institutional research plan: AV0Z1030915 Keywords : Boolean algebra * belief function * Dempster-Shafer theory * Dempster combination rule * nonspecifity degree Subject RIV: BA - General Mathematics
Constrained mathematics evaluation in probabilistic logic analysis
Energy Technology Data Exchange (ETDEWEB)
Arlin Cooper, J
1998-06-01
A challenging problem in mathematically processing uncertain operands is that constraints inherent in the problem definition can require computations that are difficult to implement. Examples of possible constraints are that the sum of the probabilities of partitioned possible outcomes must be one, and repeated appearances of the same variable must all have the identical value. The latter, called the 'repeated variable problem', will be addressed in this paper in order to show how interval-based probabilistic evaluation of Boolean logic expressions, such as those describing the outcomes of fault trees and event trees, can be facilitated in a way that can be readily implemented in software. We will illustrate techniques that can be used to transform complex constrained problems into trivial problems in most tree logic expressions, and into tractable problems in most other cases.
Boolean Models of Biological Processes Explain Cascade-Like Behavior.
Chen, Hao; Wang, Guanyu; Simha, Rahul; Du, Chenghang; Zeng, Chen
2016-01-29
Biological networks play a key role in determining biological function and therefore, an understanding of their structure and dynamics is of central interest in systems biology. In Boolean models of such networks, the status of each molecule is either "on" or "off" and along with the molecules interact with each other, their individual status changes from "on" to "off" or vice-versa and the system of molecules in the network collectively go through a sequence of changes in state. This sequence of changes is termed a biological process. In this paper, we examine the common perception that events in biomolecular networks occur sequentially, in a cascade-like manner, and ask whether this is likely to be an inherent property. In further investigations of the budding and fission yeast cell-cycle, we identify two generic dynamical rules. A Boolean system that complies with these rules will automatically have a certain robustness. By considering the biological requirements in robustness and designability, we show that those Boolean dynamical systems, compared to an arbitrary dynamical system, statistically present the characteristics of cascadeness and sequentiality, as observed in the budding and fission yeast cell- cycle. These results suggest that cascade-like behavior might be an intrinsic property of biological processes.
Controllability and observability of Boolean networks arising from biology
Li, Rui; Yang, Meng; Chu, Tianguang
2015-02-01
Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.
3D Boolean operations in virtual surgical planning.
Charton, Jerome; Laurentjoye, Mathieu; Kim, Youngjun
2017-10-01
Boolean operations in computer-aided design or computer graphics are a set of operations (e.g. intersection, union, subtraction) between two objects (e.g. a patient model and an implant model) that are important in performing accurate and reproducible virtual surgical planning. This requires accurate and robust techniques that can handle various types of data, such as a surface extracted from volumetric data, synthetic models, and 3D scan data. This article compares the performance of the proposed method (Boolean operations by a robust, exact, and simple method between two colliding shells (BORES)) and an existing method based on the Visualization Toolkit (VTK). In all tests presented in this article, BORES could handle complex configurations as well as report impossible configurations of the input. In contrast, the VTK implementations were unstable, do not deal with singular edges and coplanar collisions, and have created several defects. The proposed method of Boolean operations, BORES, is efficient and appropriate for virtual surgical planning. Moreover, it is simple and easy to implement. In future work, we will extend the proposed method to handle non-colliding components.
Directory of Open Access Journals (Sweden)
Mikaël Cozic
2016-11-01
Full Text Available The modeling of awareness and unawareness is a significant topic in the doxastic logic literature, where it is usually tackled in terms of full belief operators. The present paper aims at a treatment in terms of partial belief operators. It draws upon the modal probabilistic logic that was introduced by Aumann (1999 at the semantic level, and then axiomatized by Heifetz and Mongin (2001. The paper embodies in this framework those properties of unawareness that have been highlighted in the seminal paper by Modica and Rustichini (1999. Their paper deals with full belief, but we argue that the properties in question also apply to partial belief. Our main result is a (soundness and completeness theorem that reunites the two strands—modal and probabilistic—of doxastic logic.
International Nuclear Information System (INIS)
Lofgren, E.V.
1985-08-01
This course in System Reliability and Analysis Techniques focuses on the probabilistic quantification of accident sequences and the link between accident sequences and consequences. Other sessions in this series focus on the quantification of system reliability and the development of event trees and fault trees. This course takes the viewpoint that event tree sequences or combinations of system failures and success are available and that Boolean equations for system fault trees have been developed and are available. 93 figs., 11 tabs
On the Computation of Comprehensive Boolean Gröbner Bases
Inoue, Shutaro
We show that a comprehensive Boolean Gröbner basis of an ideal I in a Boolean polynomial ring B (bar A,bar X) with main variables bar X and parameters bar A can be obtained by simply computing a usual Boolean Gröbner basis of I regarding both bar X and bar A as variables with a certain block term order such that bar X ≫ bar A. The result together with a fact that a finite Boolean ring is isomorphic to a direct product of the Galois field mathbb{GF}_2 enables us to compute a comprehensive Boolean Gröbner basis by only computing corresponding Gröbner bases in a polynomial ring over mathbb{GF}_2. Our implementation in a computer algebra system Risa/Asir shows that our method is extremely efficient comparing with existing computation algorithms of comprehensive Boolean Gröbner bases.
The mathematics of a quantum Hamiltonian computing half adder Boolean logic gate
International Nuclear Information System (INIS)
Dridi, G; Julien, R; Hliwa, M; Joachim, C
2015-01-01
The mathematics behind the quantum Hamiltonian computing (QHC) approach of designing Boolean logic gates with a quantum system are given. Using the quantum eigenvalue repulsion effect, the QHC AND, NAND, OR, NOR, XOR, and NXOR Hamiltonian Boolean matrices are constructed. This is applied to the construction of a QHC half adder Hamiltonian matrix requiring only six quantum states to fullfil a half Boolean logical truth table. The QHC design rules open a nano-architectronic way of constructing Boolean logic gates inside a single molecule or atom by atom at the surface of a passivated semi-conductor. (paper)
The mathematics of a quantum Hamiltonian computing half adder Boolean logic gate.
Dridi, G; Julien, R; Hliwa, M; Joachim, C
2015-08-28
The mathematics behind the quantum Hamiltonian computing (QHC) approach of designing Boolean logic gates with a quantum system are given. Using the quantum eigenvalue repulsion effect, the QHC AND, NAND, OR, NOR, XOR, and NXOR Hamiltonian Boolean matrices are constructed. This is applied to the construction of a QHC half adder Hamiltonian matrix requiring only six quantum states to fullfil a half Boolean logical truth table. The QHC design rules open a nano-architectronic way of constructing Boolean logic gates inside a single molecule or atom by atom at the surface of a passivated semi-conductor.
The value of less connected agents in Boolean networks
Epstein, Daniel; Bazzan, Ana L. C.
2013-11-01
In multiagent systems, agents often face binary decisions where one seeks to take either the minority or the majority side. Examples are minority and congestion games in general, i.e., situations that require coordination among the agents in order to depict efficient decisions. In minority games such as the El Farol Bar Problem, previous works have shown that agents may reach appropriate levels of coordination, mostly by looking at the history of past decisions. Not many works consider any kind of structure of the social network, i.e., how agents are connected. Moreover, when structure is indeed considered, it assumes some kind of random network with a given, fixed connectivity degree. The present paper departs from the conventional approach in some ways. First, it considers more realistic network topologies, based on preferential attachments. This is especially useful in social networks. Second, the formalism of random Boolean networks is used to help agents to make decisions given their attachments (for example acquaintances). This is coupled with a reinforcement learning mechanism that allows agents to select strategies that are locally and globally efficient. Third, we use agent-based modeling and simulation, a microscopic approach, which allows us to draw conclusions about individuals and/or classes of individuals. Finally, for the sake of illustration we use two different scenarios, namely the El Farol Bar Problem and a binary route choice scenario. With this approach we target systems that adapt dynamically to changes in the environment, including other adaptive decision-makers. Our results using preferential attachments and random Boolean networks are threefold. First we show that an efficient equilibrium can be achieved, provided agents do experimentation. Second, microscopic analysis show that influential agents tend to consider few inputs in their Boolean functions. Third, we have also conducted measurements related to network clustering and centrality
Bebop to the Boolean boogie an unconventional guide to electronics
Maxfield, Clive
2003-01-01
From reviews of the first edition:""If you want to be reminded of the joy of electronics, take a look at Clive (Max) Maxfield's book Bebop to the Boolean Boogie.""--Computer Design ""Lives up to its title as a useful and entertaining technical guide....well-suited for students, technical writers, technicians, and sales and marketing people.""--Electronic Design""Writing a book like this one takes audacity! ... Maxfield writes lucidly on a variety of complex topics without 'writing down' to his audience."" --EDN""A highly readable, well-illustrated guided tour
Two Expectation-Maximization Algorithms for Boolean Factor Analysis
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.
2014-01-01
Roč. 130, 23 April (2014), s. 83-97 ISSN 0925-2312 R&D Projects: GA ČR GAP202/10/0262 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070; GA MŠk(CZ) EE.2.3.20.0073 Program:ED Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean Factor analysis * Binary Matrix factorization * Neural networks * Binary data model * Dimension reduction * Bars problem Subject RIV: IN - Informatics, Computer Science Impact factor: 2.083, year: 2014
A boolean optimization method for reloading a nuclear reactor
International Nuclear Information System (INIS)
Misse Nseke, Theophile.
1982-04-01
We attempt to solve the problem of optimal reloading of fuel assemblies in a PWR, without any assumption on the fuel nature. Any loading is marked by n 2 boolean variables usub(ij). The state of the reactor is characterized by his Ksub(eff) and the related power distribution. The resulting non-linear allocation problems are solved throught mathematical programming technics combining the simplex algorithm and an extension of the Balas-Geoffrion's one. Some optimal solutions are given for PWR with assemblies of different enrichment [fr
Complexity classifications for different equivalence and audit problems for Boolean circuits
BÃ¶hler, Elmar; Creignou, Nadia; Galota, Matthias; Reith, Steffen; Schnoor, Henning; Vollmer, Heribert
2010-01-01
We study Boolean circuits as a representation of Boolean functions and conskier different equivalence, audit, and enumeration problems. For a number of restricted sets of gate types (bases) we obtain efficient algorithms, while for all other gate types we show these problems are at least NP-hard.
BEAT: A Web-Based Boolean Expression Fault-Based Test Case Generation Tool
Chen, T. Y.; Grant, D. D.; Lau, M. F.; Ng, S. P.; Vasa, V. R.
2006-01-01
BEAT is a Web-based system that generates fault-based test cases from Boolean expressions. It is based on the integration of our several fault-based test case selection strategies. The generated test cases are considered to be fault-based, because they are aiming at the detection of particular faults. For example, when the Boolean expression is in…
Boolean models of biosurfactants production in Pseudomonas fluorescens.
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Adrien Richard
Full Text Available Cyclolipopeptides (CLPs are biosurfactants produced by numerous Pseudomonas fluorescens strains. CLP production is known to be regulated at least by the GacA/GacS two-component pathway, but the full regulatory network is yet largely unknown. In the clinical strain MFN1032, CLP production is abolished by a mutation in the phospholipase C gene (plcC and not restored by plcC complementation. Their production is also subject to phenotypic variation. We used a modelling approach with Boolean networks, which takes into account all these observations concerning CLP production without any assumption on the topology of the considered network. Intensive computation yielded numerous models that satisfy these properties. All models minimizing the number of components point to a bistability in CLP production, which requires the presence of a yet unknown key self-inducible regulator. Furthermore, all suggest that a set of yet unexplained phenotypic variants might also be due to this epigenetic switch. The simplest of these Boolean networks was used to propose a biological regulatory network for CLP production. This modelling approach has allowed a possible regulation to be unravelled and an unusual behaviour of CLP production in P. fluorescens to be explained.
Efficient Instantiation of Parameterised Boolean Equation Systems to Parity Games
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Gijs Kant
2012-10-01
Full Text Available Parameterised Boolean Equation Systems (PBESs are sequences of Boolean fixed point equations with data variables, used for, e.g., verification of modal mu-calculus formulae for process algebraic specifications with data. Solving a PBES is usually done by instantiation to a Parity Game and then solving the game. Practical game solvers exist, but the instantiation step is the bottleneck. We enhance the instantiation in two steps. First, we transform the PBES to a Parameterised Parity Game (PPG, a PBES with each equation either conjunctive or disjunctive. Then we use LTSmin, that offers transition caching, efficient storage of states and both distributed and symbolic state space generation, for generating the game graph. To that end we define a language module for LTSmin, consisting of an encoding of variables with parameters into state vectors, a grouped transition relation and a dependency matrix to indicate the dependencies between parts of the state vector and transition groups. Benchmarks on some large case studies, show that the method speeds up the instantiation significantly and decreases memory usage drastically.
Complex network analysis of state spaces for random Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Shreim, Amer [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Berdahl, Andrew [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Sood, Vishal [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Grassberger, Peter [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Paczuski, Maya [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada)
2008-01-15
We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 {<=} K {<=} 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2{sup N}, for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two.
Complex network analysis of state spaces for random Boolean networks
International Nuclear Information System (INIS)
Shreim, Amer; Berdahl, Andrew; Sood, Vishal; Grassberger, Peter; Paczuski, Maya
2008-01-01
We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 ≤ K ≤ 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2 N , for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two
Schweizer, B
2005-01-01
Topics include special classes of probabilistic metric spaces, topologies, and several related structures, such as probabilistic normed and inner-product spaces. 1983 edition, updated with 3 new appendixes. Includes 17 illustrations.
Adapted Boolean network models for extracellular matrix formation
Directory of Open Access Journals (Sweden)
Wollbold Johannes
2009-07-01
Full Text Available Abstract Background Due to the rapid data accumulation on pathogenesis and progression of chronic inflammation, there is an increasing demand for approaches to analyse the underlying regulatory networks. For example, rheumatoid arthritis (RA is a chronic inflammatory disease, characterised by joint destruction and perpetuated by activated synovial fibroblasts (SFB. These abnormally express and/or secrete pro-inflammatory cytokines, collagens causing joint fibrosis, or tissue-degrading enzymes resulting in destruction of the extra-cellular matrix (ECM. We applied three methods to analyse ECM regulation: data discretisation to filter out noise and to reduce complexity, Boolean network construction to implement logic relationships, and formal concept analysis (FCA for the formation of minimal, but complete rule sets from the data. Results First, we extracted literature information to develop an interaction network containing 18 genes representing ECM formation and destruction. Subsequently, we constructed an asynchronous Boolean network with biologically plausible time intervals for mRNA and protein production, secretion, and inactivation. Experimental gene expression data was obtained from SFB stimulated by TGFβ1 or by TNFα and discretised thereafter. The Boolean functions of the initial network were improved iteratively by the comparison of the simulation runs to the experimental data and by exploitation of expert knowledge. This resulted in adapted networks for both cytokine stimulation conditions. The simulations were further analysed by the attribute exploration algorithm of FCA, integrating the observed time series in a fine-tuned and automated manner. The resulting temporal rules yielded new contributions to controversially discussed aspects of fibroblast biology (e.g., considerable expression of TNF and MMP9 by fibroblasts stimulation and corroborated previously known facts (e.g., co-expression of collagens and MMPs after TNF
Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles
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Shah Imran
2011-07-01
Full Text Available Abstract Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our
Boolean modeling in systems biology: an overview of methodology and applications
International Nuclear Information System (INIS)
Wang, Rui-Sheng; Albert, Réka; Saadatpour, Assieh
2012-01-01
Mathematical modeling of biological processes provides deep insights into complex cellular systems. While quantitative and continuous models such as differential equations have been widely used, their use is obstructed in systems wherein the knowledge of mechanistic details and kinetic parameters is scarce. On the other hand, a wealth of molecular level qualitative data on individual components and interactions can be obtained from the experimental literature and high-throughput technologies, making qualitative approaches such as Boolean network modeling extremely useful. In this paper, we build on our research to provide a methodology overview of Boolean modeling in systems biology, including Boolean dynamic modeling of cellular networks, attractor analysis of Boolean dynamic models, as well as inferring biological regulatory mechanisms from high-throughput data using Boolean models. We finally demonstrate how Boolean models can be applied to perform the structural analysis of cellular networks. This overview aims to acquaint life science researchers with the basic steps of Boolean modeling and its applications in several areas of systems biology. (paper)
Griffin: A Tool for Symbolic Inference of Synchronous Boolean Molecular Networks
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Stalin Muñoz
2018-03-01
Full Text Available Boolean networks are important models of biochemical systems, located at the high end of the abstraction spectrum. A number of Boolean gene networks have been inferred following essentially the same method. Such a method first considers experimental data for a typically underdetermined “regulation” graph. Next, Boolean networks are inferred by using biological constraints to narrow the search space, such as a desired set of (fixed-point or cyclic attractors. We describe Griffin, a computer tool enhancing this method. Griffin incorporates a number of well-established algorithms, such as Dubrova and Teslenko's algorithm for finding attractors in synchronous Boolean networks. In addition, a formal definition of regulation allows Griffin to employ “symbolic” techniques, able to represent both large sets of network states and Boolean constraints. We observe that when the set of attractors is required to be an exact set, prohibiting additional attractors, a naive Boolean coding of this constraint may be unfeasible. Such cases may be intractable even with symbolic methods, as the number of Boolean constraints may be astronomically large. To overcome this problem, we employ an Artificial Intelligence technique known as “clause learning” considerably increasing Griffin's scalability. Without clause learning only toy examples prohibiting additional attractors are solvable: only one out of seven queries reported here is answered. With clause learning, by contrast, all seven queries are answered. We illustrate Griffin with three case studies drawn from the Arabidopsis thaliana literature. Griffin is available at: http://turing.iimas.unam.mx/griffin.
Boolean Algebra Application in Analysis of Flight Accidents
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Casandra Venera BALAN
2015-12-01
Full Text Available Fault tree analysis is a deductive approach for resolving an undesired event into its causes, identifying the causes of a failure and providing a framework for a qualitative and quantitative evaluation of the top event. An alternative approach to fault tree analysis methods calculus goes to logical expressions and it is based on a graphical representation of the data structure for a logic - based binary decision diagram representation. In this analysis, such sites will be reduced to a minimal size and arranged in the sense that the variables appear in the same order in each path. An event can be defined as a statement that can be true or false. Therefore, Boolean algebra rules allow restructuring of a Fault Tree into one equivalent to it, but simpler.
Logical Attractors: a Boolean Approach to the Dynamics of Psychosis
Kupper, Z.; Hoffmann, H.
A Boolean modeling approach to attractors in the dynamics of psychosis is presented: Kinetic Logic, originating from R. Thomas, describes systems on an intermediate level between a purely verbal, qualitative description and a description using nonlinear differential equations. With this method we may model impact, feedback and temporal evolution, as well as analyze the resulting attractors. In our previous research the method has been applied to general and more specific questions in the dynamics of psychotic disorders. In this paper a model is introduced that describes different dynamical patterns of chronic psychosis in the context of vocational rehabilitation. It also shows to be useful in formulating and exploring possible treatment strategies. Finally, some of the limitations and benefits of Kinetic Logic as a modeling tool for psychology and psychiatry are discussed.
Unlimited multistability and Boolean logic in microbial signalling
DEFF Research Database (Denmark)
Kothamachu, Varun B; Feliu, Elisenda; Cardelli, Luca
2015-01-01
The ability to map environmental signals onto distinct internal physiological states or programmes is critical for single-celled microbes. A crucial systems dynamics feature underpinning such ability is multistability. While unlimited multistability is known to arise from multi-site phosphorylation...... seen in the signalling networks of eukaryotic cells, a similarly universal mechanism has not been identified in microbial signalling systems. These systems are generally known as two-component systems comprising histidine kinase (HK) receptors and response regulator proteins engaging in phosphotransfer...... further prove that sharing of downstream components allows a system with n multi-domain hybrid HKs to attain 3n steady states. We find that such systems, when sensing distinct signals, can readily implement Boolean logic functions on these signals. Using two experimentally studied examples of two...
Minimum energy control and optimal-satisfactory control of Boolean control network
International Nuclear Information System (INIS)
Li, Fangfei; Lu, Xiwen
2013-01-01
In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.
Vectorial Resilient PC(l) of Order k Boolean Functions from AG-Codes
Institute of Scientific and Technical Information of China (English)
Hao CHEN; Liang MA; Jianhua LI
2011-01-01
Propagation criteria and resiliency of vectorial Boolean functions are important for cryptographic purpose (see [1- 4, 7, 8, 10, 11, 16]). Kurosawa, Stoh [8] and Carlet [1]gave a construction of Boolean functions satisfying PC(l) of order k from binary linear or nonlinear codes. In this paper, the algebraic-geometric codes over GF(2m) are used to modify the Carlet and Kurosawa-Satoh's construction for giving vectorial resilient Boolean functions satisfying PC(l) of order k criterion. This new construction is compared with previously known results.
Expected Number of Fixed Points in Boolean Networks with Arbitrary Topology.
Mori, Fumito; Mochizuki, Atsushi
2017-07-14
Boolean network models describe genetic, neural, and social dynamics in complex networks, where the dynamics depend generally on network topology. Fixed points in a genetic regulatory network are typically considered to correspond to cell types in an organism. We prove that the expected number of fixed points in a Boolean network, with Boolean functions drawn from probability distributions that are not required to be uniform or identical, is one, and is independent of network topology if only a feedback arc set satisfies a stochastic neutrality condition. We also demonstrate that the expected number is increased by the predominance of positive feedback in a cycle.
Learning Probabilistic Logic Models from Probabilistic Examples.
Chen, Jianzhong; Muggleton, Stephen; Santos, José
2008-10-01
We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples.
Interpolation of the discrete logarithm in a finite field of characteristic two by Boolean functions
DEFF Research Database (Denmark)
Brandstaetter, Nina; Lange, Tanja; Winterhof, Arne
2005-01-01
We obtain bounds on degree, weight, and the maximal Fourier coefficient of Boolean functions interpolating the discrete logarithm in finite fields of characteristic two. These bounds complement earlier results for finite fields of odd characteristic....
Sensitivity analysis of efficient solution in vector MINMAX boolean programming problem
Directory of Open Access Journals (Sweden)
Vladimir A. Emelichev
2002-11-01
Full Text Available We consider a multiple criterion Boolean programming problem with MINMAX partial criteria. The extreme level of independent perturbations of partial criteria parameters such that efficient (Pareto optimal solution preserves optimality was obtained.
Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables
Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
2013-01-01
In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization
Boolean and advanced searching for EDGAR data on www.sec.gov
Securities and Exchange Commission — This search allows users to enter complex boolean queries to access all but the most recent day's EDGAR filings on www.sec.gov. Filings are from 1994 to present.
Probabilistic Logical Characterization
DEFF Research Database (Denmark)
Hermanns, Holger; Parma, Augusto; Segala, Roberto
2011-01-01
Probabilistic automata exhibit both probabilistic and non-deterministic choice. They are therefore a powerful semantic foundation for modeling concurrent systems with random phenomena arising in many applications ranging from artificial intelligence, security, systems biology to performance...... modeling. Several variations of bisimulation and simulation relations have proved to be useful as means to abstract and compare different automata. This paper develops a taxonomy of logical characterizations of these relations on image-finite and image-infinite probabilistic automata....
Conditional Probabilistic Population Forecasting
Sanderson, W.C.; Scherbov, S.; O'Neill, B.C.; Lutz, W.
2003-01-01
Since policy makers often prefer to think in terms of scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy makers it allows them to answer "what if"...
Conditional probabilistic population forecasting
Sanderson, Warren; Scherbov, Sergei; O'Neill, Brian; Lutz, Wolfgang
2003-01-01
Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because it allows them...
Conditional Probabilistic Population Forecasting
Sanderson, Warren C.; Scherbov, Sergei; O'Neill, Brian C.; Lutz, Wolfgang
2004-01-01
Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because...
Circulant Matrices and Affine Equivalence of Monomial Rotation Symmetric Boolean Functions
2015-01-01
degree of the MRS is, we have a similar result as [40, Theorem 1.1] for n = 4p (p prime), or squarefree integers n, which along with our Theorem 5.2...Boolean functions: Construction and analysis in terms of algebraic immunity, in: H. Gilbert, H. Handschuh (Eds.), Fast Software Encryption, in: LNCS...vol. 1403, Springer-Verlag, 1998, pp. 475–488. [20] J.E. Fuller, Analysis of affine equivalent Boolean functions for cryptography (Ph.D. thesis
Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables
Chikalov, Igor
2013-01-01
In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization of decision trees and decision rules) to conduct experiments. We show that, for each monotone Boolean function with at most five variables, there exists a totally optimal decision tree which is optimal with respect to both depth and number of nodes.
An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks
Cabessa, Jérémie; Villa, Alessandro E. P.
2014-01-01
We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of -automata, and then translating the most refined classification of -automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits. PMID:24727866
Duplicate Detection in Probabilistic Data
Panse, Fabian; van Keulen, Maurice; de Keijzer, Ander; Ritter, Norbert
2009-01-01
Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches have focused
Graphene-based non-Boolean logic circuits
Liu, Guanxiong; Ahsan, Sonia; Khitun, Alexander G.; Lake, Roger K.; Balandin, Alexander A.
2013-10-01
Graphene revealed a number of unique properties beneficial for electronics. However, graphene does not have an energy band-gap, which presents a serious hurdle for its applications in digital logic gates. The efforts to induce a band-gap in graphene via quantum confinement or surface functionalization have not resulted in a breakthrough. Here we show that the negative differential resistance experimentally observed in graphene field-effect transistors of "conventional" design allows for construction of viable non-Boolean computational architectures with the gapless graphene. The negative differential resistance—observed under certain biasing schemes—is an intrinsic property of graphene, resulting from its symmetric band structure. Our atomistic modeling shows that the negative differential resistance appears not only in the drift-diffusion regime but also in the ballistic regime at the nanometer-scale—although the physics changes. The obtained results present a conceptual change in graphene research and indicate an alternative route for graphene's applications in information processing.
Boolean network model of the Pseudomonas aeruginosa quorum sensing circuits.
Dallidis, Stylianos E; Karafyllidis, Ioannis G
2014-09-01
To coordinate their behavior and virulence and to synchronize attacks against their hosts, bacteria communicate by continuously producing signaling molecules (called autoinducers) and continuously monitoring the concentration of these molecules. This communication is controlled by biological circuits called quorum sensing (QS) circuits. Recently QS circuits and have been recognized as an alternative target for controlling bacterial virulence and infections without the use of antibiotics. Pseudomonas aeruginosa is a Gram-negative bacterium that infects insects, plants, animals and humans and can cause acute infections. This bacterium has three interconnected QS circuits that form a very complex and versatile QS system, the operation of which is still under investigation. Here we use Boolean networks to model the complete QS system of Pseudomonas aeruginosa and we simulate and analyze its operation in both synchronous and asynchronous modes. The state space of the QS system is constructed and it turned out to be very large, hierarchical, modular and scale-free. Furthermore, we developed a simulation tool that can simulate gene knock-outs and study their effect on the regulons controlled by the three QS circuits. The model and tools we developed will give to life scientists a deeper insight to this complex QS system.
A New Characterization of ACC0 and Probabilistic CC0
DEFF Research Database (Denmark)
Hansen, Kristoffer Arnsfelt; Koucký, Michal
2010-01-01
Barrington, Straubing & Thérien (1990) conjectured that the Boolean And function can not be computed by polynomial size constant depth circuits built from modular counting gates, i.e., by CC0 circuits. In this work we show that the And function can be computed by uniform probabilistic CC0 circuits...... that use only O(log n) random bits. This may be viewed as evidence contrary to the conjecture. As a consequence of our construction we get that all of ACC0 can be computed by probabilistic CC0 circuits that use only O(log n) random bits. Thus, if one were able to derandomize such circuits, one would obtain...... a collapse of circuit classes giving ACC0 = CC0. We present a derandomization of probabilistic CC0 circuits using And and Or gates to obtain ACC0 = And ο Or ο CC0 = Or ο And ο CC0. (And and Or gates of sublinear fan-in suffice in non-uniform setting.) Both these results hold for uniform as well as non...
Probabilistic Structural Analysis Program
Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.
2010-01-01
NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.
Modeling integrated cellular machinery using hybrid Petri-Boolean networks.
Directory of Open Access Journals (Sweden)
Natalie Berestovsky
Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them
Probabilistic programmable quantum processors
International Nuclear Information System (INIS)
Buzek, V.; Ziman, M.; Hillery, M.
2004-01-01
We analyze how to improve performance of probabilistic programmable quantum processors. We show how the probability of success of the probabilistic processor can be enhanced by using the processor in loops. In addition, we show that an arbitrary SU(2) transformations of qubits can be encoded in program state of a universal programmable probabilistic quantum processor. The probability of success of this processor can be enhanced by a systematic correction of errors via conditional loops. Finally, we show that all our results can be generalized also for qudits. (Abstract Copyright [2004], Wiley Periodicals, Inc.)
Autonomous Modeling, Statistical Complexity and Semi-annealed Treatment of Boolean Networks
Gong, Xinwei
This dissertation presents three studies on Boolean networks. Boolean networks are a class of mathematical systems consisting of interacting elements with binary state variables. Each element is a node with a Boolean logic gate, and the presence of interactions between any two nodes is represented by directed links. Boolean networks that implement the logic structures of real systems are studied as coarse-grained models of the real systems. Large random Boolean networks are studied with mean field approximations and used to provide a baseline of possible behaviors of large real systems. This dissertation presents one study of the former type, concerning the stable oscillation of a yeast cell-cycle oscillator, and two studies of the latter type, respectively concerning the statistical complexity of large random Boolean networks and an extension of traditional mean field techniques that accounts for the presence of short loops. In the cell-cycle oscillator study, a novel autonomous update scheme is introduced to study the stability of oscillations in small networks. A motif that corrects pulse-growing perturbations and a motif that grows pulses are identified. A combination of the two motifs is capable of sustaining stable oscillations. Examining a Boolean model of the yeast cell-cycle oscillator using an autonomous update scheme yields evidence that it is endowed with such a combination. Random Boolean networks are classified as ordered, critical or disordered based on their response to small perturbations. In the second study, random Boolean networks are taken as prototypical cases for the evaluation of two measures of complexity based on a criterion for optimal statistical prediction. One measure, defined for homogeneous systems, does not distinguish between the static spatial inhomogeneity in the ordered phase and the dynamical inhomogeneity in the disordered phase. A modification in which complexities of individual nodes are calculated yields vanishing
Directory of Open Access Journals (Sweden)
Wensheng Guo
Full Text Available In biological systems, the dynamic analysis method has gained increasing attention in the past decade. The Boolean network is the most common model of a genetic regulatory network. The interactions of activation and inhibition in the genetic regulatory network are modeled as a set of functions of the Boolean network, while the state transitions in the Boolean network reflect the dynamic property of a genetic regulatory network. A difficult problem for state transition analysis is the finding of attractors. In this paper, we modeled the genetic regulatory network as a Boolean network and proposed a solving algorithm to tackle the attractor finding problem. In the proposed algorithm, we partitioned the Boolean network into several blocks consisting of the strongly connected components according to their gradients, and defined the connection between blocks as decision node. Based on the solutions calculated on the decision nodes and using a satisfiability solving algorithm, we identified the attractors in the state transition graph of each block. The proposed algorithm is benchmarked on a variety of genetic regulatory networks. Compared with existing algorithms, it achieved similar performance on small test cases, and outperformed it on larger and more complex ones, which happens to be the trend of the modern genetic regulatory network. Furthermore, while the existing satisfiability-based algorithms cannot be parallelized due to their inherent algorithm design, the proposed algorithm exhibits a good scalability on parallel computing architectures.
The spruce budworm and forest: a qualitative comparison of ODE and Boolean models
Directory of Open Access Journals (Sweden)
Raina Robeva
2016-01-01
Full Text Available Boolean and polynomial models of biological systems have emerged recently as viable companions to differential equations models. It is not immediately clear however whether such models are capable of capturing the multi-stable behaviour of certain biological systems: this behaviour is often sensitive to changes in the values of the model parameters, while Boolean and polynomial models are qualitative in nature. In the past few years, Boolean models of gene regulatory systems have been shown to capture multi-stability at the molecular level, confirming that such models can be used to obtain information about the system’s qualitative dynamics when precise information regarding its parameters may not be available. In this paper, we examine Boolean approximations of a classical ODE model of budworm outbreaks in a forest and show that these models exhibit a qualitative behaviour consistent with that derived from the ODE models. In particular, we demonstrate that these models can capture the bistable nature of insect population outbreaks, thus showing that Boolean models can be successfully utilized beyond the molecular level.
Probabilistic Infinite Secret Sharing
Csirmaz, László
2013-01-01
The study of probabilistic secret sharing schemes using arbitrary probability spaces and possibly infinite number of participants lets us investigate abstract properties of such schemes. It highlights important properties, explains why certain definitions work better than others, connects this topic to other branches of mathematics, and might yield new design paradigms. A probabilistic secret sharing scheme is a joint probability distribution of the shares and the secret together with a colle...
Probabilistic Programming (Invited Talk)
Yang, Hongseok
2017-01-01
Probabilistic programming refers to the idea of using standard programming constructs for specifying probabilistic models from machine learning and statistics, and employing generic inference algorithms for answering various queries on these models, such as posterior inference and estimation of model evidence. Although this idea itself is not new and was, in fact, explored by several programming-language and statistics researchers in the early 2000, it is only in the last few years that proba...
Sun, Mengyang; Cheng, Xianrui; Socolar, Joshua E S
2013-06-01
A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.
Acoustic logic gates and Boolean operation based on self-collimating acoustic beams
International Nuclear Information System (INIS)
Zhang, Ting; Xu, Jian-yi; Cheng, Ying; Liu, Xiao-jun; Guo, Jian-zhong
2015-01-01
The reveal of self-collimation effect in two-dimensional (2D) photonic or acoustic crystals has opened up possibilities for signal manipulation. In this paper, we have proposed acoustic logic gates based on the linear interference of self-collimated beams in 2D sonic crystals (SCs) with line-defects. The line defects on the diagonal of the 2D square SCs are actually functioning as a 3 dB splitter. By adjusting the phase difference between two input signals, the basic Boolean logic functions such as XOR, OR, AND, and NOT are achieved both theoretically and experimentally. Due to the non-diffracting property of self-collimation beams, more complex Boolean logic and algorithms such as NAND, NOR, and XNOR can be realized by cascading the basic logic gates. The achievement of acoustic logic gates and Boolean operation provides a promising approach for acoustic signal computing and manipulations
On the Boolean extension of the Birnbaum importance to non-coherent systems
International Nuclear Information System (INIS)
Aliee, Hananeh; Borgonovo, Emanuele; Glaß, Michael; Teich, Jürgen
2017-01-01
The Birnbaum importance measure plays a central role in reliability analysis. It has initially been introduced for coherent systems, where several of its properties hold and where its computation is straightforward. This work introduces a Boolean expression for the notion of criticality that allows the seamless extension of the Birnbaum importance to non-coherent systems. As a key feature, the novel definition makes the computation and encoding straightforward with well-established techniques such as Binary Decision Diagrams (BDDs) or Fault Trees (FTs). Several examples and a case study illustrate the findings. - Highlights: • We propose a Boolean expression for the notion of criticality in coherent and non-coherent systems. • The notion is connected with the Birnbaum importance measure. • The connection with Andrew's and Beeson extension is discussed. • The Boolean expression allows straightforward encoding in Binary Decision Diagrams.
Mechanical system reliability analysis using a combination of graph theory and Boolean function
International Nuclear Information System (INIS)
Tang, J.
2001-01-01
A new method based on graph theory and Boolean function for assessing reliability of mechanical systems is proposed. The procedure for this approach consists of two parts. By using the graph theory, the formula for the reliability of a mechanical system that considers the interrelations of subsystems or components is generated. Use of the Boolean function to examine the failure interactions of two particular elements of the system, followed with demonstrations of how to incorporate such failure dependencies into the analysis of larger systems, a constructive algorithm for quantifying the genuine interconnections between the subsystems or components is provided. The combination of graph theory and Boolean function provides an effective way to evaluate the reliability of a large, complex mechanical system. A numerical example demonstrates that this method an effective approaches in system reliability analysis
Improving the quantum cost of reversible Boolean functions using reorder algorithm
Ahmed, Taghreed; Younes, Ahmed; Elsayed, Ashraf
2018-05-01
This paper introduces a novel algorithm to synthesize a low-cost reversible circuits for any Boolean function with n inputs represented as a Positive Polarity Reed-Muller expansion. The proposed algorithm applies a predefined rules to reorder the terms in the function to minimize the multi-calculation of common parts of the Boolean function to decrease the quantum cost of the reversible circuit. The paper achieves a decrease in the quantum cost and/or the circuit length, on average, when compared with relevant work in the literature.
Lavrova, Anastasia I; Postnikov, Eugene B; Zyubin, Andrey Yu; Babak, Svetlana V
2017-04-01
We consider two approaches to modelling the cell metabolism of 6-mercaptopurine, one of the important chemotherapy drugs used for treating acute lymphocytic leukaemia: kinetic ordinary differential equations, and Boolean networks supplied with one controlling node, which takes continual values. We analyse their interplay with respect to taking into account ATP concentration as a key parameter of switching between different pathways. It is shown that the Boolean networks, which allow avoiding the complexity of general kinetic modelling, preserve the possibility of reproducing the principal switching mechanism.
Characterizing short-term stability for Boolean networks over any distribution of transfer functions
International Nuclear Information System (INIS)
Seshadhri, C.; Smith, Andrew M.; Vorobeychik, Yevgeniy; Mayo, Jackson R.; Armstrong, Robert C.
2016-01-01
Here we present a characterization of short-term stability of random Boolean networks under arbitrary distributions of transfer functions. Given any distribution of transfer functions for a random Boolean network, we present a formula that decides whether short-term chaos (damage spreading) will happen. We provide a formal proof for this formula, and empirically show that its predictions are accurate. Previous work only works for special cases of balanced families. Finally, it has been observed that these characterizations fail for unbalanced families, yet such families are widespread in real biological networks.
2015-12-24
manufacturing today (namely, the 14nm FinFET silicon CMOS technology). The JPEG algorithm is selected as a motivational example since it is widely...TIFF images of a U.S. Air Force F-16 aircraft provided by the University of Southern California Signal and Image Processing Institute (SIPI) image...silicon CMOS technology currently in high volume manufac- turing today (the 14 nm FinFET silicon CMOS technology). The main contribution of this
Mcclenny, Levi D; Imani, Mahdi; Braga-Neto, Ulisses M
2017-11-25
Gene regulatory networks govern the function of key cellular processes, such as control of the cell cycle, response to stress, DNA repair mechanisms, and more. Boolean networks have been used successfully in modeling gene regulatory networks. In the Boolean network model, the transcriptional state of each gene is represented by 0 (inactive) or 1 (active), and the relationship among genes is represented by logical gates updated at discrete time points. However, the Boolean gene states are never observed directly, but only indirectly and incompletely through noisy measurements based on expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays. The Partially-Observed Boolean Dynamical System (POBDS) signal model is distinct from other deterministic and stochastic Boolean network models in removing the requirement of a directly observable Boolean state vector and allowing uncertainty in the measurement process, addressing the scenario encountered in practice in transcriptomic analysis. BoolFilter is an R package that implements the POBDS model and associated algorithms for state and parameter estimation. It allows the user to estimate the Boolean states, network topology, and measurement parameters from time series of transcriptomic data using exact and approximated (particle) filters, as well as simulate the transcriptomic data for a given Boolean network model. Some of its infrastructure, such as the network interface, is the same as in the previously published R package for Boolean Networks BoolNet, which enhances compatibility and user accessibility to the new package. We introduce the R package BoolFilter for Partially-Observed Boolean Dynamical Systems (POBDS). The BoolFilter package provides a useful toolbox for the bioinformatics community, with state-of-the-art algorithms for simulation of time series transcriptomic data as well as the inverse process of system identification from data obtained with various expression
Sayers, Adrian; Ben-Shlomo, Yoav; Blom, Ashley W; Steele, Fiona
2016-06-01
Studies involving the use of probabilistic record linkage are becoming increasingly common. However, the methods underpinning probabilistic record linkage are not widely taught or understood, and therefore these studies can appear to be a 'black box' research tool. In this article, we aim to describe the process of probabilistic record linkage through a simple exemplar. We first introduce the concept of deterministic linkage and contrast this with probabilistic linkage. We illustrate each step of the process using a simple exemplar and describe the data structure required to perform a probabilistic linkage. We describe the process of calculating and interpreting matched weights and how to convert matched weights into posterior probabilities of a match using Bayes theorem. We conclude this article with a brief discussion of some of the computational demands of record linkage, how you might assess the quality of your linkage algorithm, and how epidemiologists can maximize the value of their record-linked research using robust record linkage methods. © The Author 2015; Published by Oxford University Press on behalf of the International Epidemiological Association.
Energy Technology Data Exchange (ETDEWEB)
Torres V, A.; Rivero O, J.J. [Dpto. Ingenieria Nuclear, Instituto Superior de Tecnologias y Ciencias Aplicadas, Ave. Salvador Allende y Luaces, Quinta de los Molinos, Plaza, Ciudad Habana (Cuba)]. e-mail: atorres@fctn.isctn.edu.cu
2004-07-01
The Boolean equation represented by the minimum sets of court at level of a system or of all one Probabilistic safety analysis (APS) it has been used for to evaluate the output configurations of service of teams during the exploitation. It has been carried out through applications of APS for the optimization of operational regimes. The obtaining of such boolean equations as demands of a process of high mathematical complexity for what exhaustive studies are required, even for the application of their results. The important advantages for the maintenance that they obtain of these applications they require the development of methodologies that bring near these optimization methods to the systems of management of the maintenance, and not facilitate their use for a personnel specialized in the probabilistic topics. The article presents a methodology for the preparation, solution and utilization of the results of the fault tree leaving of technological outlines. This algorithm has been automated through the MOSEG code Win to Ver 1.0 (Author)
Formalizing Probabilistic Safety Claims
Herencia-Zapana, Heber; Hagen, George E.; Narkawicz, Anthony J.
2011-01-01
A safety claim for a system is a statement that the system, which is subject to hazardous conditions, satisfies a given set of properties. Following work by John Rushby and Bev Littlewood, this paper presents a mathematical framework that can be used to state and formally prove probabilistic safety claims. It also enables hazardous conditions, their uncertainties, and their interactions to be integrated into the safety claim. This framework provides a formal description of the probabilistic composition of an arbitrary number of hazardous conditions and their effects on system behavior. An example is given of a probabilistic safety claim for a conflict detection algorithm for aircraft in a 2D airspace. The motivation for developing this mathematical framework is that it can be used in an automated theorem prover to formally verify safety claims.
The Concept of the "Imploded Boolean Search": A Case Study with Undergraduate Chemistry Students
Tomaszewski, Robert
2016-01-01
Critical thinking and analytical problem-solving skills in research involves using different search strategies. A proposed concept for an "Imploded Boolean Search" combines three unique identifiable field types to perform a search: keyword(s), numerical value(s), and a chemical structure or reaction. The object of this type of search is…
Application of fuzzy logic to Boolean models for digital soil assessment
Gruijter, de J.J.; Walvoort, D.J.J.; Bragato, G.
2011-01-01
Boolean models based on expert knowledge are often used to classify soils into a limited number of classes of a difficult-to-measure soil attribute. Although the primary data used for these classifications contain information on whether the soil is a typical class member or a boundary case between
Boolean logic and character state identity: pitfalls of character coding in metazoan cladistics
Jenner, Ronald A.
2002-01-01
A critical study of the morphological data sets used for the most recent analyses of metazoan cladistics exposes a rather cavalier attitude towards character coding. Binary absence/presence coding is ubiquitous, but without any explicit justification. This uncompromising application of Boolean logic
A new separation algorithm for the Boolean quadric and cut polytopes
DEFF Research Database (Denmark)
Sørensen, Michael Malmros; Letchford, Adam N.
2014-01-01
A separation algorithm is a procedure for generating cutting planes. Up to now, only a few polynomial-time separation algorithms were known for the Boolean quadric and cut polytopes. These polytopes arise in connection with zero–one quadratic programming and the max-cut problem, respectively. We...
Analysis and control of Boolean networks a semi-tensor product approach
Cheng, Daizhan; Li, Zhiqiang
2010-01-01
This book presents a new approach to the investigation of Boolean control networks, using the semi-tensor product (STP), which can express a logical function as a conventional discrete-time linear system. This makes it possible to analyze basic control problems.
Describing the What and Why of Students' Difficulties in Boolean Logic
Herman, Geoffrey L.; Loui, Michael C.; Kaczmarczyk, Lisa; Zilles, Craig
2012-01-01
The ability to reason with formal logic is a foundational skill for computer scientists and computer engineers that scaffolds the abilities to design, debug, and optimize. By interviewing students about their understanding of propositional logic and their ability to translate from English specifications to Boolean expressions, we characterized…
Complete ccc Boolean algebras, the order sequential topology, and a problem of von Neumann
Czech Academy of Sciences Publication Activity Database
Balcar, Bohuslav; Jech, Thomas; Pazák, Tomáš
2005-01-01
Roč. 37, č. 6 (2005), s. 885-898 ISSN 0024-6093 Institutional research plan: CEZ:AV0Z10750506; CEZ:AV0Z10190503 Keywords : Boolean algebras * Maharam submeasure * weak distributivity * independent reals Subject RIV: BA - General Mathematics Impact factor: 0.477, year: 2005
Using Vector and Extended Boolean Matching in an Expert System for Selecting Foster Homes.
Fox, Edward A.; Winett, Sheila G.
1990-01-01
Describes FOCES (Foster Care Expert System), a prototype expert system for choosing foster care placements for children which integrates information retrieval techniques with artificial intelligence. The use of prototypes and queries in Prolog routines, extended Boolean matching, and vector correlation are explained, as well as evaluation by…
Characterization of Boolean Algebras in Terms of Certain States of Jauch-Piron Type
Matoušek, Milan; Pták, Pavel
2015-12-01
Suppose that L is an orthomodular lattice (a quantum logic). We show that L is Boolean exactly if L possesses a strongly unital set of weakly Jauch-Piron states, or if L possesses a unital set of weakly positive states. We also discuss some general properties of Jauch-Piron-like states.
Finite size effects and symmetry breaking in the evolution of networks of competing Boolean nodes
International Nuclear Information System (INIS)
Liu, M; Bassler, K E
2011-01-01
Finite size effects on the evolutionary dynamics of Boolean networks are analyzed. In the model considered, Boolean networks evolve via a competition between nodes that punishes those in the majority. Previous studies have found that large networks evolve to a statistical steady state that is both critical and highly canalized, and that the evolution of canalization, which is a form of robustness found in genetic regulatory networks, is associated with a particular symmetry of the evolutionary dynamics. Here, it is found that finite size networks evolve in a fundamentally different way than infinitely large networks do. The symmetry of the evolutionary dynamics of infinitely large networks that selects for canalizing Boolean functions is broken in the evolutionary dynamics of finite size networks. In finite size networks, there is an additional selection for input-inverting Boolean functions that output a value opposite to the majority of input values. The reason for the symmetry breaking in the evolutionary dynamics is found to be due to the need for nodes in finite size networks to behave differently in order to cooperate so that the system collectively performs as efficiently as possible. The results suggest that both finite size effects and symmetry are fundamental for understanding the evolution of real-world complex networks, including genetic regulatory networks.
Czech Academy of Sciences Publication Activity Database
Kramosil, Ivan
2001-01-01
Roč. 5, č. 1 (2001), s. 45-57 ISSN 1432-7643 R&D Projects: GA AV ČR IAA1030803 Institutional research plan: AV0Z1030915 Keywords : first-order predicate calculus * standard semantics * Boolean-like semantics * frequentistic semantics * completness theorems Subject RIV: BA - General Mathematics
User Practices in Keyword and Boolean Searching on an Online Public Access Catalog.
Ensor, Pat
1992-01-01
Discussion of keyword and Boolean searching techniques in online public access catalogs (OPACs) focuses on a study conducted at Indiana State University that examined users' attitudes toward searching on NOTIS (Northwestern Online Total Integrated System). Relevant literature is reviewed, and implications for library instruction are suggested. (17…
An Efficient Algorithm for Computing Attractors of Synchronous And Asynchronous Boolean Networks
Zheng, Desheng; Yang, Guowu; Li, Xiaoyu; Wang, Zhicai; Liu, Feng; He, Lei
2013-01-01
Biological networks, such as genetic regulatory networks, often contain positive and negative feedback loops that settle down to dynamically stable patterns. Identifying these patterns, the so-called attractors, can provide important insights for biologists to understand the molecular mechanisms underlying many coordinated cellular processes such as cellular division, differentiation, and homeostasis. Both synchronous and asynchronous Boolean networks have been used to simulate genetic regulatory networks and identify their attractors. The common methods of computing attractors are that start with a randomly selected initial state and finish with exhaustive search of the state space of a network. However, the time complexity of these methods grows exponentially with respect to the number and length of attractors. Here, we build two algorithms to achieve the computation of attractors in synchronous and asynchronous Boolean networks. For the synchronous scenario, combing with iterative methods and reduced order binary decision diagrams (ROBDD), we propose an improved algorithm to compute attractors. For another algorithm, the attractors of synchronous Boolean networks are utilized in asynchronous Boolean translation functions to derive attractors of asynchronous scenario. The proposed algorithms are implemented in a procedure called geneFAtt. Compared to existing tools such as genYsis, geneFAtt is significantly faster in computing attractors for empirical experimental systems. Availability The software package is available at https://sites.google.com/site/desheng619/download. PMID:23585840
Ostrowski, M; Paulevé, L; Schaub, T; Siegel, A; Guziolowski, C
2016-11-01
Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Exact sampling from conditional Boolean models with applications to maximum likelihood inference
Lieshout, van M.N.M.; Zwet, van E.W.
2001-01-01
We are interested in estimating the intensity parameter of a Boolean model of discs (the bombing model) from a single realization. To do so, we derive the conditional distribution of the points (germs) of the underlying Poisson process. We demonstrate how to apply coupling from the past to generate
DEFF Research Database (Denmark)
Larsen, Kim Guldstrand; Mardare, Radu Iulian; Xue, Bingtian
2016-01-01
We introduce a version of the probabilistic µ-calculus (PMC) built on top of a probabilistic modal logic that allows encoding n-ary inequational conditions on transition probabilities. PMC extends previously studied calculi and we prove that, despite its expressiveness, it enjoys a series of good...... metaproperties. Firstly, we prove the decidability of satisﬁability checking by establishing the small model property. An algorithm for deciding the satisﬁability problem is developed. As a second major result, we provide a complete axiomatization for the alternation-free fragment of PMC. The completeness proof...
Probabilistic conditional independence structures
Studeny, Milan
2005-01-01
Probabilistic Conditional Independence Structures provides the mathematical description of probabilistic conditional independence structures; the author uses non-graphical methods of their description, and takes an algebraic approach.The monograph presents the methods of structural imsets and supermodular functions, and deals with independence implication and equivalence of structural imsets.Motivation, mathematical foundations and areas of application are included, and a rough overview of graphical methods is also given.In particular, the author has been careful to use suitable terminology, and presents the work so that it will be understood by both statisticians, and by researchers in artificial intelligence.The necessary elementary mathematical notions are recalled in an appendix.
Probabilistic approach to mechanisms
Sandler, BZ
1984-01-01
This book discusses the application of probabilistics to the investigation of mechanical systems. The book shows, for example, how random function theory can be applied directly to the investigation of random processes in the deflection of cam profiles, pitch or gear teeth, pressure in pipes, etc. The author also deals with some other technical applications of probabilistic theory, including, amongst others, those relating to pneumatic and hydraulic mechanisms and roller bearings. Many of the aspects are illustrated by examples of applications of the techniques under discussion.
Probabilistic systems coalgebraically: A survey
Sokolova, Ana
2011-01-01
We survey the work on both discrete and continuous-space probabilistic systems as coalgebras, starting with how probabilistic systems are modeled as coalgebras and followed by a discussion of their bisimilarity and behavioral equivalence, mentioning results that follow from the coalgebraic treatment of probabilistic systems. It is interesting to note that, for different reasons, for both discrete and continuous probabilistic systems it may be more convenient to work with behavioral equivalence than with bisimilarity. PMID:21998490
Veliz-Cuba, Alan; Aguilar, Boris; Hinkelmann, Franziska; Laubenbacher, Reinhard
2014-06-26
A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for
Quantum algorithms on Walsh transform and Hamming distance for Boolean functions
Xie, Zhengwei; Qiu, Daowen; Cai, Guangya
2018-06-01
Walsh spectrum or Walsh transform is an alternative description of Boolean functions. In this paper, we explore quantum algorithms to approximate the absolute value of Walsh transform W_f at a single point z0 (i.e., |W_f(z0)|) for n-variable Boolean functions with probability at least 8/π 2 using the number of O(1/|W_f(z_{0)|ɛ }) queries, promised that the accuracy is ɛ , while the best known classical algorithm requires O(2n) queries. The Hamming distance between Boolean functions is used to study the linearity testing and other important problems. We take advantage of Walsh transform to calculate the Hamming distance between two n-variable Boolean functions f and g using O(1) queries in some cases. Then, we exploit another quantum algorithm which converts computing Hamming distance between two Boolean functions to quantum amplitude estimation (i.e., approximate counting). If Ham(f,g)=t≠0, we can approximately compute Ham( f, g) with probability at least 2/3 by combining our algorithm and {Approx-Count(f,ɛ ) algorithm} using the expected number of Θ( √{N/(\\lfloor ɛ t\\rfloor +1)}+√{t(N-t)}/\\lfloor ɛ t\\rfloor +1) queries, promised that the accuracy is ɛ . Moreover, our algorithm is optimal, while the exact query complexity for the above problem is Θ(N) and the query complexity with the accuracy ɛ is O(1/ɛ 2N/(t+1)) in classical algorithm, where N=2n. Finally, we present three exact quantum query algorithms for two promise problems on Hamming distance using O(1) queries, while any classical deterministic algorithm solving the problem uses Ω(2n) queries.
Confluence reduction for probabilistic systems
Timmer, Mark; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette
In this presentation we introduce a novel technique for state space reduction of probabilistic specifications, based on a newly developed notion of confluence for probabilistic automata. We proved that this reduction preserves branching probabilistic bisimulation and can be applied on-the-fly. To
Bergstra, J.A.; Middelburg, C.A.
2015-01-01
We add probabilistic features to basic thread algebra and its extensions with thread-service interaction and strategic interleaving. Here, threads represent the behaviours produced by instruction sequences under execution and services represent the behaviours exhibited by the components of execution
Probabilistic simple sticker systems
Selvarajoo, Mathuri; Heng, Fong Wan; Sarmin, Nor Haniza; Turaev, Sherzod
2017-04-01
A model for DNA computing using the recombination behavior of DNA molecules, known as a sticker system, was introduced by by L. Kari, G. Paun, G. Rozenberg, A. Salomaa, and S. Yu in the paper entitled DNA computing, sticker systems and universality from the journal of Acta Informatica vol. 35, pp. 401-420 in the year 1998. A sticker system uses the Watson-Crick complementary feature of DNA molecules: starting from the incomplete double stranded sequences, and iteratively using sticking operations until a complete double stranded sequence is obtained. It is known that sticker systems with finite sets of axioms and sticker rules generate only regular languages. Hence, different types of restrictions have been considered to increase the computational power of sticker systems. Recently, a variant of restricted sticker systems, called probabilistic sticker systems, has been introduced [4]. In this variant, the probabilities are initially associated with the axioms, and the probability of a generated string is computed by multiplying the probabilities of all occurrences of the initial strings in the computation of the string. Strings for the language are selected according to some probabilistic requirements. In this paper, we study fundamental properties of probabilistic simple sticker systems. We prove that the probabilistic enhancement increases the computational power of simple sticker systems.
Visualizing Probabilistic Proof
Guerra-Pujol, Enrique
2015-01-01
The author revisits the Blue Bus Problem, a famous thought-experiment in law involving probabilistic proof, and presents simple Bayesian solutions to different versions of the blue bus hypothetical. In addition, the author expresses his solutions in standard and visual formats, i.e. in terms of probabilities and natural frequencies.
Memristive Probabilistic Computing
Alahmadi, Hamzah
2017-10-01
In the era of Internet of Things and Big Data, unconventional techniques are rising to accommodate the large size of data and the resource constraints. New computing structures are advancing based on non-volatile memory technologies and different processing paradigms. Additionally, the intrinsic resiliency of current applications leads to the development of creative techniques in computations. In those applications, approximate computing provides a perfect fit to optimize the energy efficiency while compromising on the accuracy. In this work, we build probabilistic adders based on stochastic memristor. Probabilistic adders are analyzed with respect of the stochastic behavior of the underlying memristors. Multiple adder implementations are investigated and compared. The memristive probabilistic adder provides a different approach from the typical approximate CMOS adders. Furthermore, it allows for a high area saving and design exibility between the performance and power saving. To reach a similar performance level as approximate CMOS adders, the memristive adder achieves 60% of power saving. An image-compression application is investigated using the memristive probabilistic adders with the performance and the energy trade-off.
DEFF Research Database (Denmark)
Chen, Peiyuan; Chen, Zhe; Bak-Jensen, Birgitte
2008-01-01
This paper reviews the development of the probabilistic load flow (PLF) techniques. Applications of the PLF techniques in different areas of power system steady-state analysis are also discussed. The purpose of the review is to identify different available PLF techniques and their corresponding...
Transitive probabilistic CLIR models.
Kraaij, W.; de Jong, Franciska M.G.
2004-01-01
Transitive translation could be a useful technique to enlarge the number of supported language pairs for a cross-language information retrieval (CLIR) system in a cost-effective manner. The paper describes several setups for transitive translation based on probabilistic translation models. The
Bell-Boole Inequality: Nonlocality or Probabilistic Incompatibility of Random Variables?
Directory of Open Access Journals (Sweden)
Andrei Khrennikov
2008-03-01
Full Text Available The main aim of this report is to inform the quantum information community about investigations on the problem of probabilistic compatibility of a family of random variables: a possibility to realize such a family on the basis of a single probability measure (to construct a single Kolmogorov probability space. These investigations were started hundred of years ago by J. Boole (who invented Boolean algebras. The complete solution of the problem was obtained by Soviet mathematician Vorobjev in 60th. Surprisingly probabilists and statisticians obtained inequalities for probabilities and correlations among which one can find the famous BellÃ¢Â€Â™s inequality and its generalizations. Such inequalities appeared simply as constraints for probabilistic compatibility. In this framework one can not see a priori any link to such problems as nonlocality and Ã¢Â€Âœdeath of realityÃ¢Â€Â which are typically linked to BellÃ¢Â€Â™s type inequalities in physical literature. We analyze the difference between positions of mathematicians and quantum physicists. In particular, we found that one of the most reasonable explanations of probabilistic incompatibility is mixing in BellÃ¢Â€Â™s type inequalities statistical data from a number of experiments performed under different experimental contexts.
Probabilistic assessment of faults
International Nuclear Information System (INIS)
Foden, R.W.
1987-01-01
Probabilistic safety analysis (PSA) is the process by which the probability (or frequency of occurrence) of reactor fault conditions which could lead to unacceptable consequences is assessed. The basic objective of a PSA is to allow a judgement to be made as to whether or not the principal probabilistic requirement is satisfied. It also gives insights into the reliability of the plant which can be used to identify possible improvements. This is explained in the article. The scope of a PSA and the PSA performed by the National Nuclear Corporation (NNC) for the Heysham II and Torness AGRs and Sizewell-B PWR are discussed. The NNC methods for hazards, common cause failure and operator error are mentioned. (UK)
Cordón García, Oscar; Moya Anegón, Félix de; Zarco Fernández, Carmen
2000-01-01
[ES] Although the fuzzy retrieval model constitutes a powerful extension of the boolean one, being able to deal with the imprecision and subjectivity existing in the Information Retrieval process, users are not usually able to express their query requirements in the form of an extended boolean query including weights. To solve this problem, different tools to assist the user in the query formulation have been proposed. In this paper, the genetic algorithm-programming technique is considered t...
Probabilistic Model Development
Adam, James H., Jr.
2010-01-01
Objective: Develop a Probabilistic Model for the Solar Energetic Particle Environment. Develop a tool to provide a reference solar particle radiation environment that: 1) Will not be exceeded at a user-specified confidence level; 2) Will provide reference environments for: a) Peak flux; b) Event-integrated fluence; and c) Mission-integrated fluence. The reference environments will consist of: a) Elemental energy spectra; b) For protons, helium and heavier ions.
Geothermal probabilistic cost study
Energy Technology Data Exchange (ETDEWEB)
Orren, L.H.; Ziman, G.M.; Jones, S.C.; Lee, T.K.; Noll, R.; Wilde, L.; Sadanand, V.
1981-08-01
A tool is presented to quantify the risks of geothermal projects, the Geothermal Probabilistic Cost Model (GPCM). The GPCM model is used to evaluate a geothermal reservoir for a binary-cycle electric plant at Heber, California. Three institutional aspects of the geothermal risk which can shift the risk among different agents are analyzed. The leasing of geothermal land, contracting between the producer and the user of the geothermal heat, and insurance against faulty performance are examined. (MHR)
Probabilistic approaches to recommendations
Barbieri, Nicola; Ritacco, Ettore
2014-01-01
The importance of accurate recommender systems has been widely recognized by academia and industry, and recommendation is rapidly becoming one of the most successful applications of data mining and machine learning. Understanding and predicting the choices and preferences of users is a challenging task: real-world scenarios involve users behaving in complex situations, where prior beliefs, specific tendencies, and reciprocal influences jointly contribute to determining the preferences of users toward huge amounts of information, services, and products. Probabilistic modeling represents a robus
Probabilistic liver atlas construction.
Dura, Esther; Domingo, Juan; Ayala, Guillermo; Marti-Bonmati, Luis; Goceri, E
2017-01-13
Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step. We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.
Belytschko, Ted; Wing, Kam Liu
1987-01-01
In the Probabilistic Finite Element Method (PFEM), finite element methods have been efficiently combined with second-order perturbation techniques to provide an effective method for informing the designer of the range of response which is likely in a given problem. The designer must provide as input the statistical character of the input variables, such as yield strength, load magnitude, and Young's modulus, by specifying their mean values and their variances. The output then consists of the mean response and the variance in the response. Thus the designer is given a much broader picture of the predicted performance than with simply a single response curve. These methods are applicable to a wide class of problems, provided that the scale of randomness is not too large and the probabilistic density functions possess decaying tails. By incorporating the computational techniques we have developed in the past 3 years for efficiency, the probabilistic finite element methods are capable of handling large systems with many sources of uncertainties. Sample results for an elastic-plastic ten-bar structure and an elastic-plastic plane continuum with a circular hole subject to cyclic loadings with the yield stress on the random field are given.
Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R
2017-01-01
Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.
CIRCUIT IMPLEMENTATION OF VHDL-DESCRIPTIONS OF SYSTEMS OF PARTIAL BOOLEAN FUNCTIONS
Directory of Open Access Journals (Sweden)
P. N. Bibilo
2016-01-01
Full Text Available Method for description of incompletely specified (partial Boolean functions in VHDL is proposed. Examples of synthesized VHDL models of partial Boolean functions are presented; and the results of experiments on circuit implementation of VHDL descriptions of systems of partial functions. The realizability of original partial functions in logical circuits was verified by formal verification. The results of the experiments show that the preliminary minimization in DNF class and in the class of BDD representations for pseudo-random systems of completely specified functions does not improve practically (and in the case of BDD sometimes worsens the results of the subsequent synthesis in the basis of FPGA unlike the significant efficiency of these procedures for the synthesis of benchmark circuits taken from the practice of the design.
Realization of a quantum Hamiltonian Boolean logic gate on the Si(001):H surface.
Kolmer, Marek; Zuzak, Rafal; Dridi, Ghassen; Godlewski, Szymon; Joachim, Christian; Szymonski, Marek
2015-08-07
The design and construction of the first prototypical QHC (Quantum Hamiltonian Computing) atomic scale Boolean logic gate is reported using scanning tunnelling microscope (STM) tip-induced atom manipulation on an Si(001):H surface. The NOR/OR gate truth table was confirmed by dI/dU STS (Scanning Tunnelling Spectroscopy) tracking how the surface states of the QHC quantum circuit on the Si(001):H surface are shifted according to the input logical status.
Web-page Prediction for Domain Specific Web-search using Boolean Bit Mask
Sinha, Sukanta; Duttagupta, Rana; Mukhopadhyay, Debajyoti
2012-01-01
Search Engine is a Web-page retrieval tool. Nowadays Web searchers utilize their time using an efficient search engine. To improve the performance of the search engine, we are introducing a unique mechanism which will give Web searchers more prominent search results. In this paper, we are going to discuss a domain specific Web search prototype which will generate the predicted Web-page list for user given search string using Boolean bit mask.
Identification of control targets in Boolean molecular network models via computational algebra.
Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard
2016-09-23
Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.
Complete CCC Boolean Algebras, the order Sequential Topology, and a Problem of von Neumann
Czech Academy of Sciences Publication Activity Database
Balcar, Bohuslav; Jech, Thomas; Pazák, Tomáš
2005-01-01
Roč. 37, č. 6 (2005), s. 885-898 ISSN 0024-6093 R&D Projects: GA ČR(CZ) GA201/02/0857; GA ČR(CZ) GA201/03/0933 Institutional research plan: CEZ:AV0Z10190503 Keywords : Boolean algebra * Maharam submeasure * weak distributivity Subject RIV: BA - General Mathematics Impact factor: 0.477, year: 2005
THE METHOD OF CONSTRUCTING A BOOLEAN FORMULA OF A POLYGON IN THE DISJUNCTIVE NORMAL FORM
Directory of Open Access Journals (Sweden)
A. A. Butov
2014-01-01
Full Text Available The paper focuses on finalizing the method of finding a polygon Boolean formula in disjunctive normal form, described in the previous article [1]. An improved method eliminates the drawback asso-ciated with the existence of a class of problems for which the solution is only approximate. The pro-posed method always allows to find an exact solution. The method can be used, in particular, in the systems of computer-aided design of integrated circuits topology.
Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain
Czech Academy of Sciences Publication Activity Database
Frolov, A.; Húsek, Dušan; Polyakov, P.Y.
2016-01-01
Roč. 27, č. 3 (2016), s. 538-550 ISSN 2162-237X R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:67985807 Keywords : associative memory * bars problem (BP) * Boolean factor analysis (BFA) * data mining * dimension reduction * Hebbian learning rule * information gain * likelihood maximization (LM) * neural network application * recurrent neural network * statistics Subject RIV: IN - Informatics, Computer Science Impact factor: 6.108, year: 2016
Recurrent Neural Network Based Boolean Factor Analysis and its Application to Word Clustering
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.
2009-01-01
Roč. 20, č. 7 (2009), s. 1073-1086 ISSN 1045-9227 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.889, year: 2009
Probabilistic Tsunami Hazard Analysis
Thio, H. K.; Ichinose, G. A.; Somerville, P. G.; Polet, J.
2006-12-01
The recent tsunami disaster caused by the 2004 Sumatra-Andaman earthquake has focused our attention to the hazard posed by large earthquakes that occur under water, in particular subduction zone earthquakes, and the tsunamis that they generate. Even though these kinds of events are rare, the very large loss of life and material destruction caused by this earthquake warrant a significant effort towards the mitigation of the tsunami hazard. For ground motion hazard, Probabilistic Seismic Hazard Analysis (PSHA) has become a standard practice in the evaluation and mitigation of seismic hazard to populations in particular with respect to structures, infrastructure and lifelines. Its ability to condense the complexities and variability of seismic activity into a manageable set of parameters greatly facilitates the design of effective seismic resistant buildings but also the planning of infrastructure projects. Probabilistic Tsunami Hazard Analysis (PTHA) achieves the same goal for hazards posed by tsunami. There are great advantages of implementing such a method to evaluate the total risk (seismic and tsunami) to coastal communities. The method that we have developed is based on the traditional PSHA and therefore completely consistent with standard seismic practice. Because of the strong dependence of tsunami wave heights on bathymetry, we use a full waveform tsunami waveform computation in lieu of attenuation relations that are common in PSHA. By pre-computing and storing the tsunami waveforms at points along the coast generated for sets of subfaults that comprise larger earthquake faults, we can efficiently synthesize tsunami waveforms for any slip distribution on those faults by summing the individual subfault tsunami waveforms (weighted by their slip). This efficiency make it feasible to use Green's function summation in lieu of attenuation relations to provide very accurate estimates of tsunami height for probabilistic calculations, where one typically computes
Directory of Open Access Journals (Sweden)
Jens Christian Claussen
2017-06-01
Full Text Available The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions.
Detecting small attractors of large Boolean networks by function-reduction-based strategy.
Zheng, Qiben; Shen, Liangzhong; Shang, Xuequn; Liu, Wenbin
2016-04-01
Boolean networks (BNs) are widely used to model gene regulatory networks and to design therapeutic intervention strategies to affect the long-term behaviour of systems. A central aim of Boolean-network analysis is to find attractors that correspond to various cellular states, such as cell types or the stage of cell differentiation. This problem is NP-hard and various algorithms have been used to tackle it with considerable success. The idea is that a singleton attractor corresponds to n consistent subsequences in the truth table. To find these subsequences, the authors gradually reduce the entire truth table of Boolean functions by extending a partial gene activity profile (GAP). Not only does this process delete inconsistent subsequences in truth tables, it also directly determines values for some nodes not extended, which means it can abandon the partial GAPs that cannot lead to an attractor as early as possible. The results of simulation show that the proposed algorithm can detect small attractors with length p = 4 in BNs of up to 200 nodes with average indegree K = 2.
PATHLOGIC-S: a scalable Boolean framework for modelling cellular signalling.
Directory of Open Access Journals (Sweden)
Liam G Fearnley
Full Text Available Curated databases of signal transduction have grown to describe several thousand reactions, and efficient use of these data requires the development of modelling tools to elucidate and explore system properties. We present PATHLOGIC-S, a Boolean specification for a signalling model, with its associated GPL-licensed implementation using integer programming techniques. The PATHLOGIC-S specification has been designed to function on current desktop workstations, and is capable of providing analyses on some of the largest currently available datasets through use of Boolean modelling techniques to generate predictions of stable and semi-stable network states from data in community file formats. PATHLOGIC-S also addresses major problems associated with the presence and modelling of inhibition in Boolean systems, and reduces logical incoherence due to common inhibitory mechanisms in signalling systems. We apply this approach to signal transduction networks including Reactome and two pathways from the Panther Pathways database, and present the results of computations on each along with a discussion of execution time. A software implementation of the framework and model is freely available under a GPL license.
Exploring candidate biological functions by Boolean Function Networks for Saccharomyces cerevisiae.
Directory of Open Access Journals (Sweden)
Maria Simak
Full Text Available The great amount of gene expression data has brought a big challenge for the discovery of Gene Regulatory Network (GRN. For network reconstruction and the investigation of regulatory relations, it is desirable to ensure directness of links between genes on a map, infer their directionality and explore candidate biological functions from high-throughput transcriptomic data. To address these problems, we introduce a Boolean Function Network (BFN model based on techniques of hidden Markov model (HMM, likelihood ratio test and Boolean logic functions. BFN consists of two consecutive tests to establish links between pairs of genes and check their directness. We evaluate the performance of BFN through the application to S. cerevisiae time course data. BFN produces regulatory relations which show consistency with succession of cell cycle phases. Furthermore, it also improves sensitivity and specificity when compared with alternative methods of genetic network reverse engineering. Moreover, we demonstrate that BFN can provide proper resolution for GO enrichment of gene sets. Finally, the Boolean functions discovered by BFN can provide useful insights for the identification of control mechanisms of regulatory processes, which is the special advantage of the proposed approach. In combination with low computational complexity, BFN can serve as an efficient screening tool to reconstruct genes relations on the whole genome level. In addition, the BFN approach is also feasible to a wide range of time course datasets.
PARAMETER ESTIMATION IN NON-HOMOGENEOUS BOOLEAN MODELS: AN APPLICATION TO PLANT DEFENSE RESPONSE
Directory of Open Access Journals (Sweden)
Maria Angeles Gallego
2014-11-01
Full Text Available Many medical and biological problems require to extract information from microscopical images. Boolean models have been extensively used to analyze binary images of random clumps in many scientific fields. In this paper, a particular type of Boolean model with an underlying non-stationary point process is considered. The intensity of the underlying point process is formulated as a fixed function of the distance to a region of interest. A method to estimate the parameters of this Boolean model is introduced, and its performance is checked in two different settings. Firstly, a comparative study with other existent methods is done using simulated data. Secondly, the method is applied to analyze the longleaf data set, which is a very popular data set in the context of point processes included in the R package spatstat. Obtained results show that the new method provides as accurate estimates as those obtained with more complex methods developed for the general case. Finally, to illustrate the application of this model and this method, a particular type of phytopathological images are analyzed. These images show callose depositions in leaves of Arabidopsis plants. The analysis of callose depositions, is very popular in the phytopathological literature to quantify activity of plant immunity.
Some probabilistic aspects of fracture
International Nuclear Information System (INIS)
Thomas, J.M.
1982-01-01
Some probabilistic aspects of fracture in structural and mechanical components are examined. The principles of fracture mechanics, material quality and inspection uncertainty are formulated into a conceptual and analytical framework for prediction of failure probability. The role of probabilistic fracture mechanics in a more global context of risk and optimization of decisions is illustrated. An example, where Monte Carlo simulation was used to implement a probabilistic fracture mechanics analysis, is discussed. (orig.)
Probabilistic safety assessment
International Nuclear Information System (INIS)
Hoertner, H.; Schuetz, B.
1982-09-01
For the purpose of assessing applicability and informativeness on risk-analysis methods in licencing procedures under atomic law, the choice of instruments for probabilistic analysis, the problems in and experience gained in their application, and the discussion of safety goals with respect to such instruments are of paramount significance. Naturally, such a complex field can only be dealt with step by step, making contribution relative to specific problems. The report on hand shows the essentials of a 'stocktaking' of systems relability studies in the licencing procedure under atomic law and of an American report (NUREG-0739) on 'Quantitative Safety Goals'. (orig.) [de
Probabilistic methods for physics
International Nuclear Information System (INIS)
Cirier, G
2013-01-01
We present an asymptotic method giving a probability of presence of the iterated spots of R d by a polynomial function f. We use the well-known Perron Frobenius operator (PF) that lets certain sets and measure invariant by f. Probabilistic solutions can exist for the deterministic iteration. If the theoretical result is already known, here we quantify these probabilities. This approach seems interesting to use for computing situations when the deterministic methods don't run. Among the examined applications, are asymptotic solutions of Lorenz, Navier-Stokes or Hamilton's equations. In this approach, linearity induces many difficult problems, all of whom we have not yet resolved.
Quantum probability for probabilists
Meyer, Paul-André
1993-01-01
In recent years, the classical theory of stochastic integration and stochastic differential equations has been extended to a non-commutative set-up to develop models for quantum noises. The author, a specialist of classical stochastic calculus and martingale theory, tries to provide anintroduction to this rapidly expanding field in a way which should be accessible to probabilists familiar with the Ito integral. It can also, on the other hand, provide a means of access to the methods of stochastic calculus for physicists familiar with Fock space analysis.
Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization
Voet, van der H.; Slob, W.
2007-01-01
A method is proposed for integrated probabilistic risk assessment where exposure assessment and hazard characterization are both included in a probabilistic way. The aim is to specify the probability that a random individual from a defined (sub)population will have an exposure high enough to cause a
Probabilistic Structural Analysis of SSME Turbopump Blades: Probabilistic Geometry Effects
Nagpal, V. K.
1985-01-01
A probabilistic study was initiated to evaluate the precisions of the geometric and material properties tolerances on the structural response of turbopump blades. To complete this study, a number of important probabilistic variables were identified which are conceived to affect the structural response of the blade. In addition, a methodology was developed to statistically quantify the influence of these probabilistic variables in an optimized way. The identified variables include random geometric and material properties perturbations, different loadings and a probabilistic combination of these loadings. Influences of these probabilistic variables are planned to be quantified by evaluating the blade structural response. Studies of the geometric perturbations were conducted for a flat plate geometry as well as for a space shuttle main engine blade geometry using a special purpose code which uses the finite element approach. Analyses indicate that the variances of the perturbations about given mean values have significant influence on the response.
A General Framework for Probabilistic Characterizing Formulae
DEFF Research Database (Denmark)
Sack, Joshua; Zhang, Lijun
2012-01-01
Recently, a general framework on characteristic formulae was proposed by Aceto et al. It offers a simple theory that allows one to easily obtain characteristic formulae of many non-probabilistic behavioral relations. Our paper studies their techniques in a probabilistic setting. We provide...... a general method for determining characteristic formulae of behavioral relations for probabilistic automata using fixed-point probability logics. We consider such behavioral relations as simulations and bisimulations, probabilistic bisimulations, probabilistic weak simulations, and probabilistic forward...
Probabilistic pathway construction.
Yousofshahi, Mona; Lee, Kyongbum; Hassoun, Soha
2011-07-01
Expression of novel synthesis pathways in host organisms amenable to genetic manipulations has emerged as an attractive metabolic engineering strategy to overproduce natural products, biofuels, biopolymers and other commercially useful metabolites. We present a pathway construction algorithm for identifying viable synthesis pathways compatible with balanced cell growth. Rather than exhaustive exploration, we investigate probabilistic selection of reactions to construct the pathways. Three different selection schemes are investigated for the selection of reactions: high metabolite connectivity, low connectivity and uniformly random. For all case studies, which involved a diverse set of target metabolites, the uniformly random selection scheme resulted in the highest average maximum yield. When compared to an exhaustive search enumerating all possible reaction routes, our probabilistic algorithm returned nearly identical distributions of yields, while requiring far less computing time (minutes vs. years). The pathways identified by our algorithm have previously been confirmed in the literature as viable, high-yield synthesis routes. Prospectively, our algorithm could facilitate the design of novel, non-native synthesis routes by efficiently exploring the diversity of biochemical transformations in nature. Copyright © 2011 Elsevier Inc. All rights reserved.
Probabilistic risk assessment methodology
International Nuclear Information System (INIS)
Shinaishin, M.A.
1988-06-01
The objective of this work is to provide the tools necessary for clear identification of: the purpose of a Probabilistic Risk Study, the bounds and depth of the study, the proper modeling techniques to be used, the failure modes contributing to the analysis, the classical and baysian approaches for manipulating data necessary for quantification, ways for treating uncertainties, and available computer codes that may be used in performing such probabilistic analysis. In addition, it provides the means for measuring the importance of a safety feature to maintaining a level of risk at a Nuclear Power Plant and the worth of optimizing a safety system in risk reduction. In applying these techniques so that they accommodate our national resources and needs it was felt that emphasis should be put on the system reliability analysis level of PRA. Objectives of such studies could include: comparing systems' designs of the various vendors in the bedding stage, and performing grid reliability and human performance analysis using national specific data. (author)
Probabilistic population aging
2017-01-01
We merge two methodologies, prospective measures of population aging and probabilistic population forecasts. We compare the speed of change and variability in forecasts of the old age dependency ratio and the prospective old age dependency ratio as well as the same comparison for the median age and the prospective median age. While conventional measures of population aging are computed on the basis of the number of years people have already lived, prospective measures are computed also taking account of the expected number of years they have left to live. Those remaining life expectancies change over time and differ from place to place. We compare the probabilistic distributions of the conventional and prospective measures using examples from China, Germany, Iran, and the United States. The changes over time and the variability of the prospective indicators are smaller than those that are observed in the conventional ones. A wide variety of new results emerge from the combination of methodologies. For example, for Germany, Iran, and the United States the likelihood that the prospective median age of the population in 2098 will be lower than it is today is close to 100 percent. PMID:28636675
Probabilistic cellular automata.
Agapie, Alexandru; Andreica, Anca; Giuclea, Marius
2014-09-01
Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.
Probabilistic biological network alignment.
Todor, Andrei; Dobra, Alin; Kahveci, Tamer
2013-01-01
Interactions between molecules are probabilistic events. An interaction may or may not happen with some probability, depending on a variety of factors such as the size, abundance, or proximity of the interacting molecules. In this paper, we consider the problem of aligning two biological networks. Unlike existing methods, we allow one of the two networks to contain probabilistic interactions. Allowing interaction probabilities makes the alignment more biologically relevant at the expense of explosive growth in the number of alternative topologies that may arise from different subsets of interactions that take place. We develop a novel method that efficiently and precisely characterizes this massive search space. We represent the topological similarity between pairs of aligned molecules (i.e., proteins) with the help of random variables and compute their expected values. We validate our method showing that, without sacrificing the running time performance, it can produce novel alignments. Our results also demonstrate that our method identifies biologically meaningful mappings under a comprehensive set of criteria used in the literature as well as the statistical coherence measure that we developed to analyze the statistical significance of the similarity of the functions of the aligned protein pairs.
Quantum probabilistic logic programming
Balu, Radhakrishnan
2015-05-01
We describe a quantum mechanics based logic programming language that supports Horn clauses, random variables, and covariance matrices to express and solve problems in probabilistic logic. The Horn clauses of the language wrap random variables, including infinite valued, to express probability distributions and statistical correlations, a powerful feature to capture relationship between distributions that are not independent. The expressive power of the language is based on a mechanism to implement statistical ensembles and to solve the underlying SAT instances using quantum mechanical machinery. We exploit the fact that classical random variables have quantum decompositions to build the Horn clauses. We establish the semantics of the language in a rigorous fashion by considering an existing probabilistic logic language called PRISM with classical probability measures defined on the Herbrand base and extending it to the quantum context. In the classical case H-interpretations form the sample space and probability measures defined on them lead to consistent definition of probabilities for well formed formulae. In the quantum counterpart, we define probability amplitudes on Hinterpretations facilitating the model generations and verifications via quantum mechanical superpositions and entanglements. We cast the well formed formulae of the language as quantum mechanical observables thus providing an elegant interpretation for their probabilities. We discuss several examples to combine statistical ensembles and predicates of first order logic to reason with situations involving uncertainty.
Probabilistic risk assessment methodology
Energy Technology Data Exchange (ETDEWEB)
Shinaishin, M A
1988-06-15
The objective of this work is to provide the tools necessary for clear identification of: the purpose of a Probabilistic Risk Study, the bounds and depth of the study, the proper modeling techniques to be used, the failure modes contributing to the analysis, the classical and baysian approaches for manipulating data necessary for quantification, ways for treating uncertainties, and available computer codes that may be used in performing such probabilistic analysis. In addition, it provides the means for measuring the importance of a safety feature to maintaining a level of risk at a Nuclear Power Plant and the worth of optimizing a safety system in risk reduction. In applying these techniques so that they accommodate our national resources and needs it was felt that emphasis should be put on the system reliability analysis level of PRA. Objectives of such studies could include: comparing systems' designs of the various vendors in the bedding stage, and performing grid reliability and human performance analysis using national specific data. (author)
Topics in Probabilistic Judgment Aggregation
Wang, Guanchun
2011-01-01
This dissertation is a compilation of several studies that are united by their relevance to probabilistic judgment aggregation. In the face of complex and uncertain events, panels of judges are frequently consulted to provide probabilistic forecasts, and aggregation of such estimates in groups often yield better results than could have been made…
Probabilistic studies of accident sequences
International Nuclear Information System (INIS)
Villemeur, A.; Berger, J.P.
1986-01-01
For several years, Electricite de France has carried out probabilistic assessment of accident sequences for nuclear power plants. In the framework of this program many methods were developed. As the interest in these studies was increasing and as adapted methods were developed, Electricite de France has undertaken a probabilistic safety assessment of a nuclear power plant [fr
Compression of Probabilistic XML documents
Veldman, Irma
2009-01-01
Probabilistic XML (PXML) files resulting from data integration can become extremely large, which is undesired. For XML there are several techniques available to compress the document and since probabilistic XML is in fact (a special form of) XML, it might benefit from these methods even more. In
Probabilistic Structural Analysis Theory Development
Burnside, O. H.
1985-01-01
The objective of the Probabilistic Structural Analysis Methods (PSAM) project is to develop analysis techniques and computer programs for predicting the probabilistic response of critical structural components for current and future space propulsion systems. This technology will play a central role in establishing system performance and durability. The first year's technical activity is concentrating on probabilistic finite element formulation strategy and code development. Work is also in progress to survey critical materials and space shuttle mian engine components. The probabilistic finite element computer program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) is being developed. The final probabilistic code will have, in the general case, the capability of performing nonlinear dynamic of stochastic structures. It is the goal of the approximate methods effort to increase problem solving efficiency relative to finite element methods by using energy methods to generate trial solutions which satisfy the structural boundary conditions. These approximate methods will be less computer intensive relative to the finite element approach.
Model checking optimal finite-horizon control for probabilistic gene regulatory networks.
Wei, Ou; Guo, Zonghao; Niu, Yun; Liao, Wenyuan
2017-12-14
Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. We first describe a procedure of modeling a CS-PBNp using the language provided by a widely used probabilistic model checker PRISM. We then analyze the reward-based temporal properties and the computation in probabilistic model checking; based on the analysis, we provide a method to formulate the optimal control problem as minimum reachability reward properties. Furthermore, we incorporate control and state cost information into the PRISM code of a CS-PBNp such that automated model checking a minimum reachability reward property on the code gives the solution to the optimal control problem. We conduct experiments on two examples, an apoptosis network and a WNT5A network. Preliminary experiment results show the feasibility and effectiveness of our approach. The approach based on probabilistic model checking for optimal control avoids explicit computation of large-size state transition relations associated with PBNs. It enables a natural depiction of the dynamics of gene regulatory networks, and provides a canonical form to formulate optimal control problems using temporal properties that can be automated solved by leveraging the analysis power of underlying model checking engines. This work will be helpful for further utilization of the advances in formal verification techniques in system biology.
A Probabilistic Approach to Control of Complex Systems and Its Application to Real-Time Pricing
Directory of Open Access Journals (Sweden)
Koichi Kobayashi
2014-01-01
Full Text Available Control of complex systems is one of the fundamental problems in control theory. In this paper, a control method for complex systems modeled by a probabilistic Boolean network (PBN is studied. A PBN is widely used as a model of complex systems such as gene regulatory networks. For a PBN, the structural control problem is newly formulated. In this problem, a discrete probability distribution appeared in a PBN is controlled by the continuous-valued input. For this problem, an approximate solution method using a matrix-based representation for a PBN is proposed. Then, the problem is approximated by a linear programming problem. Furthermore, the proposed method is applied to design of real-time pricing systems of electricity. Electricity conservation is achieved by appropriately determining the electricity price over time. The effectiveness of the proposed method is presented by a numerical example on real-time pricing systems.
Probabilistic escalation modelling
Energy Technology Data Exchange (ETDEWEB)
Korneliussen, G.; Eknes, M.L.; Haugen, K.; Selmer-Olsen, S. [Det Norske Veritas, Oslo (Norway)
1997-12-31
This paper describes how structural reliability methods may successfully be applied within quantitative risk assessment (QRA) as an alternative to traditional event tree analysis. The emphasis is on fire escalation in hydrocarbon production and processing facilities. This choice was made due to potential improvements over current QRA practice associated with both the probabilistic approach and more detailed modelling of the dynamics of escalating events. The physical phenomena important for the events of interest are explicitly modelled as functions of time. Uncertainties are represented through probability distributions. The uncertainty modelling enables the analysis to be simple when possible and detailed when necessary. The methodology features several advantages compared with traditional risk calculations based on event trees. (Author)
Probabilistic fracture finite elements
Liu, W. K.; Belytschko, T.; Lua, Y. J.
1991-05-01
The Probabilistic Fracture Mechanics (PFM) is a promising method for estimating the fatigue life and inspection cycles for mechanical and structural components. The Probability Finite Element Method (PFEM), which is based on second moment analysis, has proved to be a promising, practical approach to handle problems with uncertainties. As the PFEM provides a powerful computational tool to determine first and second moment of random parameters, the second moment reliability method can be easily combined with PFEM to obtain measures of the reliability of the structural system. The method is also being applied to fatigue crack growth. Uncertainties in the material properties of advanced materials such as polycrystalline alloys, ceramics, and composites are commonly observed from experimental tests. This is mainly attributed to intrinsic microcracks, which are randomly distributed as a result of the applied load and the residual stress.
Probabilistic retinal vessel segmentation
Wu, Chang-Hua; Agam, Gady
2007-03-01
Optic fundus assessment is widely used for diagnosing vascular and non-vascular pathology. Inspection of the retinal vasculature may reveal hypertension, diabetes, arteriosclerosis, cardiovascular disease and stroke. Due to various imaging conditions retinal images may be degraded. Consequently, the enhancement of such images and vessels in them is an important task with direct clinical applications. We propose a novel technique for vessel enhancement in retinal images that is capable of enhancing vessel junctions in addition to linear vessel segments. This is an extension of vessel filters we have previously developed for vessel enhancement in thoracic CT scans. The proposed approach is based on probabilistic models which can discern vessels and junctions. Evaluation shows the proposed filter is better than several known techniques and is comparable to the state of the art when evaluated on a standard dataset. A ridge-based vessel tracking process is applied on the enhanced image to demonstrate the effectiveness of the enhancement filter.
Probabilistic sensory recoding.
Jazayeri, Mehrdad
2008-08-01
A hallmark of higher brain functions is the ability to contemplate the world rather than to respond reflexively to it. To do so, the nervous system makes use of a modular architecture in which sensory representations are dissociated from areas that control actions. This flexibility however necessitates a recoding scheme that would put sensory information to use in the control of behavior. Sensory recoding faces two important challenges. First, recoding must take into account the inherent variability of sensory responses. Second, it must be flexible enough to satisfy the requirements of different perceptual goals. Recent progress in theory, psychophysics, and neurophysiology indicate that cortical circuitry might meet these challenges by evaluating sensory signals probabilistically.
Qubits and quantum Hamiltonian computing performances for operating a digital Boolean 1/2-adder
Dridi, Ghassen; Faizy Namarvar, Omid; Joachim, Christian
2018-04-01
Quantum Boolean (1 + 1) digits 1/2-adders are designed with 3 qubits for the quantum computing (Qubits) and 4 quantum states for the quantum Hamiltonian computing (QHC) approaches. Detailed analytical solutions are provided to analyse the time operation of those different 1/2-adder gates. QHC is more robust to noise than Qubits and requires about the same amount of energy for running its 1/2-adder logical operations. QHC is faster in time than Qubits but its logical output measurement takes longer.
2017-09-01
satisfying the strict avalanche criterion,” Discrete Math ., vol. 185, pp. 29–39, 1998. [2] R.C. Bose, “On some connections between the design of... Discrete Appl. Math ., vol. 149, pp. 73–86, 2005. [11] T.W. Cusick and P. Stănică, Cryptographic Boolean Functions and Applications, 2nd ed., San Diego...Stănică, “Bisecting binomial coefficients,” Discrete Appl. Math ., vol. 227, pp. 70–83, 2017. [28] T. Martinsen, W. Meidl, and P. Stănică, “Generalized
Construction of a fuzzy and all Boolean logic gates based on DNA
DEFF Research Database (Denmark)
M. Zadegan, Reza; Jepsen, Mette D E; Hildebrandt, Lasse
2015-01-01
to the operation of the six Boolean logic gates AND, NAND, OR, NOR, XOR, and XNOR. The logic gate complex is shown to work also when implemented in a three-dimensional DNA origami box structure, where it controlled the position of the lid in a closed or open position. Implementation of multiple microRNA sensitive...... DNA locks on one DNA origami box structure enabled fuzzy logical operation that allows biosensing of complex molecular signals. Integrating logic gates with DNA origami systems opens a vast avenue to applications in the fields of nanomedicine for diagnostics and therapeutics....
Variances as order parameter and complexity measure for random Boolean networks
International Nuclear Information System (INIS)
Luque, Bartolo; Ballesteros, Fernando J; Fernandez, Manuel
2005-01-01
Several order parameters have been considered to predict and characterize the transition between ordered and disordered phases in random Boolean networks, such as the Hamming distance between replicas or the stable core, which have been successfully used. In this work, we propose a natural and clear new order parameter: the temporal variance. We compute its value analytically and compare it with the results of numerical experiments. Finally, we propose a complexity measure based on the compromise between temporal and spatial variances. This new order parameter and its related complexity measure can be easily applied to other complex systems
Security analysis of boolean algebra based on Zhang-Wang digital signature scheme
International Nuclear Information System (INIS)
Zheng, Jinbin
2014-01-01
In 2005, Zhang and Wang proposed an improvement signature scheme without using one-way hash function and message redundancy. In this paper, we show that this scheme exits potential safety concerns through the analysis of boolean algebra, such as bitwise exclusive-or, and point out that mapping is not one to one between assembly instructions and machine code actually by means of the analysis of the result of the assembly program segment, and which possibly causes safety problems unknown to the software
Variances as order parameter and complexity measure for random Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Luque, Bartolo [Departamento de Matematica Aplicada y EstadIstica, Escuela Superior de Ingenieros Aeronauticos, Universidad Politecnica de Madrid, Plaza Cardenal Cisneros 3, Madrid 28040 (Spain); Ballesteros, Fernando J [Observatori Astronomic, Universitat de Valencia, Ed. Instituts d' Investigacio, Pol. La Coma s/n, E-46980 Paterna, Valencia (Spain); Fernandez, Manuel [Departamento de Matematica Aplicada y EstadIstica, Escuela Superior de Ingenieros Aeronauticos, Universidad Politecnica de Madrid, Plaza Cardenal Cisneros 3, Madrid 28040 (Spain)
2005-02-04
Several order parameters have been considered to predict and characterize the transition between ordered and disordered phases in random Boolean networks, such as the Hamming distance between replicas or the stable core, which have been successfully used. In this work, we propose a natural and clear new order parameter: the temporal variance. We compute its value analytically and compare it with the results of numerical experiments. Finally, we propose a complexity measure based on the compromise between temporal and spatial variances. This new order parameter and its related complexity measure can be easily applied to other complex systems.
Efficient Multi-Valued Bounded Model Checking for LTL over Quasi-Boolean Algebras
Andrade, Jefferson O.; Kameyama, Yukiyoshi
2012-01-01
Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In thi...
A quantum speedup in machine learning: finding an N-bit Boolean function for a classification
International Nuclear Information System (INIS)
Yoo, Seokwon; Lee, Jinhyoung; Bang, Jeongho; Lee, Changhyoup
2014-01-01
We compare quantum and classical machines designed for learning an N-bit Boolean function in order to address how a quantum system improves the machine learning behavior. The machines of the two types consist of the same number of operations and control parameters, but only the quantum machines utilize the quantum coherence naturally induced by unitary operators. We show that quantum superposition enables quantum learning that is faster than classical learning by expanding the approximate solution regions, i.e., the acceptable regions. This is also demonstrated by means of numerical simulations with a standard feedback model, namely random search, and a practical model, namely differential evolution. (paper)
Assessment of Electronic Circuits Reliability Using Boolean Truth Table Modeling Method
International Nuclear Information System (INIS)
EI-Shanshoury, A.I.
2011-01-01
This paper explores the use of Boolean Truth Table modeling Method (BTTM) in the analysis of qualitative data. It is widely used in certain fields especially in the fields of electrical and electronic engineering. Our work focuses on the evaluation of power supply circuit reliability using (BTTM) which involves systematic attempts to falsify and identify hypotheses on the basis of truth tables constructed from qualitative data. Reliability parameters such as the system's failure rates for the power supply case study are estimated. All possible state combinations (operating and failed states) of the major components in the circuit were listed and their effects on overall system were studied
Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.
Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence
2012-08-29
Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential
Strahler, Alan H.; Jupp, David L. B.
1990-01-01
Geometric-optical discrete-element mathematical models for forest canopies have been developed using the Boolean logic and models of Serra. The geometric-optical approach is considered to be particularly well suited to describing the bidirectional reflectance of forest woodland canopies, where the concentration of leaf material within crowns and the resulting between-tree gaps make plane-parallel, radiative-transfer models inappropriate. The approach leads to invertible formulations, in which the spatial and directional variance provides the means for remote estimation of tree crown size, shape, and total cover from remotedly sensed imagery.
Security analysis of boolean algebra based on Zhang-Wang digital signature scheme
Energy Technology Data Exchange (ETDEWEB)
Zheng, Jinbin, E-mail: jbzheng518@163.com [School of Mathematics and Computer Science, Long Yan University, Longyan 364012 (China)
2014-10-06
In 2005, Zhang and Wang proposed an improvement signature scheme without using one-way hash function and message redundancy. In this paper, we show that this scheme exits potential safety concerns through the analysis of boolean algebra, such as bitwise exclusive-or, and point out that mapping is not one to one between assembly instructions and machine code actually by means of the analysis of the result of the assembly program segment, and which possibly causes safety problems unknown to the software.
Li, X Y; Yang, G W; Zheng, D S; Guo, W S; Hung, W N N
2015-04-28
Genetic regulatory networks are the key to understanding biochemical systems. One condition of the genetic regulatory network under different living environments can be modeled as a synchronous Boolean network. The attractors of these Boolean networks will help biologists to identify determinant and stable factors. Existing methods identify attractors based on a random initial state or the entire state simultaneously. They cannot identify the fixed length attractors directly. The complexity of including time increases exponentially with respect to the attractor number and length of attractors. This study used the bounded model checking to quickly locate fixed length attractors. Based on the SAT solver, we propose a new algorithm for efficiently computing the fixed length attractors, which is more suitable for large Boolean networks and numerous attractors' networks. After comparison using the tool BooleNet, empirical experiments involving biochemical systems demonstrated the feasibility and efficiency of our approach.
Probabilistic brains: knowns and unknowns
Pouget, Alexandre; Beck, Jeffrey M; Ma, Wei Ji; Latham, Peter E
2015-01-01
There is strong behavioral and physiological evidence that the brain both represents probability distributions and performs probabilistic inference. Computational neuroscientists have started to shed light on how these probabilistic representations and computations might be implemented in neural circuits. One particularly appealing aspect of these theories is their generality: they can be used to model a wide range of tasks, from sensory processing to high-level cognition. To date, however, these theories have only been applied to very simple tasks. Here we discuss the challenges that will emerge as researchers start focusing their efforts on real-life computations, with a focus on probabilistic learning, structural learning and approximate inference. PMID:23955561
Probabilistic Decision Graphs - Combining Verification and AI Techniques for Probabilistic Inference
DEFF Research Database (Denmark)
Jaeger, Manfred
2004-01-01
We adopt probabilistic decision graphs developed in the field of automated verification as a tool for probabilistic model representation and inference. We show that probabilistic inference has linear time complexity in the size of the probabilistic decision graph, that the smallest probabilistic ...
Boolean logic analysis for flow regime recognition of gas–liquid horizontal flow
International Nuclear Information System (INIS)
Ramskill, Nicholas P; Wang, Mi
2011-01-01
In order to develop a flowmeter for the accurate measurement of multiphase flows, it is of the utmost importance to correctly identify the flow regime present to enable the selection of the optimal method for metering. In this study, the horizontal flow of air and water in a pipeline was studied under a multitude of conditions using electrical resistance tomography but the flow regimes that are presented in this paper have been limited to plug and bubble air–water flows. This study proposes a novel method for recognition of the prevalent flow regime using only a fraction of the data, thus rendering the analysis more efficient. By considering the average conductivity of five zones along the central axis of the tomogram, key features can be identified, thus enabling the recognition of the prevalent flow regime. Boolean logic and frequency spectrum analysis has been applied for flow regime recognition. Visualization of the flow using the reconstructed images provides a qualitative comparison between different flow regimes. Application of the Boolean logic scheme enables a quantitative comparison of the flow patterns, thus reducing the subjectivity in the identification of the prevalent flow regime
Feedback topology and XOR-dynamics in Boolean networks with varying input structure
Ciandrini, L.; Maffi, C.; Motta, A.; Bassetti, B.; Cosentino Lagomarsino, M.
2009-08-01
We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter γ . We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying γ , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.
On the number of different dynamics in Boolean networks with deterministic update schedules.
Aracena, J; Demongeot, J; Fanchon, E; Montalva, M
2013-04-01
Deterministic Boolean networks are a type of discrete dynamical systems widely used in the modeling of genetic networks. The dynamics of such systems is characterized by the local activation functions and the update schedule, i.e., the order in which the nodes are updated. In this paper, we address the problem of knowing the different dynamics of a Boolean network when the update schedule is changed. We begin by proving that the problem of the existence of a pair of update schedules with different dynamics is NP-complete. However, we show that certain structural properties of the interaction diagraph are sufficient for guaranteeing distinct dynamics of a network. In [1] the authors define equivalence classes which have the property that all the update schedules of a given class yield the same dynamics. In order to determine the dynamics associated to a network, we develop an algorithm to efficiently enumerate the above equivalence classes by selecting a representative update schedule for each class with a minimum number of blocks. Finally, we run this algorithm on the well known Arabidopsis thaliana network to determine the full spectrum of its different dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.
Feedback topology and XOR-dynamics in Boolean networks with varying input structure.
Ciandrini, L; Maffi, C; Motta, A; Bassetti, B; Cosentino Lagomarsino, M
2009-08-01
We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter gamma. We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying gamma , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.
Attractor-Based Obstructions to Growth in Homogeneous Cyclic Boolean Automata.
Khan, Bilal; Cantor, Yuri; Dombrowski, Kirk
2015-11-01
We consider a synchronous Boolean organism consisting of N cells arranged in a circle, where each cell initially takes on an independently chosen Boolean value. During the lifetime of the organism, each cell updates its own value by responding to the presence (or absence) of diversity amongst its two neighbours' values. We show that if all cells eventually take a value of 0 (irrespective of their initial values) then the organism necessarily has a cell count that is a power of 2. In addition, the converse is also proved: if the number of cells in the organism is a proper power of 2, then no matter what the initial values of the cells are, eventually all cells take on a value of 0 and then cease to change further. We argue that such an absence of structure in the dynamical properties of the organism implies a lack of adaptiveness, and so is evolutionarily disadvantageous. It follows that as the organism doubles in size (say from m to 2m) it will necessarily encounter an intermediate size that is a proper power of 2, and suffers from low adaptiveness. Finally we show, through computational experiments, that one way an organism can grow to more than twice its size and still avoid passing through intermediate sizes that lack structural dynamics, is for the organism to depart from assumptions of homogeneity at the cellular level.
Boolean network model for cancer pathways: predicting carcinogenesis and targeted therapy outcomes.
Directory of Open Access Journals (Sweden)
Herman F Fumiã
Full Text Available A Boolean dynamical system integrating the main signaling pathways involved in cancer is constructed based on the currently known protein-protein interaction network. This system exhibits stationary protein activation patterns--attractors--dependent on the cell's microenvironment. These dynamical attractors were determined through simulations and their stabilities against mutations were tested. In a higher hierarchical level, it was possible to group the network attractors into distinct cell phenotypes and determine driver mutations that promote phenotypic transitions. We find that driver nodes are not necessarily central in the network topology, but at least they are direct regulators of central components towards which converge or through which crosstalk distinct cancer signaling pathways. The predicted drivers are in agreement with those pointed out by diverse census of cancer genes recently performed for several human cancers. Furthermore, our results demonstrate that cell phenotypes can evolve towards full malignancy through distinct sequences of accumulated mutations. In particular, the network model supports routes of carcinogenesis known for some tumor types. Finally, the Boolean network model is employed to evaluate the outcome of molecularly targeted cancer therapies. The major find is that monotherapies were additive in their effects and that the association of targeted drugs is necessary for cancer eradication.
Probabilistic Open Set Recognition
Jain, Lalit Prithviraj
Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary
Probabilistic broadcasting of mixed states
International Nuclear Information System (INIS)
Li Lvjun; Li Lvzhou; Wu Lihua; Zou Xiangfu; Qiu Daowen
2009-01-01
It is well known that the non-broadcasting theorem proved by Barnum et al is a fundamental principle of quantum communication. As we are aware, optimal broadcasting (OB) is the only method to broadcast noncommuting mixed states approximately. In this paper, motivated by the probabilistic cloning of quantum states proposed by Duan and Guo, we propose a new way for broadcasting noncommuting mixed states-probabilistic broadcasting (PB), and we present a sufficient condition for PB of mixed states. To a certain extent, we generalize the probabilistic cloning theorem from pure states to mixed states, and in particular, we generalize the non-broadcasting theorem, since the case that commuting mixed states can be exactly broadcast can be thought of as a special instance of PB where the success ratio is 1. Moreover, we discuss probabilistic local broadcasting (PLB) of separable bipartite states
Evaluation of Probabilistic Disease Forecasts.
Hughes, Gareth; Burnett, Fiona J
2017-10-01
The statistical evaluation of probabilistic disease forecasts often involves calculation of metrics defined conditionally on disease status, such as sensitivity and specificity. However, for the purpose of disease management decision making, metrics defined conditionally on the result of the forecast-predictive values-are also important, although less frequently reported. In this context, the application of scoring rules in the evaluation of probabilistic disease forecasts is discussed. An index of separation with application in the evaluation of probabilistic disease forecasts, described in the clinical literature, is also considered and its relation to scoring rules illustrated. Scoring rules provide a principled basis for the evaluation of probabilistic forecasts used in plant disease management. In particular, the decomposition of scoring rules into interpretable components is an advantageous feature of their application in the evaluation of disease forecasts.
14th International Probabilistic Workshop
Taerwe, Luc; Proske, Dirk
2017-01-01
This book presents the proceedings of the 14th International Probabilistic Workshop that was held in Ghent, Belgium in December 2016. Probabilistic methods are currently of crucial importance for research and developments in the field of engineering, which face challenges presented by new materials and technologies and rapidly changing societal needs and values. Contemporary needs related to, for example, performance-based design, service-life design, life-cycle analysis, product optimization, assessment of existing structures and structural robustness give rise to new developments as well as accurate and practically applicable probabilistic and statistical engineering methods to support these developments. These proceedings are a valuable resource for anyone interested in contemporary developments in the field of probabilistic engineering applications.
Cumulative Dominance and Probabilistic Sophistication
Wakker, P.P.; Sarin, R.H.
2000-01-01
Machina & Schmeidler (Econometrica, 60, 1992) gave preference conditions for probabilistic sophistication, i.e. decision making where uncertainty can be expressed in terms of (subjective) probabilities without commitment to expected utility maximization. This note shows that simpler and more general
Probabilistic simulation of fermion paths
International Nuclear Information System (INIS)
Zhirov, O.V.
1989-01-01
Permutation symmetry of fermion path integral allows (while spin degrees of freedom are ignored) to use in its simulation any probabilistic algorithm, like Metropolis one, heat bath, etc. 6 refs., 2 tabs
Probabilistic modeling of timber structures
DEFF Research Database (Denmark)
Köhler, Jochen; Sørensen, John Dalsgaard; Faber, Michael Havbro
2007-01-01
The present paper contains a proposal for the probabilistic modeling of timber material properties. It is produced in the context of the Probabilistic Model Code (PMC) of the Joint Committee on Structural Safety (JCSS) [Joint Committee of Structural Safety. Probabilistic Model Code, Internet...... Publication: www.jcss.ethz.ch; 2001] and of the COST action E24 ‘Reliability of Timber Structures' [COST Action E 24, Reliability of timber structures. Several meetings and Publications, Internet Publication: http://www.km.fgg.uni-lj.si/coste24/coste24.htm; 2005]. The present proposal is based on discussions...... and comments from participants of the COST E24 action and the members of the JCSS. The paper contains a description of the basic reference properties for timber strength parameters and ultimate limit state equations for timber components. The recommended probabilistic model for these basic properties...
De la Sen, M.
2015-01-01
In the framework of complete probabilistic metric spaces and, in particular, in probabilistic Menger spaces, this paper investigates some relevant properties of convergence of sequences to probabilistic α-fuzzy fixed points under some types of probabilistic contractive conditions.
Directory of Open Access Journals (Sweden)
Yih-Lon Lin
2013-01-01
Full Text Available If the given Boolean function is linearly separable, a robust uncoupled cellular neural network can be designed as a maximal margin classifier. On the other hand, if the given Boolean function is linearly separable but has a small geometric margin or it is not linearly separable, a popular approach is to find a sequence of robust uncoupled cellular neural networks implementing the given Boolean function. In the past research works using this approach, the control template parameters and thresholds are restricted to assume only a given finite set of integers, and this is certainly unnecessary for the template design. In this study, we try to remove this restriction. Minterm- and maxterm-based decomposition algorithms utilizing the soft margin and maximal margin support vector classifiers are proposed to design a sequence of robust templates implementing an arbitrary Boolean function. Several illustrative examples are simulated to demonstrate the efficiency of the proposed method by comparing our results with those produced by other decomposition methods with restricted weights.
Probabilistic numerical discrimination in mice.
Berkay, Dilara; Çavdaroğlu, Bilgehan; Balcı, Fuat
2016-03-01
Previous studies showed that both human and non-human animals can discriminate between different quantities (i.e., time intervals, numerosities) with a limited level of precision due to their endogenous/representational uncertainty. In addition, other studies have shown that subjects can modulate their temporal categorization responses adaptively by incorporating information gathered regarding probabilistic contingencies into their time-based decisions. Despite the psychophysical similarities between the interval timing and nonverbal counting functions, the sensitivity of count-based decisions to probabilistic information remains an unanswered question. In the current study, we investigated whether exogenous probabilistic information can be integrated into numerosity-based judgments by mice. In the task employed in this study, reward was presented either after few (i.e., 10) or many (i.e., 20) lever presses, the last of which had to be emitted on the lever associated with the corresponding trial type. In order to investigate the effect of probabilistic information on performance in this task, we manipulated the relative frequency of different trial types across different experimental conditions. We evaluated the behavioral performance of the animals under models that differed in terms of their assumptions regarding the cost of responding (e.g., logarithmically increasing vs. no response cost). Our results showed for the first time that mice could adaptively modulate their count-based decisions based on the experienced probabilistic contingencies in directions predicted by optimality.
Probabilistic Design and Analysis Framework
Strack, William C.; Nagpal, Vinod K.
2010-01-01
PRODAF is a software package designed to aid analysts and designers in conducting probabilistic analysis of components and systems. PRODAF can integrate multiple analysis programs to ease the tedious process of conducting a complex analysis process that requires the use of multiple software packages. The work uses a commercial finite element analysis (FEA) program with modules from NESSUS to conduct a probabilistic analysis of a hypothetical turbine blade, disk, and shaft model. PRODAF applies the response surface method, at the component level, and extrapolates the component-level responses to the system level. Hypothetical components of a gas turbine engine are first deterministically modeled using FEA. Variations in selected geometrical dimensions and loading conditions are analyzed to determine the effects of the stress state within each component. Geometric variations include the cord length and height for the blade, inner radius, outer radius, and thickness, which are varied for the disk. Probabilistic analysis is carried out using developing software packages like System Uncertainty Analysis (SUA) and PRODAF. PRODAF was used with a commercial deterministic FEA program in conjunction with modules from the probabilistic analysis program, NESTEM, to perturb loads and geometries to provide a reliability and sensitivity analysis. PRODAF simplified the handling of data among the various programs involved, and will work with many commercial and opensource deterministic programs, probabilistic programs, or modules.
Probabilistic methods used in NUSS
International Nuclear Information System (INIS)
Fischer, J.; Giuliani, P.
1985-01-01
Probabilistic considerations are used implicitly or explicitly in all technical areas. In the NUSS codes and guides the two areas of design and siting are those where more use is made of these concepts. A brief review of the relevant documents in these two areas is made in this paper. It covers the documents where either probabilistic considerations are implied or where probabilistic approaches are recommended in the evaluation of situations and of events. In the siting guides the review mainly covers the area of seismic hydrological and external man-made events analysis, as well as some aspects of meteorological extreme events analysis. Probabilistic methods are recommended in the design guides but they are not made a requirement. There are several reasons for this, mainly lack of reliable data and the absence of quantitative safety limits or goals against which to judge the design analysis. As far as practical, engineering judgement should be backed up by quantitative probabilistic analysis. Examples are given and the concept of design basis as used in NUSS design guides is explained. (author)
Super-transient scaling in time-delay autonomous Boolean network motifs
Energy Technology Data Exchange (ETDEWEB)
D' Huys, Otti, E-mail: otti.dhuys@phy.duke.edu; Haynes, Nicholas D. [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Lohmann, Johannes [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Institut für Theoretische Physik, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin (Germany); Gauthier, Daniel J. [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Department of Physics, The Ohio State University, Columbus, Ohio 43210 (United States)
2016-09-15
Autonomous Boolean networks are commonly used to model the dynamics of gene regulatory networks and allow for the prediction of stable dynamical attractors. However, most models do not account for time delays along the network links and noise, which are crucial features of real biological systems. Concentrating on two paradigmatic motifs, the toggle switch and the repressilator, we develop an experimental testbed that explicitly includes both inter-node time delays and noise using digital logic elements on field-programmable gate arrays. We observe transients that last millions to billions of characteristic time scales and scale exponentially with the amount of time delays between nodes, a phenomenon known as super-transient scaling. We develop a hybrid model that includes time delays along network links and allows for stochastic variation in the delays. Using this model, we explain the observed super-transient scaling of both motifs and recreate the experimentally measured transient distributions.
Fisher information at the edge of chaos in random Boolean networks.
Wang, X Rosalind; Lizier, Joseph T; Prokopenko, Mikhail
2011-01-01
We study the order-chaos phase transition in random Boolean networks (RBNs), which have been used as models of gene regulatory networks. In particular we seek to characterize the phase diagram in information-theoretic terms, focusing on the effect of the control parameters (activity level and connectivity). Fisher information, which measures how much system dynamics can reveal about the control parameters, offers a natural interpretation of the phase diagram in RBNs. We report that this measure is maximized near the order-chaos phase transitions in RBNs, since this is the region where the system is most sensitive to its parameters. Furthermore, we use this study of RBNs to clarify the relationship between Shannon and Fisher information measures.
Quantum tests for the linearity and permutation invariance of Boolean functions
Energy Technology Data Exchange (ETDEWEB)
Hillery, Mark [Department of Physics, Hunter College of the City University of New York, 695 Park Avenue, New York, New York 10021 (United States); Andersson, Erika [SUPA, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS (United Kingdom)
2011-12-15
The goal in function property testing is to determine whether a black-box Boolean function has a certain property or is {epsilon}-far from having that property. The performance of the algorithm is judged by how many calls need to be made to the black box in order to determine, with high probability, which of the two alternatives is the case. Here we present two quantum algorithms, the first to determine whether the function is linear and the second to determine whether it is symmetric (invariant under permutations of the arguments). Both require order {epsilon}{sup -2/3} calls to the oracle, which is better than known classical algorithms. In addition, in the case of linearity testing, if the function is linear, the quantum algorithm identifies which linear function it is. The linearity test combines the Bernstein-Vazirani algorithm and amplitude amplification, while the test to determine whether a function is symmetric uses projective measurements and amplitude amplification.
The pseudo-Boolean optimization approach to form the N-version software structure
Kovalev, I. V.; Kovalev, D. I.; Zelenkov, P. V.; Voroshilova, A. A.
2015-10-01
The problem of developing an optimal structure of N-version software system presents a kind of very complex optimization problem. This causes the use of deterministic optimization methods inappropriate for solving the stated problem. In this view, exploiting heuristic strategies looks more rational. In the field of pseudo-Boolean optimization theory, the so called method of varied probabilities (MVP) has been developed to solve problems with a large dimensionality. Some additional modifications of MVP have been made to solve the problem of N-version systems design. Those algorithms take into account the discovered specific features of the objective function. The practical experiments have shown the advantage of using these algorithm modifications because of reducing a search space.
Lima, Ricardo
2016-06-16
This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. © 2016 Springer Science+Business Media New York
Lima, Ricardo; Grossmann, Ignacio E.
2016-01-01
This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. © 2016 Springer Science+Business Media New York
Directory of Open Access Journals (Sweden)
Chao Luo
Full Text Available A novel algebraic approach is proposed to study dynamics of asynchronous random Boolean networks where a random number of nodes can be updated at each time step (ARBNs. In this article, the logical equations of ARBNs are converted into the discrete-time linear representation and dynamical behaviors of systems are investigated. We provide a general formula of network transition matrices of ARBNs as well as a necessary and sufficient algebraic criterion to determine whether a group of given states compose an attractor of length[Formula: see text] in ARBNs. Consequently, algorithms are achieved to find all of the attractors and basins in ARBNs. Examples are showed to demonstrate the feasibility of the proposed scheme.
Strahler, Alan H.; Li, Xiao-Wen; Jupp, David L. B.
1991-01-01
The bidirectional radiance or reflectance of a forest or woodland can be modeled using principles of geometric optics and Boolean models for random sets in a three dimensional space. This model may be defined at two levels, the scene includes four components; sunlight and shadowed canopy, and sunlit and shadowed background. The reflectance of the scene is modeled as the sum of the reflectances of the individual components as weighted by their areal proportions in the field of view. At the leaf level, the canopy envelope is an assemblage of leaves, and thus the reflectance is a function of the areal proportions of sunlit and shadowed leaf, and sunlit and shadowed background. Because the proportions of scene components are dependent upon the directions of irradiance and exitance, the model accounts for the hotspot that is well known in leaf and tree canopies.
Programming Cell Adhesion for On-Chip Sequential Boolean Logic Functions.
Qu, Xiangmeng; Wang, Shaopeng; Ge, Zhilei; Wang, Jianbang; Yao, Guangbao; Li, Jiang; Zuo, Xiaolei; Shi, Jiye; Song, Shiping; Wang, Lihua; Li, Li; Pei, Hao; Fan, Chunhai
2017-08-02
Programmable remodelling of cell surfaces enables high-precision regulation of cell behavior. In this work, we developed in vitro constructed DNA-based chemical reaction networks (CRNs) to program on-chip cell adhesion. We found that the RGD-functionalized DNA CRNs are entirely noninvasive when interfaced with the fluidic mosaic membrane of living cells. DNA toehold with different lengths could tunably alter the release kinetics of cells, which shows rapid release in minutes with the use of a 6-base toehold. We further demonstrated the realization of Boolean logic functions by using DNA strand displacement reactions, which include multi-input and sequential cell logic gates (AND, OR, XOR, and AND-OR). This study provides a highly generic tool for self-organization of biological systems.
Recurrent-neural-network-based Boolean factor analysis and its application to word clustering.
Frolov, Alexander A; Husek, Dusan; Polyakov, Pavel Yu
2009-07-01
The objective of this paper is to introduce a neural-network-based algorithm for word clustering as an extension of the neural-network-based Boolean factor analysis algorithm (Frolov , 2007). It is shown that this extended algorithm supports even the more complex model of signals that are supposed to be related to textual documents. It is hypothesized that every topic in textual data is characterized by a set of words which coherently appear in documents dedicated to a given topic. The appearance of each word in a document is coded by the activity of a particular neuron. In accordance with the Hebbian learning rule implemented in the network, sets of coherently appearing words (treated as factors) create tightly connected groups of neurons, hence, revealing them as attractors of the network dynamics. The found factors are eliminated from the network memory by the Hebbian unlearning rule facilitating the search of other factors. Topics related to the found sets of words can be identified based on the words' semantics. To make the method complete, a special technique based on a Bayesian procedure has been developed for the following purposes: first, to provide a complete description of factors in terms of component probability, and second, to enhance the accuracy of classification of signals to determine whether it contains the factor. Since it is assumed that every word may possibly contribute to several topics, the proposed method might be related to the method of fuzzy clustering. In this paper, we show that the results of Boolean factor analysis and fuzzy clustering are not contradictory, but complementary. To demonstrate the capabilities of this attempt, the method is applied to two types of textual data on neural networks in two different languages. The obtained topics and corresponding words are at a good level of agreement despite the fact that identical topics in Russian and English conferences contain different sets of keywords.
Implications of probabilistic risk assessment
International Nuclear Information System (INIS)
Cullingford, M.C.; Shah, S.M.; Gittus, J.H.
1987-01-01
Probabilistic risk assessment (PRA) is an analytical process that quantifies the likelihoods, consequences and associated uncertainties of the potential outcomes of postulated events. Starting with planned or normal operation, probabilistic risk assessment covers a wide range of potential accidents and considers the whole plant and the interactions of systems and human actions. Probabilistic risk assessment can be applied in safety decisions in design, licensing and operation of industrial facilities, particularly nuclear power plants. The proceedings include a review of PRA procedures, methods and technical issues in treating uncertainties, operating and licensing issues and future trends. Risk assessment for specific reactor types or components and specific risks (eg aircraft crashing onto a reactor) are used to illustrate the points raised. All 52 articles are indexed separately. (U.K.)
A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors
Directory of Open Access Journals (Sweden)
Anxing Shan
2017-05-01
Full Text Available Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs. Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ-connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm.
Probabilistic coding of quantum states
International Nuclear Information System (INIS)
Grudka, Andrzej; Wojcik, Antoni; Czechlewski, Mikolaj
2006-01-01
We discuss the properties of probabilistic coding of two qubits to one qutrit and generalize the scheme to higher dimensions. We show that the protocol preserves the entanglement between the qubits to be encoded and the environment and can also be applied to mixed states. We present a protocol that enables encoding of n qudits to one qudit of dimension smaller than the Hilbert space of the original system and then allows probabilistic but error-free decoding of any subset of k qudits. We give a formula for the probability of successful decoding
Probabilistic methods in combinatorial analysis
Sachkov, Vladimir N
2014-01-01
This 1997 work explores the role of probabilistic methods for solving combinatorial problems. These methods not only provide the means of efficiently using such notions as characteristic and generating functions, the moment method and so on but also let us use the powerful technique of limit theorems. The basic objects under investigation are nonnegative matrices, partitions and mappings of finite sets, with special emphasis on permutations and graphs, and equivalence classes specified on sequences of finite length consisting of elements of partially ordered sets; these specify the probabilist
Probabilistic reasoning in data analysis.
Sirovich, Lawrence
2011-09-20
This Teaching Resource provides lecture notes, slides, and a student assignment for a lecture on probabilistic reasoning in the analysis of biological data. General probabilistic frameworks are introduced, and a number of standard probability distributions are described using simple intuitive ideas. Particular attention is focused on random arrivals that are independent of prior history (Markovian events), with an emphasis on waiting times, Poisson processes, and Poisson probability distributions. The use of these various probability distributions is applied to biomedical problems, including several classic experimental studies.
Probabilistic Modeling of Timber Structures
DEFF Research Database (Denmark)
Köhler, J.D.; Sørensen, John Dalsgaard; Faber, Michael Havbro
2005-01-01
The present paper contains a proposal for the probabilistic modeling of timber material properties. It is produced in the context of the Probabilistic Model Code (PMC) of the Joint Committee on Structural Safety (JCSS) and of the COST action E24 'Reliability of Timber Structures'. The present...... proposal is based on discussions and comments from participants of the COST E24 action and the members of the JCSS. The paper contains a description of the basic reference properties for timber strength parameters and ultimate limit state equations for components and connections. The recommended...
Convex sets in probabilistic normed spaces
International Nuclear Information System (INIS)
Aghajani, Asadollah; Nourouzi, Kourosh
2008-01-01
In this paper we obtain some results on convexity in a probabilistic normed space. We also investigate the concept of CSN-closedness and CSN-compactness in a probabilistic normed space and generalize the corresponding results of normed spaces
Confluence Reduction for Probabilistic Systems (extended version)
Timmer, Mark; Stoelinga, Mariëlle Ida Antoinette; van de Pol, Jan Cornelis
2010-01-01
This paper presents a novel technique for state space reduction of probabilistic specifications, based on a newly developed notion of confluence for probabilistic automata. We prove that this reduction preserves branching probabilistic bisimulation and can be applied on-the-fly. To support the
Probabilistic Role Models and the Guarded Fragment
DEFF Research Database (Denmark)
Jaeger, Manfred
2004-01-01
We propose a uniform semantic framework for interpreting probabilistic concept subsumption and probabilistic role quantification through statistical sampling distributions. This general semantic principle serves as the foundation for the development of a probabilistic version of the guarded fragm...... fragment of first-order logic. A characterization of equivalence in that logic in terms of bisimulations is given....
Probabilistic role models and the guarded fragment
DEFF Research Database (Denmark)
Jaeger, Manfred
2006-01-01
We propose a uniform semantic framework for interpreting probabilistic concept subsumption and probabilistic role quantification through statistical sampling distributions. This general semantic principle serves as the foundation for the development of a probabilistic version of the guarded fragm...... fragment of first-order logic. A characterization of equivalence in that logic in terms of bisimulations is given....
Making Probabilistic Relational Categories Learnable
Jung, Wookyoung; Hummel, John E.
2015-01-01
Theories of relational concept acquisition (e.g., schema induction) based on structured intersection discovery predict that relational concepts with a probabilistic (i.e., family resemblance) structure ought to be extremely difficult to learn. We report four experiments testing this prediction by investigating conditions hypothesized to facilitate…
Probabilistic inductive inference: a survey
Ambainis, Andris
2001-01-01
Inductive inference is a recursion-theoretic theory of learning, first developed by E. M. Gold (1967). This paper surveys developments in probabilistic inductive inference. We mainly focus on finite inference of recursive functions, since this simple paradigm has produced the most interesting (and most complex) results.
Probabilistic Approaches to Video Retrieval
Ianeva, Tzvetanka; Boldareva, L.; Westerveld, T.H.W.; Cornacchia, Roberto; Hiemstra, Djoerd; de Vries, A.P.
Our experiments for TRECVID 2004 further investigate the applicability of the so-called “Generative Probabilistic Models to video retrieval��?. TRECVID 2003 results demonstrated that mixture models computed from video shot sequences improve the precision of “query by examples��? results when
Probabilistic safety analysis procedures guide
International Nuclear Information System (INIS)
Papazoglou, I.A.; Bari, R.A.; Buslik, A.J.
1984-01-01
A procedures guide for the performance of probabilistic safety assessment has been prepared for interim use in the Nuclear Regulatory Commission programs. The probabilistic safety assessment studies performed are intended to produce probabilistic predictive models that can be used and extended by the utilities and by NRC to sharpen the focus of inquiries into a range of tissues affecting reactor safety. This guide addresses the determination of the probability (per year) of core damage resulting from accident initiators internal to the plant and from loss of offsite electric power. The scope includes analyses of problem-solving (cognitive) human errors, a determination of importance of the various core damage accident sequences, and an explicit treatment and display of uncertainties for the key accident sequences. Ultimately, the guide will be augmented to include the plant-specific analysis of in-plant processes (i.e., containment performance) and the risk associated with external accident initiators, as consensus is developed regarding suitable methodologies in these areas. This guide provides the structure of a probabilistic safety study to be performed, and indicates what products of the study are essential for regulatory decision making. Methodology is treated in the guide only to the extent necessary to indicate the range of methods which is acceptable; ample reference is given to alternative methodologies which may be utilized in the performance of the study
Probabilistic uniformities of uniform spaces
Energy Technology Data Exchange (ETDEWEB)
Rodriguez Lopez, J.; Romaguera, S.; Sanchis, M.
2017-07-01
The theory of metric spaces in the fuzzy context has shown to be an interesting area of study not only from a theoretical point of view but also for its applications. Nevertheless, it is usual to consider these spaces as classical topological or uniform spaces and there are not too many results about constructing fuzzy topological structures starting from a fuzzy metric. Maybe, H/{sup o}hle was the first to show how to construct a probabilistic uniformity and a Lowen uniformity from a probabilistic pseudometric /cite{Hohle78,Hohle82a}. His method can be directly translated to the context of fuzzy metrics and allows to characterize the categories of probabilistic uniform spaces or Lowen uniform spaces by means of certain families of fuzzy pseudometrics /cite{RL}. On the other hand, other different fuzzy uniformities can be constructed in a fuzzy metric space: a Hutton $[0,1]$-quasi-uniformity /cite{GGPV06}; a fuzzifiying uniformity /cite{YueShi10}, etc. The paper /cite{GGRLRo} gives a study of several methods of endowing a fuzzy pseudometric space with a probabilistic uniformity and a Hutton $[0,1]$-quasi-uniformity. In 2010, J. Guti/'errez Garc/'{/i}a, S. Romaguera and M. Sanchis /cite{GGRoSanchis10} proved that the category of uniform spaces is isomorphic to a category formed by sets endowed with a fuzzy uniform structure, i. e. a family of fuzzy pseudometrics satisfying certain conditions. We will show here that, by means of this isomorphism, we can obtain several methods to endow a uniform space with a probabilistic uniformity. Furthermore, these constructions allow to obtain a factorization of some functors introduced in /cite{GGRoSanchis10}. (Author)
A probabilistic Hu-Washizu variational principle
Liu, W. K.; Belytschko, T.; Besterfield, G. H.
1987-01-01
A Probabilistic Hu-Washizu Variational Principle (PHWVP) for the Probabilistic Finite Element Method (PFEM) is presented. This formulation is developed for both linear and nonlinear elasticity. The PHWVP allows incorporation of the probabilistic distributions for the constitutive law, compatibility condition, equilibrium, domain and boundary conditions into the PFEM. Thus, a complete probabilistic analysis can be performed where all aspects of the problem are treated as random variables and/or fields. The Hu-Washizu variational formulation is available in many conventional finite element codes thereby enabling the straightforward inclusion of the probabilistic features into present codes.
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.
2010-01-01
Roč. 73, č. 7-9 (2010), s. 1394-1404 ISSN 0925-2312 R&D Projects: GA ČR GA205/09/1079; GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean factor analysis * Hopfield neural Network * unsupervised learning * dimension reduction * data mining Subject RIV: IN - Informatics, Computer Science Impact factor: 1.429, year: 2010
Zhu, Zheng; Andresen, Juan Carlos; Janzen, Katharina; Katzgraber, Helmut G.
2013-03-01
We study the equilibrium and nonequilibrium properties of Boolean decision problems with competing interactions on scale-free graphs in a magnetic field. Previous studies at zero field have shown a remarkable equilibrium stability of Boolean variables (Ising spins) with competing interactions (spin glasses) on scale-free networks. When the exponent that describes the power-law decay of the connectivity of the network is strictly larger than 3, the system undergoes a spin-glass transition. However, when the exponent is equal to or less than 3, the glass phase is stable for all temperatures. First we perform finite-temperature Monte Carlo simulations in a field to test the robustness of the spin-glass phase and show, in agreement with analytical calculations, that the system exhibits a de Almeida-Thouless line. Furthermore, we study avalanches in the system at zero temperature to see if the system displays self-organized criticality. This would suggest that damage (avalanches) can spread across the whole system with nonzero probability, i.e., that Boolean decision problems on scale-free networks with competing interactions are fragile when not in thermal equilibrium.
Zhu, Zheng; Andresen, Juan Carlos; Moore, M. A.; Katzgraber, Helmut G.
2014-02-01
We study the equilibrium and nonequilibrium properties of Boolean decision problems with competing interactions on scale-free networks in an external bias (magnetic field). Previous studies at zero field have shown a remarkable equilibrium stability of Boolean variables (Ising spins) with competing interactions (spin glasses) on scale-free networks. When the exponent that describes the power-law decay of the connectivity of the network is strictly larger than 3, the system undergoes a spin-glass transition. However, when the exponent is equal to or less than 3, the glass phase is stable for all temperatures. First, we perform finite-temperature Monte Carlo simulations in a field to test the robustness of the spin-glass phase and show that the system has a spin-glass phase in a field, i.e., exhibits a de Almeida-Thouless line. Furthermore, we study avalanche distributions when the system is driven by a field at zero temperature to test if the system displays self-organized criticality. Numerical results suggest that avalanches (damage) can spread across the whole system with nonzero probability when the decay exponent of the interaction degree is less than or equal to 2, i.e., that Boolean decision problems on scale-free networks with competing interactions can be fragile when not in thermal equilibrium.
Probabilistic costing of transmission services
International Nuclear Information System (INIS)
Wijayatunga, P.D.C.
1992-01-01
Costing of transmission services of electrical utilities is required for transactions involving the transport of energy over a power network. The calculation of these costs based on Short Run Marginal Costing (SRMC) is preferred over other methods proposed in the literature due to its economic efficiency. In the research work discussed here, the concept of probabilistic costing of use-of-system based on SRMC which emerges as a consequence of the uncertainties in a power system is introduced using two different approaches. The first approach, based on the Monte Carlo method, generates a large number of possible system states by simulating random variables in the system using pseudo random number generators. A second approach to probabilistic use-of-system costing is proposed based on numerical convolution and multi-area representation of the transmission network. (UK)
Probabilistic Design of Wind Turbines
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Toft, H.S.
2010-01-01
Probabilistic design of wind turbines requires definition of the structural elements to be included in the probabilistic basis: e.g., blades, tower, foundation; identification of important failure modes; careful stochastic modeling of the uncertain parameters; recommendations for target reliability....... It is described how uncertainties in wind turbine design related to computational models, statistical data from test specimens, results from a few full-scale tests and from prototype wind turbines can be accounted for using the Maximum Likelihood Method and a Bayesian approach. Assessment of the optimal...... reliability level by cost-benefit optimization is illustrated by an offshore wind turbine example. Uncertainty modeling is illustrated by an example where physical, statistical and model uncertainties are estimated....
Advances in probabilistic risk analysis
International Nuclear Information System (INIS)
Hardung von Hardung, H.
1982-01-01
Probabilistic risk analysis can now look back upon almost a quarter century of intensive development. The early studies, whose methods and results are still referred to occasionally, however, only permitted rough estimates to be made of the probabilities of recognizable accident scenarios, failing to provide a method which could have served as a reference base in calculating the overall risk associated with nuclear power plants. The first truly solid attempt was the Rasmussen Study and, partly based on it, the German Risk Study. In those studies, probabilistic risk analysis has been given a much more precise basis. However, new methodologies have been developed in the meantime, which allow much more informative risk studies to be carried out. They have been found to be valuable tools for management decisions with respect to backfitting, reinforcement and risk limitation. Today they are mainly applied by specialized private consultants and have already found widespread application especially in the USA. (orig.) [de
Proposal for nanoscale cascaded plasmonic majority gates for non-Boolean computation.
Dutta, Sourav; Zografos, Odysseas; Gurunarayanan, Surya; Radu, Iuliana; Soree, Bart; Catthoor, Francky; Naeemi, Azad
2017-12-19
Surface-plasmon-polariton waves propagating at the interface between a metal and a dielectric, hold the key to future high-bandwidth, dense on-chip integrated logic circuits overcoming the diffraction limitation of photonics. While recent advances in plasmonic logic have witnessed the demonstration of basic and universal logic gates, these CMOS oriented digital logic gates cannot fully utilize the expressive power of this novel technology. Here, we aim at unraveling the true potential of plasmonics by exploiting an enhanced native functionality - the majority voter. Contrary to the state-of-the-art plasmonic logic devices, we use the phase of the wave instead of the intensity as the state or computational variable. We propose and demonstrate, via numerical simulations, a comprehensive scheme for building a nanoscale cascadable plasmonic majority logic gate along with a novel referencing scheme that can directly translate the information encoded in the amplitude and phase of the wave into electric field intensity at the output. Our MIM-based 3-input majority gate displays a highly improved overall area of only 0.636 μm 2 for a single-stage compared with previous works on plasmonic logic. The proposed device demonstrates non-Boolean computational capability and can find direct utility in highly parallel real-time signal processing applications like pattern recognition.
Damage Spreading in Spatial and Small-world Random Boolean Networks
Energy Technology Data Exchange (ETDEWEB)
Lu, Qiming [Fermilab; Teuscher, Christof [Portland State U.
2014-02-18
The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean Networks (RBNs) are commonly used a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other non-random connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the relevant component at very low connectivities ($\\bar{K} \\ll 1$) and that the critical connectivity of stability $K_s$ changes compared to random networks. At higher $\\bar{K}$, this scaling remains unchanged. We also show that the relevant component of spatially local networks scales with a power-law as the system size N increases, but with a different exponent for local and small-world networks. The scaling behaviors are obtained by finite-size scaling. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.
An Improvement to a Multi-Client Searchable Encryption Scheme for Boolean Queries.
Jiang, Han; Li, Xue; Xu, Qiuliang
2016-12-01
The migration of e-health systems to the cloud computing brings huge benefits, as same as some security risks. Searchable Encryption(SE) is a cryptography encryption scheme that can protect the confidentiality of data and utilize the encrypted data at the same time. The SE scheme proposed by Cash et al. in Crypto2013 and its follow-up work in CCS2013 are most practical SE Scheme that support Boolean queries at present. In their scheme, the data user has to generate the search tokens by the counter number one by one and interact with server repeatedly, until he meets the correct one, or goes through plenty of tokens to illustrate that there is no search result. In this paper, we make an improvement to their scheme. We allow server to send back some information and help the user to generate exact search token in the search phase. In our scheme, there are only two round interaction between server and user, and the search token has [Formula: see text] elements, where n is the keywords number in query expression, and [Formula: see text] is the minimum documents number that contains one of keyword in query expression, and the computation cost of server is [Formula: see text] modular exponentiation operation.
Efficient Multi-Valued Bounded Model Checking for LTL over Quasi-Boolean Algebras
Andrade, Jefferson O.; Kameyama, Yukiyoshi
Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In this paper, we propose a novel, efficient algorithm for multi-valued bounded model checking. A notable feature of our algorithm is that it is not based on reduction of multi-values into two-values; instead, it generates a single formula which represents multi-valuedness by a suitable encoding, and asks a standard SAT solver to check its satisfiability. Our experimental results show a significant improvement in the number of variables and clauses and also in execution time compared with the reduction-based one.
The boolean algebra with restricted variables as a tool for fault tree modularization
International Nuclear Information System (INIS)
Caldarola, L.; Wickenhaeuser, A.
1981-08-01
The number of minimal cut sets (m.c.s.) of very complex and highly interconnected fault trees can become extremely large (e.g. more than 10 7 ). In this case the usual analytical approach of dissecting the fault tree TOP variable into m.c.s. is not only computationally prohibitively expensive, but also meaningless because it does not offer any synthetic overview of system behavior. The method proposed in this paper overcomes the deficiencies of the analytical method. It is shown that, by applying boolean algebra with restricted variables (b.a.w.r.v.), the concept of fault tree modularization can be straightforwardly extended from a single gate to a set of gates. Thus, large fault trees are divided into smaller fault trees (modules), which are connected to each other according to a simple scheme. This scheme is represented by a block diagram in which each block is a module. The modules are analyzed separately by the m.c.s. method, and the results are combined according of the TOP event. The method allows the calculation of very large fault trees in a short time and offers a synthetic overview of systems behavior through the block diagram. Numerical examples are also included. Calculations have been carried out by using the computer code MUSTAMO, which is based on the theory developed in this paper. (orig.) [de
Attractor controllability of Boolean networks by flipping a subset of their nodes
Rafimanzelat, Mohammad Reza; Bahrami, Fariba
2018-04-01
The controllability analysis of Boolean networks (BNs), as models of biomolecular regulatory networks, has drawn the attention of researchers in recent years. In this paper, we aim at governing the steady-state behavior of BNs using an intervention method which can easily be applied to most real system, which can be modeled as BNs, particularly to biomolecular regulatory networks. To this end, we introduce the concept of attractor controllability of a BN by flipping a subset of its nodes, as the possibility of making a BN converge from any of its attractors to any other one, by one-time flipping members of a subset of BN nodes. Our approach is based on the algebraic state-space representation of BNs using semi-tensor product of matrices. After introducing some new matrix tools, we use them to derive necessary and sufficient conditions for the attractor controllability of BNs. A forward search algorithm is then suggested to identify the minimal perturbation set for attractor controllability of a BN. Next, a lower bound is derived for the cardinality of this set. Two new indices are also proposed for quantifying the attractor controllability of a BN and the influence of each network variable on the attractor controllability of the network and the relationship between them is revealed. Finally, we confirm the efficiency of the proposed approach by applying it to the BN models of some real biomolecular networks.
Prescribed burning impact on forest soil properties--a Fuzzy Boolean Nets approach.
Castro, Ana C Meira; Paulo Carvalho, Joao; Ribeiro, S
2011-02-01
The Portuguese northern forests are often and severely affected by wildfires during the Summer season. These occurrences significantly affect and negatively impact all ecosystems, namely soil, fauna and flora. In order to reduce the occurrences of natural wildfires, some measures to control the availability of fuel mass are regularly implemented. Those preventive actions concern mainly prescribed burnings and vegetation pruning. This work reports on the impact of a prescribed burning on several forest soil properties, namely pH, soil moisture, organic matter content and iron content, by monitoring the soil self-recovery capabilities during a one year span. The experiments were carried out in soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, Portugal, which was kept intact from prescribed burnings during a period of four years. Soil samples were collected from five plots at three different layers (0-3, 3-6 and 6-18) 1 day before prescribed fire and at regular intervals after the prescribed fire. This paper presents an approach where Fuzzy Boolean Nets (FBN) and Fuzzy reasoning are used to extract qualitative knowledge regarding the effect of prescribed fire burning on soil properties. FBN were chosen due to the scarcity on available quantitative data. The results showed that soil properties were affected by prescribed burning practice and were unable to recover their initial values after one year. Copyright © 2010 Elsevier Inc. All rights reserved.
Probabilistic risk assessment of HTGRs
International Nuclear Information System (INIS)
Fleming, K.N.; Houghton, W.J.; Hannaman, G.W.; Joksimovic, V.
1980-08-01
Probabilistic Risk Assessment methods have been applied to gas-cooled reactors for more than a decade and to HTGRs for more than six years in the programs sponsored by the US Department of Energy. Significant advancements to the development of PRA methodology in these programs are summarized as are the specific applications of the methods to HTGRs. Emphasis here is on PRA as a tool for evaluating HTGR design options. Current work and future directions are also discussed
Probabilistic methods for rotordynamics analysis
Wu, Y.-T.; Torng, T. Y.; Millwater, H. R.; Fossum, A. F.; Rheinfurth, M. H.
1991-01-01
This paper summarizes the development of the methods and a computer program to compute the probability of instability of dynamic systems that can be represented by a system of second-order ordinary linear differential equations. Two instability criteria based upon the eigenvalues or Routh-Hurwitz test functions are investigated. Computational methods based on a fast probability integration concept and an efficient adaptive importance sampling method are proposed to perform efficient probabilistic analysis. A numerical example is provided to demonstrate the methods.
Probabilistic analysis and related topics
Bharucha-Reid, A T
1983-01-01
Probabilistic Analysis and Related Topics, Volume 3 focuses on the continuity, integrability, and differentiability of random functions, including operator theory, measure theory, and functional and numerical analysis. The selection first offers information on the qualitative theory of stochastic systems and Langevin equations with multiplicative noise. Discussions focus on phase-space evolution via direct integration, phase-space evolution, linear and nonlinear systems, linearization, and generalizations. The text then ponders on the stability theory of stochastic difference systems and Marko
Probabilistic analysis and related topics
Bharucha-Reid, A T
1979-01-01
Probabilistic Analysis and Related Topics, Volume 2 focuses on the integrability, continuity, and differentiability of random functions, as well as functional analysis, measure theory, operator theory, and numerical analysis.The selection first offers information on the optimal control of stochastic systems and Gleason measures. Discussions focus on convergence of Gleason measures, random Gleason measures, orthogonally scattered Gleason measures, existence of optimal controls without feedback, random necessary conditions, and Gleason measures in tensor products. The text then elaborates on an
Probabilistic risk assessment of HTGRs
International Nuclear Information System (INIS)
Fleming, K.N.; Houghton, W.J.; Hannaman, G.W.; Joksimovic, V.
1981-01-01
Probabilistic Risk Assessment methods have been applied to gas-cooled reactors for more than a decade and to HTGRs for more than six years in the programs sponsored by the U.S. Department of Energy. Significant advancements to the development of PRA methodology in these programs are summarized as are the specific applications of the methods to HTGRs. Emphasis here is on PRA as a tool for evaluating HTGR design options. Current work and future directions are also discussed. (author)
Probabilistic finite elements for fracture mechanics
Besterfield, Glen
1988-01-01
The probabilistic finite element method (PFEM) is developed for probabilistic fracture mechanics (PFM). A finite element which has the near crack-tip singular strain embedded in the element is used. Probabilistic distributions, such as expectation, covariance and correlation stress intensity factors, are calculated for random load, random material and random crack length. The method is computationally quite efficient and can be expected to determine the probability of fracture or reliability.
Probabilistic Harmonic Modeling of Wind Power Plants
DEFF Research Database (Denmark)
Guest, Emerson; Jensen, Kim H.; Rasmussen, Tonny Wederberg
2017-01-01
A probabilistic sequence domain (SD) harmonic model of a grid-connected voltage-source converter is used to estimate harmonic emissions in a wind power plant (WPP) comprised of Type-IV wind turbines. The SD representation naturally partitioned converter generated voltage harmonics into those...... with deterministic phase and those with probabilistic phase. A case study performed on a string of ten 3MW, Type-IV wind turbines implemented in PSCAD was used to verify the probabilistic SD harmonic model. The probabilistic SD harmonic model can be employed in the planning phase of WPP projects to assess harmonic...
Students’ difficulties in probabilistic problem-solving
Arum, D. P.; Kusmayadi, T. A.; Pramudya, I.
2018-03-01
There are many errors can be identified when students solving mathematics problems, particularly in solving the probabilistic problem. This present study aims to investigate students’ difficulties in solving the probabilistic problem. It focuses on analyzing and describing students errors during solving the problem. This research used the qualitative method with case study strategy. The subjects in this research involve ten students of 9th grade that were selected by purposive sampling. Data in this research involve students’ probabilistic problem-solving result and recorded interview regarding students’ difficulties in solving the problem. Those data were analyzed descriptively using Miles and Huberman steps. The results show that students have difficulties in solving the probabilistic problem and can be divided into three categories. First difficulties relate to students’ difficulties in understanding the probabilistic problem. Second, students’ difficulties in choosing and using appropriate strategies for solving the problem. Third, students’ difficulties with the computational process in solving the problem. Based on the result seems that students still have difficulties in solving the probabilistic problem. It means that students have not able to use their knowledge and ability for responding probabilistic problem yet. Therefore, it is important for mathematics teachers to plan probabilistic learning which could optimize students probabilistic thinking ability.
Neutral space analysis for a Boolean network model of the fission yeast cell cycle network
Directory of Open Access Journals (Sweden)
Gonzalo A Ruz
2014-01-01
Full Text Available BACKGROUND: Interactions between genes and their products give rise to complex circuits known as gene regulatory networks (GRN that enable cells to process information and respond to external stimuli. Several important processes for life, depend of an accurate and context-specific regulation of gene expression, such as the cell cycle, which can be analyzed through its GRN, where deregulation can lead to cancer in animals or a directed regulation could be applied for biotechnological processes using yeast. An approach to study the robustness of GRN is through the neutral space. In this paper, we explore the neutral space of a Schizosaccharomyces pombe (fission yeast cell cycle network through an evolution strategy to generate a neutral graph, composed of Boolean regulatory networks that share the same state sequences of the fission yeast cell cycle. RESULTS: Through simulations it was found that in the generated neutral graph, the functional networks that are not in the wildtype connected component have in general a Hamming distance more than 3 with the wildtype, and more than 10 between the other disconnected functional networks. Significant differences were found between the functional networks in the connected component of the wildtype network and the rest of the network, not only at a topological level, but also at the state space level, where significant differences in the distribution of the basin of attraction for the G1 fixed point was found for deterministic updating schemes. CONCLUSIONS: In general, functional networks in the wildtype network connected component, can mutate up to no more than 3 times, then they reach a point of no return where the networks leave the connected component of the wildtype. The proposed method to construct a neutral graph is general and can be used to explore the neutral space of other biologically interesting networks, and also formulate new biological hypotheses studying the functional networks in the
Coded diffraction system in X-ray crystallography using a boolean phase coded aperture approximation
Pinilla, Samuel; Poveda, Juan; Arguello, Henry
2018-03-01
Phase retrieval is a problem present in many applications such as optics, astronomical imaging, computational biology and X-ray crystallography. Recent work has shown that the phase can be better recovered when the acquisition architecture includes a coded aperture, which modulates the signal before diffraction, such that the underlying signal is recovered from coded diffraction patterns. Moreover, this type of modulation effect, before the diffraction operation, can be obtained using a phase coded aperture, just after the sample under study. However, a practical implementation of a phase coded aperture in an X-ray application is not feasible, because it is computationally modeled as a matrix with complex entries which requires changing the phase of the diffracted beams. In fact, changing the phase implies finding a material that allows to deviate the direction of an X-ray beam, which can considerably increase the implementation costs. Hence, this paper describes a low cost coded X-ray diffraction system based on block-unblock coded apertures that enables phase reconstruction. The proposed system approximates the phase coded aperture with a block-unblock coded aperture by using the detour-phase method. Moreover, the SAXS/WAXS X-ray crystallography software was used to simulate the diffraction patterns of a real crystal structure called Rhombic Dodecahedron. Additionally, several simulations were carried out to analyze the performance of block-unblock approximations in recovering the phase, using the simulated diffraction patterns. Furthermore, the quality of the reconstructions was measured in terms of the Peak Signal to Noise Ratio (PSNR). Results show that the performance of the block-unblock phase coded apertures approximation decreases at most 12.5% compared with the phase coded apertures. Moreover, the quality of the reconstructions using the boolean approximations is up to 2.5 dB of PSNR less with respect to the phase coded aperture reconstructions.
Probabilistic Flood Defence Assessment Tools
Directory of Open Access Journals (Sweden)
Slomp Robert
2016-01-01
institutions managing flood the defences, and not by just a small number of experts in probabilistic assessment. Therefore, data management and use of software are main issues that have been covered in courses and training in 2016 and 2017. All in all, this is the largest change in the assessment of Dutch flood defences since 1996. In 1996 probabilistic techniques were first introduced to determine hydraulic boundary conditions (water levels and waves (wave height, wave period and direction for different return periods. To simplify the process, the assessment continues to consist of a three-step approach, moving from simple decision rules, to the methods for semi-probabilistic assessment, and finally to a fully probabilistic analysis to compare the strength of flood defences with the hydraulic loads. The formal assessment results are thus mainly based on the fully probabilistic analysis and the ultimate limit state of the strength of a flood defence. For complex flood defences, additional models and software were developed. The current Hydra software suite (for policy analysis, formal flood defence assessment and design will be replaced by the model Ringtoets. New stand-alone software has been developed for revetments, geotechnical analysis and slope stability of the foreshore. Design software and policy analysis software, including the Delta model, will be updated in 2018. A fully probabilistic method results in more precise assessments and more transparency in the process of assessment and reconstruction of flood defences. This is of increasing importance, as large-scale infrastructural projects in a highly urbanized environment are increasingly subject to political and societal pressure to add additional features. For this reason, it is of increasing importance to be able to determine which new feature really adds to flood protection, to quantify how much its adds to the level of flood protection and to evaluate if it is really worthwhile. Please note: The Netherlands
Aging in probabilistic safety assessment
International Nuclear Information System (INIS)
Jordan Cizelj, R.; Kozuh, M.
1995-01-01
Aging is a phenomenon, which is influencing on unavailability of all components of the plant. The influence of aging on Probabilistic Safety Assessment calculations was estimated for Electrical Power Supply System. The average increase of system unavailability due to aging of system components was estimated and components were prioritized regarding their influence on change of system unavailability and relative increase of their unavailability due to aging. After the analysis of some numerical results, the recommendation for a detailed research of aging phenomena and its influence on system availability is given. (author)
Probabilistic assessment of SGTR management
International Nuclear Information System (INIS)
Champ, M.; Cornille, Y.; Lanore, J.M.
1989-04-01
In case of steam generator tube rupture (SGTR) event, in France, the mitigation of accident relies on operator intervention, by applying a specific accidental procedure. A detailed probabilistic analysis has been conducted which required the assessment of the failure probability of the operator actions, and for that purpose it was necessary to estimate the time available for the operator to apply the adequate procedure for various sequences. The results indicate that by taking into account the delays and the existence of adequate accidental procedures, the risk is reduced to a reasonably low level
Probabilistic accident sequence recovery analysis
International Nuclear Information System (INIS)
Stutzke, Martin A.; Cooper, Susan E.
2004-01-01
Recovery analysis is a method that considers alternative strategies for preventing accidents in nuclear power plants during probabilistic risk assessment (PRA). Consideration of possible recovery actions in PRAs has been controversial, and there seems to be a widely held belief among PRA practitioners, utility staff, plant operators, and regulators that the results of recovery analysis should be skeptically viewed. This paper provides a framework for discussing recovery strategies, thus lending credibility to the process and enhancing regulatory acceptance of PRA results and conclusions. (author)
Probabilistic risk assessment: Number 219
International Nuclear Information System (INIS)
Bari, R.A.
1985-01-01
This report describes a methodology for analyzing the safety of nuclear power plants. A historical overview of plants in the US is provided, and past, present, and future nuclear safety and risk assessment are discussed. A primer on nuclear power plants is provided with a discussion of pressurized water reactors (PWR) and boiling water reactors (BWR) and their operation and containment. Probabilistic Risk Assessment (PRA), utilizing both event-tree and fault-tree analysis, is discussed as a tool in reactor safety, decision making, and communications. (FI)
Axiomatisation of fully probabilistic design
Czech Academy of Sciences Publication Activity Database
Kárný, Miroslav; Kroupa, Tomáš
2012-01-01
Roč. 186, č. 1 (2012), s. 105-113 ISSN 0020-0255 R&D Projects: GA MŠk(CZ) 2C06001; GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian decision making * Fully probabilistic design * Kullback–Leibler divergence * Unified decision making Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.643, year: 2012 http://library.utia.cas.cz/separaty/2011/AS/karny-0367271.pdf
Probabilistic Analysis of Crack Width
Directory of Open Access Journals (Sweden)
J. Marková
2000-01-01
Full Text Available Probabilistic analysis of crack width of a reinforced concrete element is based on the formulas accepted in Eurocode 2 and European Model Code 90. Obtained values of reliability index b seem to be satisfactory for the reinforced concrete slab that fulfils requirements for the crack width specified in Eurocode 2. However, the reliability of the slab seems to be insufficient when the European Model Code 90 is considered; reliability index is less than recommended value 1.5 for serviceability limit states indicated in Eurocode 1. Analysis of sensitivity factors of basic variables enables to find out variables significantly affecting the total crack width.
Probabilistic approach to EMP assessment
International Nuclear Information System (INIS)
Bevensee, R.M.; Cabayan, H.S.; Deadrick, F.J.; Martin, L.C.; Mensing, R.W.
1980-09-01
The development of nuclear EMP hardness requirements must account for uncertainties in the environment, in interaction and coupling, and in the susceptibility of subsystems and components. Typical uncertainties of the last two kinds are briefly summarized, and an assessment methodology is outlined, based on a probabilistic approach that encompasses the basic concepts of reliability. It is suggested that statements of survivability be made compatible with system reliability. Validation of the approach taken for simple antenna/circuit systems is performed with experiments and calculations that involve a Transient Electromagnetic Range, numerical antenna modeling, separate device failure data, and a failure analysis computer program
Probabilistic risk assessment, Volume I
International Nuclear Information System (INIS)
Anon.
1982-01-01
This book contains 158 papers presented at the International Topical Meeting on Probabilistic Risk Assessment held by the American Nuclear Society (ANS) and the European Nuclear Society (ENS) in Port Chester, New York in 1981. The meeting was second in a series of three. The main focus of the meeting was on the safety of light water reactors. The papers discuss safety goals and risk assessment. Quantitative safety goals, risk assessment in non-nuclear technologies, and operational experience and data base are also covered. Included is an address by Dr. Chauncey Starr
Probabilistic safety analysis using microcomputer
International Nuclear Information System (INIS)
Futuro Filho, F.L.F.; Mendes, J.E.S.; Santos, M.J.P. dos
1990-01-01
The main steps of execution of a Probabilistic Safety Assessment (PSA) are presented in this report, as the study of the system description, construction of event trees and fault trees, and the calculation of overall unavailability of the systems. It is also presented the use of microcomputer in performing some tasks, highlightning the main characteristics of a software to perform adequately the job. A sample case of fault tree construction and calculation is presented, using the PSAPACK software, distributed by the IAEA (International Atomic Energy Agency) for training purpose. (author)
Compression of Probabilistic XML Documents
Veldman, Irma; de Keijzer, Ander; van Keulen, Maurice
Database techniques to store, query and manipulate data that contains uncertainty receives increasing research interest. Such UDBMSs can be classified according to their underlying data model: relational, XML, or RDF. We focus on uncertain XML DBMS with as representative example the Probabilistic XML model (PXML) of [10,9]. The size of a PXML document is obviously a factor in performance. There are PXML-specific techniques to reduce the size, such as a push down mechanism, that produces equivalent but more compact PXML documents. It can only be applied, however, where possibilities are dependent. For normal XML documents there also exist several techniques for compressing a document. Since Probabilistic XML is (a special form of) normal XML, it might benefit from these methods even more. In this paper, we show that existing compression mechanisms can be combined with PXML-specific compression techniques. We also show that best compression rates are obtained with a combination of PXML-specific technique with a rather simple generic DAG-compression technique.
Living probabilistic safety assessment (LPSA)
International Nuclear Information System (INIS)
1999-08-01
Over the past few years many nuclear power plant organizations have performed probabilistic safety assessments (PSAs) to identify and understand key plant vulnerabilities. As a result of the availability of these PSA studies, there is a desire to use them to enhance plant safety and to operate the nuclear stations in the most efficient manner. PSA is an effective tool for this purpose as it assists plant management to target resources where the largest benefit to plant safety can be obtained. However, any PSA which is to be used in this way must have a credible and defensible basis. Thus, it is very important to have a high quality 'living PSA' accepted by the plant and the regulator. With this background in mind, the IAEA has prepared this report on Living Probabilistic Safety Assessment (LPSA) which addresses the updating, documentation, quality assurance, and management and organizational requirements for LPSA. Deficiencies in the areas addressed in this report would seriously reduce the adequacy of the LPSA as a tool to support decision making at NPPs. This report was reviewed by a working group during a Technical Committee Meeting on PSA Applications to Improve NPP Safety held in Madrid, Spain, from 23 to 27 February 1998
Software for Probabilistic Risk Reduction
Hensley, Scott; Michel, Thierry; Madsen, Soren; Chapin, Elaine; Rodriguez, Ernesto
2004-01-01
A computer program implements a methodology, denoted probabilistic risk reduction, that is intended to aid in planning the development of complex software and/or hardware systems. This methodology integrates two complementary prior methodologies: (1) that of probabilistic risk assessment and (2) a risk-based planning methodology, implemented in a prior computer program known as Defect Detection and Prevention (DDP), in which multiple requirements and the beneficial effects of risk-mitigation actions are taken into account. The present methodology and the software are able to accommodate both process knowledge (notably of the efficacy of development practices) and product knowledge (notably of the logical structure of a system, the development of which one seeks to plan). Estimates of the costs and benefits of a planned development can be derived. Functional and non-functional aspects of software can be taken into account, and trades made among them. It becomes possible to optimize the planning process in the sense that it becomes possible to select the best suite of process steps and design choices to maximize the expectation of success while remaining within budget.
Is Probabilistic Evidence a Source of Knowledge?
Friedman, Ori; Turri, John
2015-01-01
We report a series of experiments examining whether people ascribe knowledge for true beliefs based on probabilistic evidence. Participants were less likely to ascribe knowledge for beliefs based on probabilistic evidence than for beliefs based on perceptual evidence (Experiments 1 and 2A) or testimony providing causal information (Experiment 2B).…
Probabilistic Cue Combination: Less Is More
Yurovsky, Daniel; Boyer, Ty W.; Smith, Linda B.; Yu, Chen
2013-01-01
Learning about the structure of the world requires learning probabilistic relationships: rules in which cues do not predict outcomes with certainty. However, in some cases, the ability to track probabilistic relationships is a handicap, leading adults to perform non-normatively in prediction tasks. For example, in the "dilution effect,"…
Multiobjective optimal allocation problem with probabilistic non ...
African Journals Online (AJOL)
This paper considers the optimum compromise allocation in multivariate stratified sampling with non-linear objective function and probabilistic non-linear cost constraint. The probabilistic non-linear cost constraint is converted into equivalent deterministic one by using Chance Constrained programming. A numerical ...
Probabilistic reasoning with graphical security models
Kordy, Barbara; Pouly, Marc; Schweitzer, Patrick
This work provides a computational framework for meaningful probabilistic evaluation of attack–defense scenarios involving dependent actions. We combine the graphical security modeling technique of attack–defense trees with probabilistic information expressed in terms of Bayesian networks. In order
Probabilistic Geoacoustic Inversion in Complex Environments
2015-09-30
Probabilistic Geoacoustic Inversion in Complex Environments Jan Dettmer School of Earth and Ocean Sciences, University of Victoria, Victoria BC...long-range inversion methods can fail to provide sufficient resolution. For proper quantitative examination of variability, parameter uncertainty must...project aims to advance probabilistic geoacoustic inversion methods for complex ocean environments for a range of geoacoustic data types. The work is
Application of probabilistic precipitation forecasts from a ...
African Journals Online (AJOL)
2014-02-14
Feb 14, 2014 ... Application of probabilistic precipitation forecasts from a deterministic model ... aim of this paper is to investigate the increase in the lead-time of flash flood warnings of the SAFFG using probabilistic precipitation forecasts ... The procedure is applied to a real flash flood event and the ensemble-based.
Why do probabilistic finite element analysis ?
Thacker, Ben H
2008-01-01
The intention of this book is to provide an introduction to performing probabilistic finite element analysis. As a short guideline, the objective is to inform the reader of the use, benefits and issues associated with performing probabilistic finite element analysis without excessive theory or mathematical detail.
Branching bisimulation congruence for probabilistic systems
Trcka, N.; Georgievska, S.; Aldini, A.; Baier, C.
2008-01-01
The notion of branching bisimulation for the alternating model of probabilistic systems is not a congruence with respect to parallel composition. In this paper we first define another branching bisimulation in the more general model allowing consecutive probabilistic transitions, and we prove that
Probabilistic Reversible Automata and Quantum Automata
Golovkins, Marats; Kravtsev, Maksim
2002-01-01
To study relationship between quantum finite automata and probabilistic finite automata, we introduce a notion of probabilistic reversible automata (PRA, or doubly stochastic automata). We find that there is a strong relationship between different possible models of PRA and corresponding models of quantum finite automata. We also propose a classification of reversible finite 1-way automata.
Bisimulations meet PCTL equivalences for probabilistic automata
DEFF Research Database (Denmark)
Song, Lei; Zhang, Lijun; Godskesen, Jens Chr.
2013-01-01
Probabilistic automata (PAs) have been successfully applied in formal verification of concurrent and stochastic systems. Efficient model checking algorithms have been studied, where the most often used logics for expressing properties are based on probabilistic computation tree logic (PCTL) and its...
Error Discounting in Probabilistic Category Learning
Craig, Stewart; Lewandowsky, Stephan; Little, Daniel R.
2011-01-01
The assumption in some current theories of probabilistic categorization is that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report 2 probabilistic-categorization experiments in which we investigated error…
Consideration of aging in probabilistic safety assessment
International Nuclear Information System (INIS)
Titina, B.; Cepin, M.
2007-01-01
Probabilistic safety assessment is a standardised tool for assessment of safety of nuclear power plants. It is a complement to the safety analyses. Standard probabilistic models of safety equipment assume component failure rate as a constant. Ageing of systems, structures and components can theoretically be included in new age-dependent probabilistic safety assessment, which generally causes the failure rate to be a function of age. New age-dependent probabilistic safety assessment models, which offer explicit calculation of the ageing effects, are developed. Several groups of components are considered which require their unique models: e.g. operating components e.g. stand-by components. The developed models on the component level are inserted into the models of the probabilistic safety assessment in order that the ageing effects are evaluated for complete systems. The preliminary results show that the lack of necessary data for consideration of ageing causes highly uncertain models and consequently the results. (author)
Structural reliability codes for probabilistic design
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
1997-01-01
probabilistic code format has not only strong influence on the formal reliability measure, but also on the formal cost of failure to be associated if a design made to the target reliability level is considered to be optimal. In fact, the formal cost of failure can be different by several orders of size for two...... different, but by and large equally justifiable probabilistic code formats. Thus, the consequence is that a code format based on decision theoretical concepts and formulated as an extension of a probabilistic code format must specify formal values to be used as costs of failure. A principle of prudence...... is suggested for guiding the choice of the reference probabilistic code format for constant reliability. In the author's opinion there is an urgent need for establishing a standard probabilistic reliability code. This paper presents some considerations that may be debatable, but nevertheless point...
Energy Technology Data Exchange (ETDEWEB)
Oh, Kye Min [KHNP Central Research Institute, Daejeon (Korea, Republic of); Han, Sang Hoon; Park, Jin Hee; Lim, Ho Gon; Yang, Joon Yang [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of)
2017-06-15
In Korea, many nuclear power plants operate at a single site based on geographical characteristics, but the population density near the sites is higher than that in other countries. Thus, multiunit accidents are a more important consideration than in other countries and should be addressed appropriately. Currently, there are many issues related to a multiunit probabilistic safety assessment (PSA). One of them is the quantification of a multiunit PSA model. A traditional PSA uses a Boolean manipulation of the fault tree in terms of the minimal cut set. However, such methods have some limitations when rare event approximations cannot be used effectively or a very small truncation limit should be applied to identify accident sequence combinations for a multiunit site. In particular, it is well known that seismic risk in terms of core damage frequency can be overestimated because there are many events that have a high failure probability. In this study, we propose a quantification method based on a Monte Carlo approach for a multiunit PSA model. This method can consider all possible accident sequence combinations in a multiunit site and calculate a more exact value for events that have a high failure probability. An example model for six identical units at a site was also developed and quantified to confirm the applicability of the proposed method.
International Nuclear Information System (INIS)
Sen, P.; Tan, John K.G.; Spencer, David
1999-01-01
Probabilistic risk analysis (PRA) methods have been proven to be valuable in risk and reliability analysis. However, a weak link seems to exist between methods for analysing risks and those for making rational decisions. The integrated decision support system (IDSS) methodology presented in this paper attempts to address this issue in a practical manner. In consists of three phases: a PRA phase, a risk sensitivity analysis (SA) phase and an optimisation phase, which are implemented through an integrated computer software system. In the risk analysis phase the problem is analysed by the Boolean representation method (BRM), a PRA method that can deal with systems with multiple state variables and feedback loops. In the second phase the results obtained from the BRM are utilised directly to perform importance and risk SA. In the third phase, the problem is formulated as a multiple objective decision making problem in the form of multiple objective reliability optimisation. An industrial example is included. The resultant solutions of a five objective reliability optimisation are presented, on the basis of which rational decision making can be explored
Lovrics, Anna
2014-11-14
We have assembled a network of cell-fate determining transcription factors that play a key role in the specification of the ventral neuronal subtypes of the spinal cord on the basis of published transcriptional interactions. Asynchronous Boolean modelling of the network was used to compare simulation results with reported experimental observations. Such comparison highlighted the need to include additional regulatory connections in order to obtain the fixed point attractors of the model associated with the five known progenitor cell types located in the ventral spinal cord. The revised gene regulatory network reproduced previously observed cell state switches between progenitor cells observed in knock-out animal models or in experiments where the transcription factors were overexpressed. Furthermore the network predicted the inhibition of Irx3 by Nkx2.2 and this prediction was tested experimentally. Our results provide evidence for the existence of an as yet undescribed inhibitory connection which could potentially have significance beyond the ventral spinal cord. The work presented in this paper demonstrates the strength of Boolean modelling for identifying gene regulatory networks.
Probabilistic Survivability Versus Time Modeling
Joyner, James J., Sr.
2016-01-01
This presentation documents Kennedy Space Center's Independent Assessment work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer during key programmatic reviews and provided the GSDO Program with analyses of how egress time affects the likelihood of astronaut and ground worker survival during an emergency. For each assessment, a team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedy's Vehicle Assembly Building.
Probabilistic cloning with supplementary information
International Nuclear Information System (INIS)
Azuma, Koji; Shimamura, Junichi; Koashi, Masato; Imoto, Nobuyuki
2005-01-01
We consider probabilistic cloning of a state chosen from a mutually nonorthogonal set of pure states, with the help of a party holding supplementary information in the form of pure states. When the number of states is 2, we show that the best efficiency of producing m copies is always achieved by a two-step protocol in which the helping party first attempts to produce m-1 copies from the supplementary state, and if it fails, then the original state is used to produce m copies. On the other hand, when the number of states exceeds two, the best efficiency is not always achieved by such a protocol. We give examples in which the best efficiency is not achieved even if we allow any amount of one-way classical communication from the helping party
Machine learning a probabilistic perspective
Murphy, Kevin P
2012-01-01
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic method...
Probabilistic analysis of modernization options
International Nuclear Information System (INIS)
Wunderlich, W.O.; Giles, J.E.
1991-01-01
This paper reports on benefit-cost analysis for hydropower operations, a standard procedure for reaching planning decisions. Cost overruns and benefit shortfalls are also common occurrences. One reason for the difficulty of predicting future benefits and costs is that they usually cannot be represented with sufficient reliability by accurate values, because of the many uncertainties that enter the analysis through assumptions on inputs and system parameters. Therefore, ranges of variables need to be analyzed instead of single values. As a consequence, the decision criteria, such as net benefit and benefit-cost ratio, also vary over some range. A probabilistic approach will be demonstrated as a tool for assessing the reliability of the results
Probabilistic assessments of fuel performance
International Nuclear Information System (INIS)
Kelppe, S.; Ranta-Puska, K.
1998-01-01
The probabilistic Monte Carlo Method, coupled with quasi-random sampling, is applied for the fuel performance analyses. By using known distributions of fabrication parameters and real power histories with their randomly selected combinations, and by making a large number of ENIGMA code calculations, one expects to find out the state of the whole reactor fuel. Good statistics requires thousands of runs. A sample case representing VVER-440 reactor fuel indicates relatively low fuel temperatures and mainly athermal fission gas release if any. The rod internal pressure remains typically below 2.5 MPa, which leaves a large margin to the system pressure of 12 MPa Gap conductance, an essential parameter in the accident evaluations, shows no decrease from its start-of-life value. (orig.)
Probabilistic Fatigue Damage Program (FATIG)
Michalopoulos, Constantine
2012-01-01
FATIG computes fatigue damage/fatigue life using the stress rms (root mean square) value, the total number of cycles, and S-N curve parameters. The damage is computed by the following methods: (a) traditional method using Miner s rule with stress cycles determined from a Rayleigh distribution up to 3*sigma; and (b) classical fatigue damage formula involving the Gamma function, which is derived from the integral version of Miner's rule. The integration is carried out over all stress amplitudes. This software solves the problem of probabilistic fatigue damage using the integral form of the Palmgren-Miner rule. The software computes fatigue life using an approach involving all stress amplitudes, up to N*sigma, as specified by the user. It can be used in the design of structural components subjected to random dynamic loading, or by any stress analyst with minimal training for fatigue life estimates of structural components.
Probabilistic cloning of equidistant states
International Nuclear Information System (INIS)
Jimenez, O.; Roa, Luis; Delgado, A.
2010-01-01
We study the probabilistic cloning of equidistant states. These states are such that the inner product between them is a complex constant or its conjugate. Thereby, it is possible to study their cloning in a simple way. In particular, we are interested in the behavior of the cloning probability as a function of the phase of the overlap among the involved states. We show that for certain families of equidistant states Duan and Guo's cloning machine leads to cloning probabilities lower than the optimal unambiguous discrimination probability of equidistant states. We propose an alternative cloning machine whose cloning probability is higher than or equal to the optimal unambiguous discrimination probability for any family of equidistant states. Both machines achieve the same probability for equidistant states whose inner product is a positive real number.
Probabilistic safety assessment - regulatory perspective
International Nuclear Information System (INIS)
Solanki, R.B.; Paul, U.K.; Hajra, P.; Agarwal, S.K.
2002-01-01
Full text: Nuclear power plants (NPPs) have been designed, constructed and operated mainly based on deterministic safety analysis philosophy. In this approach, a substantial amount of safety margin is incorporated in the design and operational requirements. Additional margin is incorporated by applying the highest quality engineering codes, standards and practices, and the concept of defence-in-depth in design and operating procedures, by including conservative assumptions and acceptance criteria in plant response analysis of postulated initiating events (PIEs). However, as the probabilistic approach has been improved and refined over the years, it is possible for the designer, operator and regulator to get a more detailed and realistic picture of the safety importance of plant design features, operating procedures and operational practices by using probabilistic safety assessment (PSA) along with the deterministic methodology. At present, many countries including USA, UK and France are using PSA insights in their decision making along with deterministic basis. India has also made substantial progress in the development of methods for carrying out PSA. However, consensus on the use of PSA in regulatory decision-making has not been achieved yet. This paper emphasises on the requirements (e.g.,level of details, key modelling assumptions, data, modelling aspects, success criteria, sensitivity and uncertainty analysis) for improving the quality and consistency in performance and use of PSA that can facilitate meaningful use of the PSA insights in the regulatory decision-making in India. This paper also provides relevant information on international scenario and various application areas of PSA along with progress made in India. The PSA perspective presented in this paper may help in achieving consensus on the use of PSA for regulatory / utility decision-making in design and operation of NPPs
Probabilistic machine learning and artificial intelligence.
Ghahramani, Zoubin
2015-05-28
How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.
Probabilistic machine learning and artificial intelligence
Ghahramani, Zoubin
2015-05-01
How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.
Probabilistic assessment of nuclear safety and safeguards
International Nuclear Information System (INIS)
Higson, D.J.
1987-01-01
Nuclear reactor accidents and diversions of materials from the nuclear fuel cycle are perceived by many people as particularly serious threats to society. Probabilistic assessment is a rational approach to the evaluation of both threats, and may provide a basis for decisions on appropriate actions to control them. Probabilistic method have become standard tools used in the analysis of safety, but there are disagreements on the criteria to be applied when assessing the results of analysis. Probabilistic analysis and assessment of the effectiveness of nuclear material safeguards are still at an early stage of development. (author)
Integrated Deterministic-Probabilistic Safety Assessment Methodologies
Energy Technology Data Exchange (ETDEWEB)
Kudinov, P.; Vorobyev, Y.; Sanchez-Perea, M.; Queral, C.; Jimenez Varas, G.; Rebollo, M. J.; Mena, L.; Gomez-Magin, J.
2014-02-01
IDPSA (Integrated Deterministic-Probabilistic Safety Assessment) is a family of methods which use tightly coupled probabilistic and deterministic approaches to address respective sources of uncertainties, enabling Risk informed decision making in a consistent manner. The starting point of the IDPSA framework is that safety justification must be based on the coupling of deterministic (consequences) and probabilistic (frequency) considerations to address the mutual interactions between stochastic disturbances (e.g. failures of the equipment, human actions, stochastic physical phenomena) and deterministic response of the plant (i.e. transients). This paper gives a general overview of some IDPSA methods as well as some possible applications to PWR safety analyses. (Author)
A History of Probabilistic Inductive Logic Programming
Directory of Open Access Journals (Sweden)
Fabrizio eRiguzzi
2014-09-01
Full Text Available The field of Probabilistic Logic Programming (PLP has seen significant advances in the last 20 years, with many proposals for languages that combine probability with logic programming. Since the start, the problem of learning probabilistic logic programs has been the focus of much attention. Learning these programs represents a whole subfield of Inductive Logic Programming (ILP. In Probabilistic ILP (PILP two problems are considered: learning the parameters of a program given the structure (the rules and learning both the structure and the parameters. Usually structure learning systems use parameter learning as a subroutine. In this article we present an overview of PILP and discuss the main results.
PROBABILISTIC RELATIONAL MODELS OF COMPLETE IL-SEMIRINGS
Tsumagari, Norihiro
2012-01-01
This paper studies basic properties of probabilistic multirelations which are generalized the semantic domain of probabilistic systems and then provides two probabilistic models of complete IL-semirings using probabilistic multirelations. Also it is shown that these models need not be models of complete idempotentsemirings.
A convergence theory for probabilistic metric spaces | Jäger ...
African Journals Online (AJOL)
We develop a theory of probabilistic convergence spaces based on Tardiff's neighbourhood systems for probabilistic metric spaces. We show that the resulting category is a topological universe and we characterize a subcategory that is isomorphic to the category of probabilistic metric spaces. Keywords: Probabilistic metric ...
Disjunctive Probabilistic Modal Logic is Enough for Bisimilarity on Reactive Probabilistic Systems
Bernardo, Marco; Miculan, Marino
2016-01-01
Larsen and Skou characterized probabilistic bisimilarity over reactive probabilistic systems with a logic including true, negation, conjunction, and a diamond modality decorated with a probabilistic lower bound. Later on, Desharnais, Edalat, and Panangaden showed that negation is not necessary to characterize the same equivalence. In this paper, we prove that the logical characterization holds also when conjunction is replaced by disjunction, with negation still being not necessary. To this e...
On synchronous parallel computations with independent probabilistic choice
International Nuclear Information System (INIS)
Reif, J.H.
1984-01-01
This paper introduces probabilistic choice to synchronous parallel machine models; in particular parallel RAMs. The power of probabilistic choice in parallel computations is illustrate by parallelizing some known probabilistic sequential algorithms. The authors characterize the computational complexity of time, space, and processor bounded probabilistic parallel RAMs in terms of the computational complexity of probabilistic sequential RAMs. They show that parallelism uniformly speeds up time bounded probabilistic sequential RAM computations by nearly a quadratic factor. They also show that probabilistic choice can be eliminated from parallel computations by introducing nonuniformity
Probabilistic Counterfactuals: Semantics, Computation, and Applications
National Research Council Canada - National Science Library
Balke, Alexander
1997-01-01
... handled within the framework of standard probability theory. Starting with functional description of physical mechanisms, we were able to derive the standard probabilistic properties of Bayesian networks and to show: (1...
Multiobjective optimal allocation problem with probabilistic non ...
African Journals Online (AJOL)
user
The probabilistic non-linear cost constraint is converted into equivalent deterministic .... Further, in a survey the costs for enumerating a character in various strata are not known exactly, rather these are being ...... Naval Research Logistics, Vol.
Strategic Team AI Path Plans: Probabilistic Pathfinding
Directory of Open Access Journals (Sweden)
Tng C. H. John
2008-01-01
Full Text Available This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002, in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006. We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.
Probabilistic Meteorological Characterization for Turbine Loads
DEFF Research Database (Denmark)
Kelly, Mark C.; Larsen, Gunner Chr.; Dimitrov, Nikolay Krasimirov
2014-01-01
Beyond the existing, limited IEC prescription to describe fatigue loads on wind turbines, we look towards probabilistic characterization of the loads via analogous characterization of the atmospheric flow, particularly for today's "taller" turbines with rotors well above the atmospheric surface...
Probabilistic composition of preferences, theory and applications
Parracho Sant'Anna, Annibal
2015-01-01
Putting forward a unified presentation of the features and possible applications of probabilistic preferences composition, and serving as a methodology for decisions employing multiple criteria, this book maximizes reader insights into the evaluation in probabilistic terms and the development of composition approaches that do not depend on assigning weights to the criteria. With key applications in important areas of management such as failure modes, effects analysis and productivity analysis – together with explanations about the application of the concepts involved –this book makes available numerical examples of probabilistic transformation development and probabilistic composition. Useful not only as a reference source for researchers, but also in teaching classes of graduate courses in Production Engineering and Management Science, the key themes of the book will be of especial interest to researchers in the field of Operational Research.
Advanced Test Reactor probabilistic risk assessment
International Nuclear Information System (INIS)
Atkinson, S.A.; Eide, S.A.; Khericha, S.T.; Thatcher, T.A.
1993-01-01
This report discusses Level 1 probabilistic risk assessment (PRA) incorporating a full-scope external events analysis which has been completed for the Advanced Test Reactor (ATR) located at the Idaho National Engineering Laboratory
Probabilistic safety assessment for seismic events
International Nuclear Information System (INIS)
1993-10-01
This Technical Document on Probabilistic Safety Assessment for Seismic Events is mainly associated with the Safety Practice on Treatment of External Hazards in PSA and discusses in detail one specific external hazard, i.e. earthquakes
Estimating software development project size, using probabilistic ...
African Journals Online (AJOL)
Estimating software development project size, using probabilistic techniques. ... of managing the size of software development projects by Purchasers (Clients) and Vendors (Development ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT
Comparing Categorical and Probabilistic Fingerprint Evidence.
Garrett, Brandon; Mitchell, Gregory; Scurich, Nicholas
2018-04-23
Fingerprint examiners traditionally express conclusions in categorical terms, opining that impressions do or do not originate from the same source. Recently, probabilistic conclusions have been proposed, with examiners estimating the probability of a match between recovered and known prints. This study presented a nationally representative sample of jury-eligible adults with a hypothetical robbery case in which an examiner opined on the likelihood that a defendant's fingerprints matched latent fingerprints in categorical or probabilistic terms. We studied model language developed by the U.S. Defense Forensic Science Center to summarize results of statistical analysis of the similarity between prints. Participant ratings of the likelihood the defendant left prints at the crime scene and committed the crime were similar when exposed to categorical and strong probabilistic match evidence. Participants reduced these likelihoods when exposed to the weaker probabilistic evidence, but did not otherwise discriminate among the prints assigned different match probabilities. © 2018 American Academy of Forensic Sciences.
Probabilistic methods in exotic option pricing
Anderluh, J.H.M.
2007-01-01
The thesis presents three ways of calculating the Parisian option price as an illustration of probabilistic methods in exotic option pricing. Moreover options on commidities are considered and double-sided barrier options in a compound Poisson framework.
Non-unitary probabilistic quantum computing
Gingrich, Robert M.; Williams, Colin P.
2004-01-01
We present a method for designing quantum circuits that perform non-unitary quantum computations on n-qubit states probabilistically, and give analytic expressions for the success probability and fidelity.
A logic for inductive probabilistic reasoning
DEFF Research Database (Denmark)
Jaeger, Manfred
2005-01-01
Inductive probabilistic reasoning is understood as the application of inference patterns that use statistical background information to assign (subjective) probabilities to single events. The simplest such inference pattern is direct inference: from '70% of As are Bs" and "a is an A" infer...... that a is a B with probability 0.7. Direct inference is generalized by Jeffrey's rule and the principle of cross-entropy minimization. To adequately formalize inductive probabilistic reasoning is an interesting topic for artificial intelligence, as an autonomous system acting in a complex environment may have...... to base its actions on a probabilistic model of its environment, and the probabilities needed to form this model can often be obtained by combining statistical background information with particular observations made, i.e., by inductive probabilistic reasoning. In this paper a formal framework...
Do probabilistic forecasts lead to better decisions?
Directory of Open Access Journals (Sweden)
M. H. Ramos
2013-06-01
Full Text Available The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also started focusing attention on ways of communicating the probabilistic forecasts to decision-makers. Communicating probabilistic forecasts includes preparing tools and products for visualisation, but also requires understanding how decision-makers perceive and use uncertainty information in real time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision-makers. Answers were collected and analysed. In this paper, we present the results of this exercise and discuss if we indeed make better decisions on the basis of probabilistic forecasts.
Risk assessment using probabilistic standards
International Nuclear Information System (INIS)
Avila, R.
2004-01-01
A core element of risk is uncertainty represented by plural outcomes and their likelihood. No risk exists if the future outcome is uniquely known and hence guaranteed. The probability that we will die some day is equal to 1, so there would be no fatal risk if sufficiently long time frame is assumed. Equally, rain risk does not exist if there was 100% assurance of rain tomorrow, although there would be other risks induced by the rain. In a formal sense, any risk exists if, and only if, more than one outcome is expected at a future time interval. In any practical risk assessment we have to deal with uncertainties associated with the possible outcomes. One way of dealing with the uncertainties is to be conservative in the assessments. For example, we may compare the maximal exposure to a radionuclide with a conservatively chosen reference value. In this case, if the exposure is below the reference value then it is possible to assure that the risk is low. Since single values are usually compared; this approach is commonly called 'deterministic'. Its main advantage lies in the simplicity and in that it requires minimum information. However, problems arise when the reference values are actually exceeded or might be exceeded, as in the case of potential exposures, and when the costs for realizing the reference values are high. In those cases, the lack of knowledge on the degree of conservatism involved impairs a rational weighing of the risks against other interests. In this presentation we will outline an approach for dealing with uncertainties that in our opinion is more consistent. We will call it a 'fully probabilistic risk assessment'. The essence of this approach consists in measuring the risk in terms of probabilities, where the later are obtained from comparison of two probabilistic distributions, one reflecting the uncertainties in the outcomes and one reflecting the uncertainties in the reference value (standard) used for defining adverse outcomes. Our first aim
New probabilistic interest measures for association rules
Hahsler, Michael; Hornik, Kurt
2008-01-01
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for association rules. However, these measures fail to take the probabilistic properties of the mined data into account. In this paper, we start with presenting a simple probabilistic framework for transaction data which can be used to simulate transaction data when no associations are present. We use such data and a rea...
Semantics of probabilistic processes an operational approach
Deng, Yuxin
2015-01-01
This book discusses the semantic foundations of concurrent systems with nondeterministic and probabilistic behaviour. Particular attention is given to clarifying the relationship between testing and simulation semantics and characterising bisimulations from metric, logical, and algorithmic perspectives. Besides presenting recent research outcomes in probabilistic concurrency theory, the book exemplifies the use of many mathematical techniques to solve problems in computer science, which is intended to be accessible to postgraduate students in Computer Science and Mathematics. It can also be us
Probabilistic cloning of three symmetric states
International Nuclear Information System (INIS)
Jimenez, O.; Bergou, J.; Delgado, A.
2010-01-01
We study the probabilistic cloning of three symmetric states. These states are defined by a single complex quantity, the inner product among them. We show that three different probabilistic cloning machines are necessary to optimally clone all possible families of three symmetric states. We also show that the optimal cloning probability of generating M copies out of one original can be cast as the quotient between the success probability of unambiguously discriminating one and M copies of symmetric states.
Probabilistic Analysis Methods for Hybrid Ventilation
DEFF Research Database (Denmark)
Brohus, Henrik; Frier, Christian; Heiselberg, Per
This paper discusses a general approach for the application of probabilistic analysis methods in the design of ventilation systems. The aims and scope of probabilistic versus deterministic methods are addressed with special emphasis on hybrid ventilation systems. A preliminary application...... of stochastic differential equations is presented comprising a general heat balance for an arbitrary number of loads and zones in a building to determine the thermal behaviour under random conditions....
Ari, Eszter; Ittzés, Péter; Podani, János; Thi, Quynh Chi Le; Jakó, Eena
2012-04-01
Boolean analysis (or BOOL-AN; Jakó et al., 2009. BOOL-AN: A method for comparative sequence analysis and phylogenetic reconstruction. Mol. Phylogenet. Evol. 52, 887-97.), a recently developed method for sequence comparison uses the Iterative Canonical Form of Boolean functions. It considers sequence information in a way entirely different from standard phylogenetic methods (i.e. Maximum Parsimony, Maximum-Likelihood, Neighbor-Joining, and Bayesian analysis). The performance and reliability of Boolean analysis were tested and compared with the standard phylogenetic methods, using artificially evolved - simulated - nucleotide sequences and the 22 mitochondrial tRNA genes of the great apes. At the outset, we assumed that the phylogeny of Hominidae is generally well established, and the guide tree of artificial sequence evolution can also be used as a benchmark. These offer a possibility to compare and test the performance of different phylogenetic methods. Trees were reconstructed by each method from 2500 simulated sequences and 22 mitochondrial tRNA sequences. We also introduced a special re-sampling method for Boolean analysis on permuted sequence sites, the P-BOOL-AN procedure. Considering the reliability values (branch support values of consensus trees and Robinson-Foulds distances) we used for simulated sequence trees produced by different phylogenetic methods, BOOL-AN appeared as the most reliable method. Although the mitochondrial tRNA sequences of great apes are relatively short (59-75 bases long) and the ratio of their constant characters is about 75%, BOOL-AN, P-BOOL-AN and the Bayesian approach produced the same tree-topology as the established phylogeny, while the outcomes of Maximum Parsimony, Maximum-Likelihood and Neighbor-Joining methods were equivocal. We conclude that Boolean analysis is a promising alternative to existing methods of sequence comparison for phylogenetic reconstruction and congruence analysis. Copyright Â© 2012 Elsevier Inc. All
Probabilistic causality and radiogenic cancers
International Nuclear Information System (INIS)
Groeer, P.G.
1986-01-01
A review and scrutiny of the literature on probability and probabilistic causality shows that it is possible under certain assumptions to estimate the probability that a certain type of cancer diagnosed in an individual exposed to radiation prior to diagnosis was caused by this exposure. Diagnosis of this causal relationship like diagnosis of any disease - malignant or not - requires always some subjective judgments by the diagnostician. It is, therefore, illusory to believe that tables based on actuarial data can provide objective estimates of the chance that a cancer diagnosed in an individual is radiogenic. It is argued that such tables can only provide a base from which the diagnostician(s) deviate in one direction or the other according to his (their) individual (consensual) judgment. Acceptance of a physician's diagnostic judgment by patients is commonplace. Similar widespread acceptance of expert judgment by claimants in radiation compensation cases does presently not exist. Judicious use of the present radioepidemiological tables prepared by the Working Group of the National Institutes of Health or of updated future versions of similar tables may improve the situation. 20 references
Dynamical systems probabilistic risk assessment
Energy Technology Data Exchange (ETDEWEB)
Denman, Matthew R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ames, Arlo Leroy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-03-01
Probabilistic Risk Assessment (PRA) is the primary tool used to risk-inform nuclear power regulatory and licensing activities. Risk-informed regulations are intended to reduce inherent conservatism in regulatory metrics (e.g., allowable operating conditions and technical specifications) which are built into the regulatory framework by quantifying both the total risk profile as well as the change in the risk profile caused by an event or action (e.g., in-service inspection procedures or power uprates). Dynamical Systems (DS) analysis has been used to understand unintended time-dependent feedbacks in both industrial and organizational settings. In dynamical systems analysis, feedback loops can be characterized and studied as a function of time to describe the changes to the reliability of plant Structures, Systems and Components (SSCs). While DS has been used in many subject areas, some even within the PRA community, it has not been applied toward creating long-time horizon, dynamic PRAs (with time scales ranging between days and decades depending upon the analysis). Understanding slowly developing dynamic effects, such as wear-out, on SSC reliabilities may be instrumental in ensuring a safely and reliably operating nuclear fleet. Improving the estimation of a plant's continuously changing risk profile will allow for more meaningful risk insights, greater stakeholder confidence in risk insights, and increased operational flexibility.
Computing Distances between Probabilistic Automata
Directory of Open Access Journals (Sweden)
Mathieu Tracol
2011-07-01
Full Text Available We present relaxed notions of simulation and bisimulation on Probabilistic Automata (PA, that allow some error epsilon. When epsilon is zero we retrieve the usual notions of bisimulation and simulation on PAs. We give logical characterisations of these notions by choosing suitable logics which differ from the elementary ones, L with negation and L without negation, by the modal operator. Using flow networks, we show how to compute the relations in PTIME. This allows the definition of an efficiently computable non-discounted distance between the states of a PA. A natural modification of this distance is introduced, to obtain a discounted distance, which weakens the influence of long term transitions. We compare our notions of distance to others previously defined and illustrate our approach on various examples. We also show that our distance is not expansive with respect to process algebra operators. Although L without negation is a suitable logic to characterise epsilon-(bisimulation on deterministic PAs, it is not for general PAs; interestingly, we prove that it does characterise weaker notions, called a priori epsilon-(bisimulation, which we prove to be NP-difficult to decide.
Probabilistic modeling of children's handwriting
Puri, Mukta; Srihari, Sargur N.; Hanson, Lisa
2013-12-01
There is little work done in the analysis of children's handwriting, which can be useful in developing automatic evaluation systems and in quantifying handwriting individuality. We consider the statistical analysis of children's handwriting in early grades. Samples of handwriting of children in Grades 2-4 who were taught the Zaner-Bloser style were considered. The commonly occurring word "and" written in cursive style as well as hand-print were extracted from extended writing. The samples were assigned feature values by human examiners using a truthing tool. The human examiners looked at how the children constructed letter formations in their writing, looking for similarities and differences from the instructions taught in the handwriting copy book. These similarities and differences were measured using a feature space distance measure. Results indicate that the handwriting develops towards more conformity with the class characteristics of the Zaner-Bloser copybook which, with practice, is the expected result. Bayesian networks were learnt from the data to enable answering various probabilistic queries, such as determining students who may continue to produce letter formations as taught during lessons in school and determining the students who will develop a different and/or variation of the those letter formations and the number of different types of letter formations.
Probabilistic description of traffic flow
International Nuclear Information System (INIS)
Mahnke, R.; Kaupuzs, J.; Lubashevsky, I.
2005-01-01
A stochastic description of traffic flow, called probabilistic traffic flow theory, is developed. The general master equation is applied to relatively simple models to describe the formation and dissolution of traffic congestions. Our approach is mainly based on spatially homogeneous systems like periodically closed circular rings without on- and off-ramps. We consider a stochastic one-step process of growth or shrinkage of a car cluster (jam). As generalization we discuss the coexistence of several car clusters of different sizes. The basic problem is to find a physically motivated ansatz for the transition rates of the attachment and detachment of individual cars to a car cluster consistent with the empirical observations in real traffic. The emphasis is put on the analogy with first-order phase transitions and nucleation phenomena in physical systems like supersaturated vapour. The results are summarized in the flux-density relation, the so-called fundamental diagram of traffic flow, and compared with empirical data. Different regimes of traffic flow are discussed: free flow, congested mode as stop-and-go regime, and heavy viscous traffic. The traffic breakdown is studied based on the master equation as well as the Fokker-Planck approximation to calculate mean first passage times or escape rates. Generalizations are developed to allow for on-ramp effects. The calculated flux-density relation and characteristic breakdown times coincide with empirical data measured on highways. Finally, a brief summary of the stochastic cellular automata approach is given
Distribution functions of probabilistic automata
Vatan, F.
2001-01-01
Each probabilistic automaton M over an alphabet A defines a probability measure Prob sub(M) on the set of all finite and infinite words over A. We can identify a k letter alphabet A with the set {0, 1,..., k-1}, and, hence, we can consider every finite or infinite word w over A as a radix k expansion of a real number X(w) in the interval [0, 1]. This makes X(w) a random variable and the distribution function of M is defined as usual: F(x) := Prob sub(M) { w: X(w) automata in detail. Automata with continuous distribution functions are characterized. By a new, and much more easier method, it is shown that the distribution function F(x) is an analytic function if it is a polynomial. Finally, answering a question posed by D. Knuth and A. Yao, we show that a polynomial distribution function F(x) on [0, 1] can be generated by a prob abilistic automaton iff all the roots of F'(x) = 0 in this interval, if any, are rational numbers. For this, we define two dynamical systems on the set of polynomial distributions and study attracting fixed points of random composition of these two systems.
Probabilistic transport models for fusion
International Nuclear Information System (INIS)
Milligen, B.Ph. van; Carreras, B.A.; Lynch, V.E.; Sanchez, R.
2005-01-01
A generalization of diffusive (Fickian) transport is considered, in which particle motion is described by probability distributions. We design a simple model that includes a critical mechanism to switch between two transport channels, and show that it exhibits various interesting characteristics, suggesting that the ideas of probabilistic transport might provide a framework for the description of a range of unusual transport phenomena observed in fusion plasmas. The model produces power degradation and profile consistency, as well as a scaling of the confinement time with system size reminiscent of the gyro-Bohm/Bohm scalings observed in fusion plasmas, and rapid propagation of disturbances. In the present work we show how this model may also produce on-axis peaking of the profiles with off-axis fuelling. It is important to note that the fluid limit of a simple model like this, characterized by two transport channels, does not correspond to the usual (Fickian) transport models commonly used for modelling transport in fusion plasmas, and behaves in a fundamentally different way. (author)
Prospects for probabilistic safety assessment
International Nuclear Information System (INIS)
Hirschberg, S.
1992-01-01
This article provides some reflections on future developments of Probabilistic Safety Assessment (PSA) in view of the present state of the art and evaluates current trends in the use of PSA for safety management. The main emphasis is on Level 1 PSA, although Level 2 aspects are also highlighted to some extent. As a starting point, the role of PSA is outlined from a historical perspective, demonstrating the rapid expansion of the uses of PSA. In this context the wide spectrum of PSA applications and the associated benefits to the users are in focus. It should be kept in mind, however, that PSA, in spite of its merits, is not a self-standing safety tool. It complements deterministic analysis and thus improves understanding and facilitating prioritization of safety issues. Significant progress in handling PSA limitations - such as reliability data, common-cause failures, human interactions, external events, accident progression, containment performance, and source-term issues - is described. This forms a background for expected future developments of PSA. Among the most important issues on the agenda for the future are PSA scope extensions, methodological improvements and computer code advancements, and full exploitation of the potential benefits of applications to operational safety management. Many PSA uses, if properly exercised, lead to safety improvements as well as major burden reductions. The article provides, in addition, International Atomic Energy Agency (IAEA) perspective on the topics covered, as reflected in the current PSA programs of the agency. 74 refs., 6 figs., 1 tab
Loke, Desmond; Skelton, Jonathan M; Chong, Tow-Chong; Elliott, Stephen R
2016-12-21
One of the requirements for achieving faster CMOS electronics is to mitigate the unacceptably large chip areas required to steer heat away from or, more recently, toward the critical nodes of state-of-the-art devices. Thermal-guiding (TG) structures can efficiently direct heat by "meta-materials" engineering; however, some key aspects of the behavior of these systems are not fully understood. Here, we demonstrate control of the thermal-diffusion properties of TG structures by using nanometer-scale, CMOS-integrable, graphene-on-silica stacked materials through finite-element-methods simulations. It has been shown that it is possible to implement novel, controllable, thermally based Boolean-logic and spike-timing-dependent plasticity operations for advanced (neuromorphic) computing applications using such thermal-guide architectures.
Szejka, Agnes; Drossel, Barbara
2010-02-01
We study the evolution of Boolean networks as model systems for gene regulation. Inspired by biological networks, we select simultaneously for robust attractors and for the ability to respond to external inputs by changing the attractor. Mutations change the connections between the nodes and the update functions. In order to investigate the influence of the type of update functions, we perform our simulations with canalizing as well as with threshold functions. We compare the properties of the fitness landscapes that result for different versions of the selection criterion and the update functions. We find that for all studied cases the fitness landscape has a plateau with maximum fitness resulting in the fact that structurally very different networks are able to fulfill the same task and are connected by neutral paths in network (“genotype”) space. We find furthermore a connection between the attractor length and the mutational robustness, and an extremely long memory of the initial evolutionary stage.
Directory of Open Access Journals (Sweden)
Mikko Niilo-Rämä
2014-06-01
Full Text Available A novel estimator for estimating the mean length of fibres is proposed for censored data observed in square shaped windows. Instead of observing the fibre lengths, we observe the ratio between the intensity estimates of minus-sampling and plus-sampling. It is well-known that both intensity estimators are biased. In the current work, we derive the ratio of these biases as a function of the mean length assuming a Boolean line segment model with exponentially distributed lengths and uniformly distributed directions. Having the observed ratio of the intensity estimators, the inverse of the derived function is suggested as a new estimator for the mean length. For this estimator, an approximation of its variance is derived. The accuracies of the approximations are evaluated by means of simulation experiments. The novel method is compared to other methods and applied to real-world industrial data from nanocellulose crystalline.
Directory of Open Access Journals (Sweden)
Shohag Barman
Full Text Available Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately.In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods.Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network.
Orhan, A Emin; Ma, Wei Ji
2017-07-26
Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.
Fatimah, F.; Rosadi, D.; Hakim, R. B. F.
2018-03-01
In this paper, we motivate and introduce probabilistic soft sets and dual probabilistic soft sets for handling decision making problem in the presence of positive and negative parameters. We propose several types of algorithms related to this problem. Our procedures are flexible and adaptable. An example on real data is also given.
The probabilistic innovation theoretical framework
Directory of Open Access Journals (Sweden)
Chris W. Callaghan
2017-07-01
Full Text Available Background: Despite technological advances that offer new opportunities for solving societal problems in real time, knowledge management theory development has largely not kept pace with these developments. This article seeks to offer useful insights into how more effective theory development in this area could be enabled. Aim: This article suggests different streams of literature for inclusion into a theoretical framework for an emerging stream of research, termed ‘probabilistic innovation’, which seeks to develop a system of real-time research capability. The objective of this research is therefore to provide a synthesis of a range of diverse literatures, and to provide useful insights into how research enabled by crowdsourced research and development can potentially be used to address serious knowledge problems in real time. Setting: This research suggests that knowledge management theory can provide an anchor for a new stream of research contributing to the development of real-time knowledge problem solving. Methods: This conceptual article seeks to re-conceptualise the problem of real-time research and locate this knowledge problem in relation to a host of rapidly developing streams of literature. In doing so, a novel perspective of societal problem-solving is enabled. Results: An analysis of theory and literature suggests that certain rapidly developing streams of literature might more effectively contribute to societally important real-time research problem solving if these steams are united under a theoretical framework with this goal as its explicit focus. Conclusion: Although the goal of real-time research is as yet not attainable, research that contributes to its attainment may ultimately make an important contribution to society.
Use and Communication of Probabilistic Forecasts.
Raftery, Adrian E
2016-12-01
Probabilistic forecasts are becoming more and more available. How should they be used and communicated? What are the obstacles to their use in practice? I review experience with five problems where probabilistic forecasting played an important role. This leads me to identify five types of potential users: Low Stakes Users, who don't need probabilistic forecasts; General Assessors, who need an overall idea of the uncertainty in the forecast; Change Assessors, who need to know if a change is out of line with expectatations; Risk Avoiders, who wish to limit the risk of an adverse outcome; and Decision Theorists, who quantify their loss function and perform the decision-theoretic calculations. This suggests that it is important to interact with users and to consider their goals. The cognitive research tells us that calibration is important for trust in probability forecasts, and that it is important to match the verbal expression with the task. The cognitive load should be minimized, reducing the probabilistic forecast to a single percentile if appropriate. Probabilities of adverse events and percentiles of the predictive distribution of quantities of interest seem often to be the best way to summarize probabilistic forecasts. Formal decision theory has an important role, but in a limited range of applications.
Use and Communication of Probabilistic Forecasts
Raftery, Adrian E.
2015-01-01
Probabilistic forecasts are becoming more and more available. How should they be used and communicated? What are the obstacles to their use in practice? I review experience with five problems where probabilistic forecasting played an important role. This leads me to identify five types of potential users: Low Stakes Users, who don’t need probabilistic forecasts; General Assessors, who need an overall idea of the uncertainty in the forecast; Change Assessors, who need to know if a change is out of line with expectatations; Risk Avoiders, who wish to limit the risk of an adverse outcome; and Decision Theorists, who quantify their loss function and perform the decision-theoretic calculations. This suggests that it is important to interact with users and to consider their goals. The cognitive research tells us that calibration is important for trust in probability forecasts, and that it is important to match the verbal expression with the task. The cognitive load should be minimized, reducing the probabilistic forecast to a single percentile if appropriate. Probabilities of adverse events and percentiles of the predictive distribution of quantities of interest seem often to be the best way to summarize probabilistic forecasts. Formal decision theory has an important role, but in a limited range of applications. PMID:28446941
Probabilistic numerics and uncertainty in computations.
Hennig, Philipp; Osborne, Michael A; Girolami, Mark
2015-07-08
We deliver a call to arms for probabilistic numerical methods : algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.
bayesPop: Probabilistic Population Projections
Ševčíková, Hana; Raftery, Adrian E.
2016-01-01
We describe bayesPop, an R package for producing probabilistic population projections for all countries. This uses probabilistic projections of total fertility and life expectancy generated by Bayesian hierarchical models. It produces a sample from the joint posterior predictive distribution of future age- and sex-specific population counts, fertility rates and mortality rates, as well as future numbers of births and deaths. It provides graphical ways of summarizing this information, including trajectory plots and various kinds of probabilistic population pyramids. An expression language is introduced which allows the user to produce the predictive distribution of a wide variety of derived population quantities, such as the median age or the old age dependency ratio. The package produces aggregated projections for sets of countries, such as UN regions or trading blocs. The methodology has been used by the United Nations to produce their most recent official population projections for all countries, published in the World Population Prospects. PMID:28077933
Probabilistic Modeling and Visualization for Bankruptcy Prediction
DEFF Research Database (Denmark)
Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara
2017-01-01
In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful...... studies on bankruptcy detection, seldom probabilistic approaches were carried out. In this paper we assume a probabilistic point-of-view by applying Gaussian Processes (GP) in the context of bankruptcy prediction, comparing it against the Support Vector Machines (SVM) and the Logistic Regression (LR......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...
Probabilistic inversion for chicken processing lines
International Nuclear Information System (INIS)
Cooke, Roger M.; Nauta, Maarten; Havelaar, Arie H.; Fels, Ine van der
2006-01-01
We discuss an application of probabilistic inversion techniques to a model of campylobacter transmission in chicken processing lines. Such techniques are indicated when we wish to quantify a model which is new and perhaps unfamiliar to the expert community. In this case there are no measurements for estimating model parameters, and experts are typically unable to give a considered judgment. In such cases, experts are asked to quantify their uncertainty regarding variables which can be predicted by the model. The experts' distributions (after combination) are then pulled back onto the parameter space of the model, a process termed 'probabilistic inversion'. This study illustrates two such techniques, iterative proportional fitting (IPF) and PARmeter fitting for uncertain models (PARFUM). In addition, we illustrate how expert judgement on predicted observable quantities in combination with probabilistic inversion may be used for model validation and/or model criticism
Scalable group level probabilistic sparse factor analysis
DEFF Research Database (Denmark)
Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard
2017-01-01
Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...
bayesPop: Probabilistic Population Projections
Directory of Open Access Journals (Sweden)
Hana Ševčíková
2016-12-01
Full Text Available We describe bayesPop, an R package for producing probabilistic population projections for all countries. This uses probabilistic projections of total fertility and life expectancy generated by Bayesian hierarchical models. It produces a sample from the joint posterior predictive distribution of future age- and sex-specific population counts, fertility rates and mortality rates, as well as future numbers of births and deaths. It provides graphical ways of summarizing this information, including trajectory plots and various kinds of probabilistic population pyramids. An expression language is introduced which allows the user to produce the predictive distribution of a wide variety of derived population quantities, such as the median age or the old age dependency ratio. The package produces aggregated projections for sets of countries, such as UN regions or trading blocs. The methodology has been used by the United Nations to produce their most recent official population projections for all countries, published in the World Population Prospects.
Probabilistic Design of Wave Energy Devices
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Kofoed, Jens Peter; Ferreira, C.B.
2011-01-01
Wave energy has a large potential for contributing significantly to production of renewable energy. However, the wave energy sector is still not able to deliver cost competitive and reliable solutions. But the sector has already demonstrated several proofs of concepts. The design of wave energy...... devices is a new and expanding technical area where there is no tradition for probabilistic design—in fact very little full scale devices has been build to date, so it can be said that no design tradition really exists in this area. For this reason it is considered to be of great importance to develop...... and advocate for a probabilistic design approach, as it is assumed (in other areas this has been demonstrated) that this leads to more economical designs compared to designs based on deterministic methods. In the present paper a general framework for probabilistic design and reliability analysis of wave energy...
Probabilistic Learning by Rodent Grid Cells.
Cheung, Allen
2016-10-01
Mounting evidence shows mammalian brains are probabilistic computers, but the specific cells involved remain elusive. Parallel research suggests that grid cells of the mammalian hippocampal formation are fundamental to spatial cognition but their diverse response properties still defy explanation. No plausible model exists which explains stable grids in darkness for twenty minutes or longer, despite being one of the first results ever published on grid cells. Similarly, no current explanation can tie together grid fragmentation and grid rescaling, which show very different forms of flexibility in grid responses when the environment is varied. Other properties such as attractor dynamics and grid anisotropy seem to be at odds with one another unless additional properties are assumed such as a varying velocity gain. Modelling efforts have largely ignored the breadth of response patterns, while also failing to account for the disastrous effects of sensory noise during spatial learning and recall, especially in darkness. Here, published electrophysiological evidence from a range of experiments are reinterpreted using a novel probabilistic learning model, which shows that grid cell responses are accurately predicted by a probabilistic learning process. Diverse response properties of probabilistic grid cells are statistically indistinguishable from rat grid cells across key manipulations. A simple coherent set of probabilistic computations explains stable grid fields in darkness, partial grid rescaling in resized arenas, low-dimensional attractor grid cell dynamics, and grid fragmentation in hairpin mazes. The same computations also reconcile oscillatory dynamics at the single cell level with attractor dynamics at the cell ensemble level. Additionally, a clear functional role for boundary cells is proposed for spatial learning. These findings provide a parsimonious and unified explanation of grid cell function, and implicate grid cells as an accessible neuronal population
Directory of Open Access Journals (Sweden)
A. Torres Valle
2004-05-01
Full Text Available La ecuación booleana representada por los conjuntos mínimos de corte a nivel de un sistema o de todo un AnálisisProbabilista de Seguridad (APS ha sido utilizada para evaluar las configuraciones de salida de servicio de equipos durantela explotación. Ello se ha realizado a través de aplicaciones de APS para la optimización de regímenes operacionales. Laobtención de tales ecuaciones booleanas demanda de un proceso de alta complejidad matemática por lo que se requierenestudios exhaustivos, incluso para la aplicación de sus resultados. Las importantes ventajas para el mantenimiento que seobtienen de estas aplicaciones requieren el desarrollo de metodologías que acerquen estos métodos de optimización a lossistemas de gestión del mantenimiento, y faciliten su uso por un personal no especializado en los temas probabilistas. Elartículo presenta una metodología para la preparación, solución y utilización de los resultados de los árboles de fallospartiendo de esquemas tecnológicos. Este algoritmo ha sido automatizado a través del código MOSEG Win Ver 1.0.Palabras claves: Análisis probabilista de seguridad, esquemas tecnológicos, árboles de fallos, modos de fallo.____________________________________________________________________________Abstract.The Boolean equation represented by the minimal cut sets both at a system and at a Probabilistic SafetyAnalysis (PSA levels has been used to evaluate the out-of-order equipment configurations during operation.This analysis has been used during PSA applications for the optimization of facility operational states. A highmathematical complexity is usually demanded as part of the process for generating such Boolean equations.Exhaustive studies are also required even for applying their results. Given the advantages obtained from theseapplications, there is an arising need for developing methodologies that incorporate such methods into themaintenance management facilitating their use by alien
Probabilistic Damage Stability Calculations for Ships
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher
1996-01-01
The aim of these notes is to provide background material for the present probabilistic damage stability rules fro dry cargo ships.The formulas for the damage statistics are derived and shortcomings as well as possible improvements are discussed. The advantage of the definiton of fictitious...... compartments in the formulation of a computer-based general procedure for probabilistic damaged stability assessment is shown. Some comments are given on the current state of knowledge on the ship survivability in damaged conditions. Finally, problems regarding proper account of water ingress through openings...
Quantum logic networks for probabilistic teleportation
Institute of Scientific and Technical Information of China (English)
刘金明; 张永生; 等
2003-01-01
By eans of the primitive operations consisting of single-qubit gates.two-qubit controlled-not gates,Von Neuman measurement and classically controlled operations.,we construct efficient quantum logic networks for implementing probabilistic teleportation of a single qubit,a two-particle entangled state,and an N-particle entanglement.Based on the quantum networks,we show that after the partially entangled states are concentrated into maximal entanglement,the above three kinds of probabilistic teleportation are the same as the standard teleportation using the corresponding maximally entangled states as the quantum channels.
Probabilistic Durability Analysis in Advanced Engineering Design
Directory of Open Access Journals (Sweden)
A. Kudzys
2000-01-01
Full Text Available Expedience of probabilistic durability concepts and approaches in advanced engineering design of building materials, structural members and systems is considered. Target margin values of structural safety and serviceability indices are analyzed and their draft values are presented. Analytical methods of the cumulative coefficient of correlation and the limit transient action effect for calculation of reliability indices are given. Analysis can be used for probabilistic durability assessment of carrying and enclosure metal, reinforced concrete, wood, plastic, masonry both homogeneous and sandwich or composite structures and some kinds of equipments. Analysis models can be applied in other engineering fields.
Probabilistic Design of Offshore Structural Systems
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
1988-01-01
Probabilistic design of structural systems is considered in this paper. The reliability is estimated using first-order reliability methods (FORM). The design problem is formulated as the optimization problem to minimize a given cost function such that the reliability of the single elements...... satisfies given requirements or such that the systems reliability satisfies a given requirement. Based on a sensitivity analysis optimization procedures to solve the optimization problems are presented. Two of these procedures solve the system reliability-based optimization problem sequentially using quasi......-analytical derivatives. Finally an example of probabilistic design of an offshore structure is considered....
Probabilistic Design of Offshore Structural Systems
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
Probabilistic design of structural systems is considered in this paper. The reliability is estimated using first-order reliability methods (FORM). The design problem is formulated as the optimization problem to minimize a given cost function such that the reliability of the single elements...... satisfies given requirements or such that the systems reliability satisfies a given requirement. Based on a sensitivity analysis optimization procedures to solve the optimization problems are presented. Two of these procedures solve the system reliability-based optimization problem sequentially using quasi......-analytical derivatives. Finally an example of probabilistic design of an offshore structure is considered....
Documentation design for probabilistic risk assessment
International Nuclear Information System (INIS)
Parkinson, W.J.; von Herrmann, J.L.
1985-01-01
This paper describes a framework for documentation design of probabilistic risk assessment (PRA) and is based on the EPRI document NP-3470 ''Documentation Design for Probabilistic Risk Assessment''. The goals for PRA documentation are stated. Four audiences are identified which PRA documentation must satisfy, and the documentation consistent with the needs of the various audiences are discussed, i.e., the Summary Report, the Executive Summary, the Main Report, and Appendices. The authors recommend the documentation specifications discussed herein as guides rather than rigid definitions
Probabilistic calculation of dose commitment from uranium mill tailings
International Nuclear Information System (INIS)
1983-10-01
The report discusses in a general way considerations of uncertainty in relation to probabilistic modelling. An example of a probabilistic calculation applied to the behaviour of uranium mill tailings is given
Probabilistic inversion in priority setting of emerging zoonoses.
Kurowicka, D.; Bucura, C.; Cooke, R.; Havelaar, A.H.
2010-01-01
This article presents methodology of applying probabilistic inversion in combination with expert judgment in priority setting problem. Experts rank scenarios according to severity. A linear multi-criteria analysis model underlying the expert preferences is posited. Using probabilistic inversion, a
International Nuclear Information System (INIS)
Piriou, Pierre-Yves; Faure, Jean-Marc; Lesage, Jean-Jacques
2017-01-01
This paper presents a modeling framework that permits to describe in an integrated manner the structure of the critical system to analyze, by using an enriched fault tree, the dysfunctional behavior of its components, by means of Markov processes, and the reconfiguration strategies that have been planned to ensure safety and availability, with Moore machines. This framework has been developed from BDMP (Boolean logic Driven Markov Processes), a previous framework for dynamic repairable systems. First, the contribution is motivated by pinpointing the limitations of BDMP to model complex reconfiguration strategies and the failures of the control of these strategies. The syntax and semantics of GBDMP (Generalized Boolean logic Driven Markov Processes) are then formally defined; in particular, an algorithm to analyze the dynamic behavior of a GBDMP model is developed. The modeling capabilities of this framework are illustrated on three representative examples. Last, qualitative and quantitative analysis of GDBMP models highlight the benefits of the approach.
Review of the Brunswick Steam Electric Plant Probabilistic Risk Assessment
International Nuclear Information System (INIS)
Sattison, M.B.; Davis, P.R.; Satterwhite, D.G.; Gilmore, W.E.; Gregg, R.E.
1989-11-01
A review of the Brunswick Steam Electric Plant probabilistic risk Assessment was conducted with the objective of confirming the safety perspectives brought to light by the probabilistic risk assessment. The scope of the review included the entire Level I probabilistic risk assessment including external events. This is consistent with the scope of the probabilistic risk assessment. The review included an assessment of the assumptions, methods, models, and data used in the study. 47 refs., 14 figs., 15 tabs
Arbitrage and Hedging in a non probabilistic framework
Alvarez, Alexander; Ferrando, Sebastian; Olivares, Pablo
2011-01-01
The paper studies the concepts of hedging and arbitrage in a non probabilistic framework. It provides conditions for non probabilistic arbitrage based on the topological structure of the trajectory space and makes connections with the usual notion of arbitrage. Several examples illustrate the non probabilistic arbitrage as well perfect replication of options under continuous and discontinuous trajectories, the results can then be applied in probabilistic models path by path. The approach is r...
A common fixed point for operators in probabilistic normed spaces
International Nuclear Information System (INIS)
Ghaemi, M.B.; Lafuerza-Guillen, Bernardo; Razani, A.
2009-01-01
Probabilistic Metric spaces was introduced by Karl Menger. Alsina, Schweizer and Sklar gave a general definition of probabilistic normed space based on the definition of Menger [Alsina C, Schweizer B, Sklar A. On the definition of a probabilistic normed spaces. Aequationes Math 1993;46:91-8]. Here, we consider the equicontinuity of a class of linear operators in probabilistic normed spaces and finally, a common fixed point theorem is proved. Application to quantum Mechanic is considered.
Chikalov, Igor
2011-04-02
Hydrogen bonds (H-bonds) play a key role in both the formation and stabilization of protein structures. H-bonds involving atoms from residues that are close to each other in the main-chain sequence stabilize secondary structure elements. H-bonds between atoms from distant residues stabilize a protein’s tertiary structure. However, H-bonds greatly vary in stability. They form and break while a protein deforms. For instance, the transition of a protein from a nonfunctional to a functional state may require some H-bonds to break and others to form. The intrinsic strength of an individual H-bond has been studied from an energetic viewpoint, but energy alone may not be a very good predictor. Other local interactions may reinforce (or weaken) an H-bond. This paper describes inductive learning methods to train a protein-independent probabilistic model of H-bond stability from molecular dynamics (MD) simulation trajectories. The training data describes H-bond occurrences at successive times along these trajectories by the values of attributes called predictors. A trained model is constructed in the form of a regression tree in which each non-leaf node is a Boolean test (split) on a predictor. Each occurrence of an H-bond maps to a path in this tree from the root to a leaf node. Its predicted stability is associated with the leaf node. Experimental results demonstrate that such models can predict H-bond stability quite well. In particular, their performance is roughly 20% better than that of models based on H-bond energy alone. In addition, they can accurately identify a large fraction of the least stable H-bonds in a given conformation. The paper discusses several extensions that may yield further improvements.
International Nuclear Information System (INIS)
Vilaragut Llanes, J.J.; Ferro Fernandez, R.; Rodriguez Marti, M.; Ramirez, M.L.; Perez Mulas, A.; Barrientos Montero, M.; Ortiz Lopez, P.; Somoano, F.; Delgado Rodriguez, J.M.; Papadopulos, S.B.; Pereira, P.P. Jr.; Lopez Morones, R.; Larrinaga Cortinai, E.; Rivero Oliva, J.J.; Alemany, J.
2008-01-01
This paper presents the results of the Probabilistic Safety Assessment (PSA) to the radiotherapy treatment process with an Electron Linear Accelerator (LINAC) for Medical Uses, which was conducted in the framework of the Extra budgetary Programme on Nuclear and Radiological Safety in Iberian-America. The PSA tools were used to evaluate occupational, public and medical exposures during treatment. The study focused on the radiological protection of patients. Equipment Failure Modes and Human Errors were evaluated for each system and treatment phase by FMEA. It was aimed at obtaining an exhaustive list of deviations with a reasonable probability of occurrence and which might produce significant adverse outcomes. Separate events trees were constructed for each initiating event group. Each event tree had a different structure since the initiating events were grouped according to mitigation requirements. Fault tree models were constructed for each top event. The fault trees were developed up to the level of components. In addition to hardware faults, the fault trees included human errors associated with the response to accidents, and human errors associated with the treatment. Each accident sequence was quantified. The combination of the initiating event and top events through one fault tree was the method used to analyse the accident sequences. After combining the appropriate models, a Boolean reduction was conducted by computer software to produce sequence cut sets. Several findings were analysed concerning the treatment process and the study proposed safety recommendations to avoid them. (author)
Delineating probabilistic species pools in ecology and biogeography
Karger, Dirk Nikolaus; Cord, Anna F; Kessler, Michael; Kreft, Holger; Kühn, Ingolf; Pompe, Sven; Sandel, Brody; Sarmento Cabral, Juliano; Smith, Adam B; Svenning, Jens-Christian; Tuomisto, Hanna; Weigelt, Patrick; Wesche, Karsten
2016-01-01
Aim To provide a mechanistic and probabilistic framework for defining the species pool based on species-specific probabilities of dispersal, environmental suitability and biotic interactions within a specific temporal extent, and to show how probabilistic species pools can help disentangle the geographical structure of different community assembly processes. Innovation Probabilistic species pools provide an improved species pool definition based on probabilities in conjuncti...
Probabilistic analysis of tokamak plasma disruptions
International Nuclear Information System (INIS)
Sanzo, D.L.; Apostolakis, G.E.
1985-01-01
An approximate analytical solution to the heat conduction equations used in modeling component melting and vaporization resulting from plasma disruptions is presented. This solution is then used to propagate uncertainties in the input data characterizing disruptions, namely, energy density and disruption time, to obtain a probabilistic description of the output variables of interest, material melted and vaporized. (orig.)
Strong Ideal Convergence in Probabilistic Metric Spaces
Indian Academy of Sciences (India)
In the present paper we introduce the concepts of strongly ideal convergent sequence and strong ideal Cauchy sequence in a probabilistic metric (PM) space endowed with the strong topology, and establish some basic facts. Next, we define the strong ideal limit points and the strong ideal cluster points of a sequence in this ...
Quantum Probabilistic Dyadic Second-Order Logic
Baltag, A.; Bergfeld, J.M.; Kishida, K.; Sack, J.; Smets, S.J.L.; Zhong, S.; Libkin, L.; Kohlenbach, U.; de Queiroz, R.
2013-01-01
We propose an expressive but decidable logic for reasoning about quantum systems. The logic is endowed with tensor operators to capture properties of composite systems, and with probabilistic predication formulas P ≥ r (s), saying that a quantum system in state s will yield the answer ‘yes’ (i.e.
Probabilistic analysis of a materially nonlinear structure
Millwater, H. R.; Wu, Y.-T.; Fossum, A. F.
1990-01-01
A probabilistic finite element program is used to perform probabilistic analysis of a materially nonlinear structure. The program used in this study is NESSUS (Numerical Evaluation of Stochastic Structure Under Stress), under development at Southwest Research Institute. The cumulative distribution function (CDF) of the radial stress of a thick-walled cylinder under internal pressure is computed and compared with the analytical solution. In addition, sensitivity factors showing the relative importance of the input random variables are calculated. Significant plasticity is present in this problem and has a pronounced effect on the probabilistic results. The random input variables are the material yield stress and internal pressure with Weibull and normal distributions, respectively. The results verify the ability of NESSUS to compute the CDF and sensitivity factors of a materially nonlinear structure. In addition, the ability of the Advanced Mean Value (AMV) procedure to assess the probabilistic behavior of structures which exhibit a highly nonlinear response is shown. Thus, the AMV procedure can be applied with confidence to other structures which exhibit nonlinear behavior.
Probabilistic Programming : A True Verification Challenge
Katoen, Joost P.; Finkbeiner, Bernd; Pu, Geguang; Zhang, Lijun
2015-01-01
Probabilistic programs [6] are sequential programs, written in languages like C, Java, Scala, or ML, with two added constructs: (1) the ability to draw values at random from probability distributions, and (2) the ability to condition values of variables in a program through observations. For a
Probabilistic calculation for angular dependence collision
International Nuclear Information System (INIS)
Villarino, E.A.
1990-01-01
This collision probabilistic method is broadly used in cylindrical geometry (in one- or two-dimensions). It constitutes a powerful tool for the heterogeneous Response Method where, the coupling current is of the cosine type, that is, without angular dependence at azimuthal angle θ and proportional to μ (cosine of the θ polar angle). (Author) [es
Probabilistic safety assessment in radioactive waste disposal
International Nuclear Information System (INIS)
Robinson, P.C.
1987-07-01
Probabilistic safety assessment codes are now widely used in radioactive waste disposal assessments. This report gives an overview of the current state of the field. The relationship between the codes and the regulations covering radioactive waste disposal is discussed and the characteristics of current codes is described. The problems of verification and validation are considered. (author)
Ignorability in Statistical and Probabilistic Inference
DEFF Research Database (Denmark)
Jaeger, Manfred
2005-01-01
When dealing with incomplete data in statistical learning, or incomplete observations in probabilistic inference, one needs to distinguish the fact that a certain event is observed from the fact that the observed event has happened. Since the modeling and computational complexities entailed...
Probabilistic fuzzy systems as additive fuzzy systems
Almeida, R.J.; Verbeek, N.; Kaymak, U.; Costa Sousa, da J.M.; Laurent, A.; Strauss, O.; Bouchon-Meunier, B.; Yager, R.
2014-01-01
Probabilistic fuzzy systems combine a linguistic description of the system behaviour with statistical properties of data. It was originally derived based on Zadeh’s concept of probability of a fuzzy event. Two possible and equivalent additive reasoning schemes were proposed, that lead to the
A Geometric Presentation of Probabilistic Satisfiability
Morales-Luna, Guillermo
2010-01-01
By considering probability distributions over the set of assignments the expected truth values assignment to propositional variables are extended through linear operators, and the expected truth values of the clauses at any given conjunctive form are also extended through linear maps. The probabilistic satisfiability problems are discussed in terms of the introduced linear extensions. The case of multiple truth values is also discussed.
Probabilistic studies for a safety assurance program
International Nuclear Information System (INIS)
Iyer, S.S.; Davis, J.F.
1985-01-01
The adequate supply of energy is always a matter of concern for any country. Nuclear power has played, and will continue to play an important role in supplying this energy. However, safety in nuclear power production is a fundamental prerequisite in fulfilling this role. This paper outlines a program to ensure safe operation of a nuclear power plant utilizing the Probabilistic Safety Studies
Probabilistic safety goals. Phase 3 - Status report
Energy Technology Data Exchange (ETDEWEB)
Holmberg, J.-E. (VTT (Finland)); Knochenhauer, M. (Relcon Scandpower AB, Sundbyberg (Sweden))
2009-07-15
The first phase of the project (2006) described the status, concepts and history of probabilistic safety goals for nuclear power plants. The second and third phases (2007-2008) have provided guidance related to the resolution of some of the problems identified, and resulted in a common understanding regarding the definition of safety goals. The basic aim of phase 3 (2009) has been to increase the scope and level of detail of the project, and to start preparations of a guidance document. Based on the conclusions from the previous project phases, the following issues have been covered: 1) Extension of international overview. Analysis of results from the questionnaire performed within the ongoing OECD/NEA WGRISK activity on probabilistic safety criteria, including participation in the preparation of the working report for OECD/NEA/WGRISK (to be finalised in phase 4). 2) Use of subsidiary criteria and relations between these (to be finalised in phase 4). 3) Numerical criteria when using probabilistic analyses in support of deterministic safety analysis (to be finalised in phase 4). 4) Guidance for the formulation, application and interpretation of probabilistic safety criteria (to be finalised in phase 4). (LN)
Safety Verification for Probabilistic Hybrid Systems
DEFF Research Database (Denmark)
Zhang, Lijun; She, Zhikun; Ratschan, Stefan
2010-01-01
The interplay of random phenomena and continuous real-time control deserves increased attention for instance in wireless sensing and control applications. Safety verification for such systems thus needs to consider probabilistic variations of systems with hybrid dynamics. In safety verification o...... on a number of case studies, tackled using a prototypical implementation....
Ambient Surveillance by Probabilistic-Possibilistic Perception
Bittermann, M.S.; Ciftcioglu, O.
2013-01-01
A method for quantifying ambient surveillance is presented, which is based on probabilistic-possibilistic perception. The human surveillance of a scene through observing camera sensed images on a monitor is modeled in three steps. First immersion of the observer is simulated by modeling perception
HERMES probabilistic risk assessment. Pilot study
International Nuclear Information System (INIS)
Parisot, F.; Munoz, J.
1993-01-01
The study was performed in 1989 of the contribution of probabilistic analysis for the optimal construction of system safety status in aeronautical and European nuclear industries, shows the growing trends towards incorporation of quantitative safety assessment and lead to an agreement to undertake a prototype proof study on Hermes. The main steps of the study and results are presented in the paper
Some probabilistic properties of fractional point processes
Garra, Roberto; Orsingher, Enzo; Scavino, Marco
2017-01-01
P{T-k(alpha) < infinity} are explicitly obtained and analyzed. The processes N-f (t) are time-changed Poisson processes N( H-f (t)) with subordinators H-f (t) and here we study N(Sigma H-n(j= 1)f j (t)) and obtain probabilistic features
Strong Statistical Convergence in Probabilistic Metric Spaces
Şençimen, Celaleddin; Pehlivan, Serpil
2008-01-01
In this article, we introduce the concepts of strongly statistically convergent sequence and strong statistically Cauchy sequence in a probabilistic metric (PM) space endowed with the strong topology, and establish some basic facts. Next, we define the strong statistical limit points and the strong statistical cluster points of a sequence in this space and investigate the relations between these concepts.
Effectiveness of Securities with Fuzzy Probabilistic Return
Directory of Open Access Journals (Sweden)
Krzysztof Piasecki
2011-01-01
Full Text Available The generalized fuzzy present value of a security is defined here as fuzzy valued utility of cash flow. The generalized fuzzy present value cannot depend on the value of future cash flow. There exists such a generalized fuzzy present value which is not a fuzzy present value in the sense given by some authors. If the present value is a fuzzy number and the future value is a random one, then the return rate is given as a probabilistic fuzzy subset on a real line. This kind of return rate is called a fuzzy probabilistic return. The main goal of this paper is to derive the family of effective securities with fuzzy probabilistic return. Achieving this goal requires the study of the basic parameters characterizing fuzzy probabilistic return. Therefore, fuzzy expected value and variance are determined for this case of return. These results are a starting point for constructing a three-dimensional image. The set of effective securities is introduced as the Pareto optimal set determined by the maximization of the expected return rate and minimization of the variance. Finally, the set of effective securities is distinguished as a fuzzy set. These results are obtained without the assumption that the distribution of future values is Gaussian. (original abstract
Dialectical Multivalued Logic and Probabilistic Theory
Directory of Open Access Journals (Sweden)
José Luis Usó Doménech
2017-02-01
Full Text Available There are two probabilistic algebras: one for classical probability and the other for quantum mechanics. Naturally, it is the relation to the object that decides, as in the case of logic, which algebra is to be used. From a paraconsistent multivalued logic therefore, one can derive a probability theory, adding the correspondence between truth value and fortuity.
Revisiting the formal foundation of Probabilistic Databases
Wanders, B.; van Keulen, Maurice
2015-01-01
One of the core problems in soft computing is dealing with uncertainty in data. In this paper, we revisit the formal foundation of a class of probabilistic databases with the purpose to (1) obtain data model independence, (2) separate metadata on uncertainty and probabilities from the raw data, (3)
Probabilistic Resource Analysis by Program Transformation
DEFF Research Database (Denmark)
Kirkeby, Maja Hanne; Rosendahl, Mads
2016-01-01
The aim of a probabilistic resource analysis is to derive a probability distribution of possible resource usage for a program from a probability distribution of its input. We present an automated multi-phase rewriting based method to analyze programs written in a subset of C. It generates...
Application of probabilistic precipitation forecasts from a ...
African Journals Online (AJOL)
Application of probabilistic precipitation forecasts from a deterministic model towards increasing the lead-time of flash flood forecasts in South Africa. ... The procedure is applied to a real flash flood event and the ensemble-based rainfall forecasts are verified against rainfall estimated by the SAFFG system. The approach ...
Probabilistic safety assessment goals in Canada
International Nuclear Information System (INIS)
Snell, V.G.
1986-01-01
CANDU safety philosphy, both in design and in licensing, has always had a strong bias towards quantitative probabilistically-based goals derived from comparative safety. Formal probabilistic safety assessment began in Canada as a design tool. The influence of this carried over later on into the definition of the deterministic safety guidelines used in CANDU licensing. Design goals were further developed which extended the consequence/frequency spectrum of 'acceptable' events, from the two points defined by the deterministic single/dual failure analysis, to a line passing through lower and higher frequencies. Since these were design tools, a complete risk summation was not necessary, allowing a cutoff at low event frequencies while preserving the identification of the most significant safety-related events. These goals gave a logical framework for making decisions on implementing design changes proposed as a result of the Probabilistic Safety Analysis. Performing this analysis became a regulatory requirement, and the design goals remained the framework under which this was submitted. Recently, there have been initiatives to incorporate more detailed probabilistic safety goals into the regulatory process in Canada. These range from far-reaching safety optimization across society, to initiatives aimed at the nuclear industry only. The effectiveness of the latter is minor at very low and very high event frequencies; at medium frequencies, a justification against expenditures per life saved in other industries should be part of the goal setting
Overview of the probabilistic risk assessment approach
International Nuclear Information System (INIS)
Reed, J.W.
1985-01-01
The techniques of probabilistic risk assessment (PRA) are applicable to Department of Energy facilities. The background and techniques of PRA are given with special attention to seismic, wind and flooding external events. A specific application to seismic events is provided to demonstrate the method. However, the PRA framework is applicable also to wind and external flooding. 3 references, 8 figures, 1 table
Probabilistic safety goals. Phase 3 - Status report
International Nuclear Information System (INIS)
Holmberg, J.-E.; Knochenhauer, M.
2009-07-01
The first phase of the project (2006) described the status, concepts and history of probabilistic safety goals for nuclear power plants. The second and third phases (2007-2008) have provided guidance related to the resolution of some of the problems identified, and resulted in a common understanding regarding the definition of safety goals. The basic aim of phase 3 (2009) has been to increase the scope and level of detail of the project, and to start preparations of a guidance document. Based on the conclusions from the previous project phases, the following issues have been covered: 1) Extension of international overview. Analysis of results from the questionnaire performed within the ongoing OECD/NEA WGRISK activity on probabilistic safety criteria, including participation in the preparation of the working report for OECD/NEA/WGRISK (to be finalised in phase 4). 2) Use of subsidiary criteria and relations between these (to be finalised in phase 4). 3) Numerical criteria when using probabilistic analyses in support of deterministic safety analysis (to be finalised in phase 4). 4) Guidance for the formulation, application and interpretation of probabilistic safety criteria (to be finalised in phase 4). (LN)
Branching bisimulation congruence for probabilistic systems
Andova, S.; Georgievska, S.; Trcka, N.
2012-01-01
A notion of branching bisimilarity for the alternating model of probabilistic systems, compatible with parallel composition, is defined. For a congruence result, an internal transition immediately followed by a non-trivial probability distribution is not considered inert. A weaker definition of
On Probabilistic Automata in Continuous Time
DEFF Research Database (Denmark)
Eisentraut, Christian; Hermanns, Holger; Zhang, Lijun
2010-01-01
We develop a compositional behavioural model that integrates a variation of probabilistic automata into a conservative extension of interactive Markov chains. The model is rich enough to embody the semantics of generalised stochastic Petri nets. We define strong and weak bisimulations and discuss...
Bisimulations Meet PCTL Equivalences for Probabilistic Automata
DEFF Research Database (Denmark)
Song, Lei; Zhang, Lijun; Godskesen, Jens Chr.
2011-01-01
Probabilistic automata (PA) [20] have been successfully applied in the formal verification of concurrent and stochastic systems. Efficient model checking algorithms have been studied, where the most often used logics for expressing properties are based on PCTL [11] and its extension PCTL∗ [4...
Validation of in vitro probabilistic tractography
DEFF Research Database (Denmark)
Dyrby, Tim B.; Sogaard, L.V.; Parker, G.J.
2007-01-01
assessed the anatomical validity and reproducibility of in vitro multi-fiber probabilistic tractography against two invasive tracers: the histochemically detectable biotinylated dextran amine and manganese enhanced magnetic resonance imaging. Post mortern DWI was used to ensure that most of the sources...
Searching Algorithms Implemented on Probabilistic Systolic Arrays
Czech Academy of Sciences Publication Activity Database
Kramosil, Ivan
1996-01-01
Roč. 25, č. 1 (1996), s. 7-45 ISSN 0308-1079 R&D Projects: GA ČR GA201/93/0781 Keywords : searching algorithms * probabilistic algorithms * systolic arrays * parallel algorithms Impact factor: 0.214, year: 1996
Financial Markets Analysis by Probabilistic Fuzzy Modelling
J.H. van den Berg (Jan); W.-M. van den Bergh (Willem-Max); U. Kaymak (Uzay)
2003-01-01
textabstractFor successful trading in financial markets, it is important to develop financial models where one can identify different states of the market for modifying one???s actions. In this paper, we propose to use probabilistic fuzzy systems for this purpose. We concentrate on Takagi???Sugeno
Towards decision making via expressive probabilistic ontologies
Acar, Erman; Thorne, Camilo; Stuckenschmidt, Heiner
2015-01-01
© Springer International Publishing Switzerland 2015. We propose a framework for automated multi-attribute deci- sion making, employing the probabilistic non-monotonic description log- ics proposed by Lukasiewicz in 2008. Using this framework, we can model artificial agents in decision-making
The Probabilistic Nature of Preferential Choice
Rieskamp, Jorg
2008-01-01
Previous research has developed a variety of theories explaining when and why people's decisions under risk deviate from the standard economic view of expected utility maximization. These theories are limited in their predictive accuracy in that they do not explain the probabilistic nature of preferential choice, that is, why an individual makes…
A Probabilistic Framework for Curve Evolution
DEFF Research Database (Denmark)
Dahl, Vedrana Andersen
2017-01-01
approach include ability to handle textured images, simple generalization to multiple regions, and efficiency in computation. We test our probabilistic framework in combination with parametric (snakes) and geometric (level-sets) curves. The experimental results on composed and natural images demonstrate...
Probabilistic Output Analysis by Program Manipulation
DEFF Research Database (Denmark)
Rosendahl, Mads; Kirkeby, Maja Hanne
2015-01-01
The aim of a probabilistic output analysis is to derive a probability distribution of possible output values for a program from a probability distribution of its input. We present a method for performing static output analysis, based on program transformation techniques. It generates a probability...
Improved transformer protection using probabilistic neural network ...
African Journals Online (AJOL)
This article presents a novel technique to distinguish between magnetizing inrush current and internal fault current of power transformer. An algorithm has been developed around the theme of the conventional differential protection method in which parallel combination of Probabilistic Neural Network (PNN) and Power ...
Financial markets analysis by probabilistic fuzzy modelling
Berg, van den J.; Kaymak, U.; Bergh, van den W.M.
2003-01-01
For successful trading in financial markets, it is important to develop financial models where one can identify different states of the market for modifying one???s actions. In this paper, we propose to use probabilistic fuzzy systems for this purpose. We concentrate on Takagi???Sugeno (TS)
Probabilistic solution of the Dirac equation
International Nuclear Information System (INIS)
Blanchard, P.; Combe, P.
1985-01-01
Various probabilistic representations of the 2, 3 and 4 dimensional Dirac equation are given in terms of expectation with respect to stochastic jump processes and are used to derive the nonrelativistic limit even in the presence of an external electromagnetic field. (orig.)
Mastering probabilistic graphical models using Python
Ankan, Ankur
2015-01-01
If you are a researcher or a machine learning enthusiast, or are working in the data science field and have a basic idea of Bayesian learning or probabilistic graphical models, this book will help you to understand the details of graphical models and use them in your data science problems.
Ye, Weiming; Li, Pengfei; Huang, Xuhui; Xia, Qinzhi; Mi, Yuanyuan; Chen, Runsheng; Hu, Gang
2010-10-01
Exploring the principle and relationship of gene transcriptional regulations (TR) has been becoming a generally researched issue. So far, two major mathematical methods, ordinary differential equation (ODE) method and Boolean map (BM) method have been widely used for these purposes. It is commonly believed that simplified BMs are reasonable approximations of more realistic ODEs, and both methods may reveal qualitatively the same essential features though the dynamical details of both systems may show some differences. In this Letter we exhaustively enumerated all the 3-gene networks and many autonomous randomly constructed TR networks with more genes by using both the ODE and BM methods. In comparison we found that both methods provide practically identical results in most of cases of steady solutions. However, to our great surprise, most of network structures showing periodic cycles with the BM method possess only stationary states in ODE descriptions. These observations strongly suggest that many periodic oscillations and other complicated oscillatory states revealed by the BM rule may be related to the computational errors of variable and time discretizations and rarely have correspondence in realistic biology transcriptional regulatory circuits.
A methodology for reviewing probabilistic risk assessments
International Nuclear Information System (INIS)
Derby, S.L.
1983-01-01
The starting point for peer review of a Probabilistic Risk Assessment (PRA) is a clear understanding of how the risk estimate was prepared and of what contributions dominate the calculation. The problem facing the reviewers is how to cut through the complex details of a PRA to gain this understanding. This paper presents a structured, analytical procedure that solves this problem. The effectiveness of this solution is demonstrated by an application on the Zion Probabilistic Safety Study. The procedure found the three dominant initiating events and provided a simplified reconstruction of the calculation of the risk estimate. Significant assessments of uncertainty were also identified. If peer review disputes the accuracy of these judgments, then the revised risk estimate could significantly increase
A probabilistic model of RNA conformational space
DEFF Research Database (Denmark)
Frellsen, Jes; Moltke, Ida; Thiim, Martin
2009-01-01
, the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these important limitations: a probabilistic model of RNA structure that allows...... conformations for 9 out of 10 test structures, solely using coarse-grained base-pairing information. In conclusion, the method provides a theoretical and practical solution for a major bottleneck on the way to routine prediction and simulation of RNA structure and dynamics in atomic detail.......The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA 3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an accurate energy function and a conformational sampling...
Growing hierarchical probabilistic self-organizing graphs.
López-Rubio, Ezequiel; Palomo, Esteban José
2011-07-01
Since the introduction of the growing hierarchical self-organizing map, much work has been done on self-organizing neural models with a dynamic structure. These models allow adjusting the layers of the model to the features of the input dataset. Here we propose a new self-organizing model which is based on a probabilistic mixture of multivariate Gaussian components. The learning rule is derived from the stochastic approximation framework, and a probabilistic criterion is used to control the growth of the model. Moreover, the model is able to adapt to the topology of each layer, so that a hierarchy of dynamic graphs is built. This overcomes the limitations of the self-organizing maps with a fixed topology, and gives rise to a faithful visualization method for high-dimensional data.
Generalized probabilistic scale space for image restoration.
Wong, Alexander; Mishra, Akshaya K
2010-10-01
A novel generalized sampling-based probabilistic scale space theory is proposed for image restoration. We explore extending the definition of scale space to better account for both noise and observation models, which is important for producing accurately restored images. A new class of scale-space realizations based on sampling and probability theory is introduced to realize this extended definition in the context of image restoration. Experimental results using 2-D images show that generalized sampling-based probabilistic scale-space theory can be used to produce more accurate restored images when compared with state-of-the-art scale-space formulations, particularly under situations characterized by low signal-to-noise ratios and image degradation.
Probabilistic cloning and deleting of quantum states
International Nuclear Information System (INIS)
Feng Yuan; Zhang Shengyu; Ying Mingsheng
2002-01-01
We construct a probabilistic cloning and deleting machine which, taking several copies of an input quantum state, can output a linear superposition of multiple cloning and deleting states. Since the machine can perform cloning and deleting in a single unitary evolution, the probabilistic cloning and other cloning machines proposed in the previous literature can be thought of as special cases of our machine. A sufficient and necessary condition for successful cloning and deleting is presented, and it requires that the copies of an arbitrarily presumed number of the input states are linearly independent. This simply generalizes some results for cloning. We also derive an upper bound for the success probability of the cloning and deleting machine
Probabilistic Modeling of Wind Turbine Drivetrain Components
DEFF Research Database (Denmark)
Rafsanjani, Hesam Mirzaei
Wind energy is one of several energy sources in the world and a rapidly growing industry in the energy sector. When placed in offshore or onshore locations, wind turbines are exposed to wave excitations, highly dynamic wind loads and/or the wakes from other wind turbines. Therefore, most components...... in a wind turbine experience highly dynamic and time-varying loads. These components may fail due to wear or fatigue, and this can lead to unplanned shutdown repairs that are very costly. The design by deterministic methods using safety factors is generally unable to account for the many uncertainties. Thus......, a reliability assessment should be based on probabilistic methods where stochastic modeling of failures is performed. This thesis focuses on probabilistic models and the stochastic modeling of the fatigue life of the wind turbine drivetrain. Hence, two approaches are considered for stochastic modeling...
A probabilistic model of RNA conformational space
DEFF Research Database (Denmark)
Frellsen, Jes; Moltke, Ida; Thiim, Martin
2009-01-01
efficient sampling of RNA conformations in continuous space, and with associated probabilities. We show that the model captures several key features of RNA structure, such as its rotameric nature and the distribution of the helix lengths. Furthermore, the model readily generates native-like 3-D......, the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these important limitations: a probabilistic model of RNA structure that allows......The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA 3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an accurate energy function and a conformational sampling...
Probabilistic approach to manipulator kinematics and dynamics
International Nuclear Information System (INIS)
Rao, S.S.; Bhatti, P.K.
2001-01-01
A high performance, high speed robotic arm must be able to manipulate objects with a high degree of accuracy and repeatability. As with any other physical system, there are a number of factors causing uncertainties in the behavior of a robotic manipulator. These factors include manufacturing and assembling tolerances, and errors in the joint actuators and controllers. In order to study the effect of these uncertainties on the robotic end-effector and to obtain a better insight into the manipulator behavior, the manipulator kinematics and dynamics are modeled using a probabilistic approach. Based on the probabilistic model, kinematic and dynamic performance criteria are defined to provide measures of the behavior of the robotic end-effector. Techniques are presented to compute the kinematic and dynamic reliabilities of the manipulator. The effects of tolerances associated with the various manipulator parameters on the reliabilities are studied. Numerical examples are presented to illustrate the procedures
Probabilistic precursor analysis - an application of PSA
International Nuclear Information System (INIS)
Hari Prasad, M.; Gopika, V.; Sanyasi Rao, V.V.S.; Vaze, K.K.
2011-01-01
Incidents are inevitably part of the operational life of any complex industrial facility, and it is hard to predict how various contributing factors combine to cause the outcome. However, it should be possible to detect the existence of latent conditions that, together with the triggering failure(s), result in abnormal events. These incidents are called precursors. Precursor study, by definition, focuses on how a particular event might have adversely developed. This paper focuses on the events which can be analyzed to assess their potential to develop into core damage situation and looks into extending Probabilistic Safety Assessment techniques to precursor studies and explains the benefits through a typical case study. A preliminary probabilistic precursor analysis has been carried out for a typical NPP. The major advantages of this approach are the strong potential for augmenting event analysis which is currently carried out purely on deterministic basis. (author)
Probabilistic Analysis of Gas Turbine Field Performance
Gorla, Rama S. R.; Pai, Shantaram S.; Rusick, Jeffrey J.
2002-01-01
A gas turbine thermodynamic cycle was computationally simulated and probabilistically evaluated in view of the several uncertainties in the performance parameters, which are indices of gas turbine health. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design, enhance performance, increase system availability and make it cost effective. The analysis leads to the selection of the appropriate measurements to be used in the gas turbine health determination and to the identification of both the most critical measurements and parameters. Probabilistic analysis aims at unifying and improving the control and health monitoring of gas turbine aero-engines by increasing the quality and quantity of information available about the engine's health and performance.
Probabilistic safety assessment for research reactors
International Nuclear Information System (INIS)
1986-12-01
Increasing interest in using Probabilistic Safety Assessment (PSA) methods for research reactor safety is being observed in many countries throughout the world. This is mainly because of the great ability of this approach in achieving safe and reliable operation of research reactors. There is also a need to assist developing countries to apply Probabilistic Safety Assessment to existing nuclear facilities which are simpler and therefore less complicated to analyse than a large Nuclear Power Plant. It may be important, therefore, to develop PSA for research reactors. This might also help to better understand the safety characteristics of the reactor and to base any backfitting on a cost-benefit analysis which would ensure that only necessary changes are made. This document touches on all the key aspects of PSA but placed greater emphasis on so-called systems analysis aspects rather than the in-plant or ex-plant consequences
Probabilistic forecasting and Bayesian data assimilation
Reich, Sebastian
2015-01-01
In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...
Fast probabilistic file fingerprinting for big data.
Tretyakov, Konstantin; Laur, Sven; Smant, Geert; Vilo, Jaak; Prins, Pjotr
2013-01-01
Biological data acquisition is raising new challenges, both in data analysis and handling. Not only is it proving hard to analyze the data at the rate it is generated today, but simply reading and transferring data files can be prohibitively slow due to their size. This primarily concerns logistics within and between data centers, but is also important for workstation users in the analysis phase. Common usage patterns, such as comparing and transferring files, are proving computationally expensive and are tying down shared resources. We present an efficient method for calculating file uniqueness for large scientific data files, that takes less computational effort than existing techniques. This method, called Probabilistic Fast File Fingerprinting (PFFF), exploits the variation present in biological data and computes file fingerprints by sampling randomly from the file instead of reading it in full. Consequently, it has a flat performance characteristic, correlated with data variation rather than file size. We demonstrate that probabilistic fingerprinting can be as reliable as existing hashing techniques, with provably negligible risk of collisions. We measure the performance of the algorithm on a number of data storage and access technologies, identifying its strengths as well as limitations. Probabilistic fingerprinting may significantly reduce the use of computational resources when comparing very large files. Utilisation of probabilistic fingerprinting techniques can increase the speed of common file-related workflows, both in the data center and for workbench analysis. The implementation of the algorithm is available as an open-source tool named pfff, as a command-line tool as well as a C library. The tool can be downloaded from http://biit.cs.ut.ee/pfff.
Probabilistic, meso-scale flood loss modelling
Kreibich, Heidi; Botto, Anna; Schröter, Kai; Merz, Bruno
2016-04-01
Flood risk analyses are an important basis for decisions on flood risk management and adaptation. However, such analyses are associated with significant uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention during the last years, they are still not standard practice for flood risk assessments and even more for flood loss modelling. State of the art in flood loss modelling is still the use of simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood loss models have been developed and validated on the micro-scale using a data-mining approach, namely bagging decision trees (Merz et al. 2013). In this presentation we demonstrate and evaluate the upscaling of the approach to the meso-scale, namely on the basis of land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany (Botto et al. submitted). The application of bagging decision tree based loss models provide a probability distribution of estimated loss per municipality. Validation is undertaken on the one hand via a comparison with eight deterministic loss models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official loss data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of loss estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation approach is that it inherently provides quantitative information about the uncertainty of the prediction. References: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64. Botto A, Kreibich H, Merz B, Schröter K (submitted) Probabilistic, multi-variable flood loss modelling on the meso-scale with BT-FLEMO. Risk Analysis.
Probabilistic Bandwidth Assignment in Wireless Sensor Networks
Khan , Dawood; Nefzi , Bilel; Santinelli , Luca; Song , Ye-Qiong
2012-01-01
International audience; With this paper we offer an insight in designing and analyzing wireless sensor networks in a versatile manner. Our framework applies probabilistic and component-based design principles for the wireless sensor network modeling and consequently analysis; while maintaining flexibility and accuracy. In particular, we address the problem of allocating and reconfiguring the available bandwidth. The framework has been successfully implemented in IEEE 802.15.4 using an Admissi...
Probabilistic real-time contingency ranking method
International Nuclear Information System (INIS)
Mijuskovic, N.A.; Stojnic, D.
2000-01-01
This paper describes a real-time contingency method based on a probabilistic index-expected energy not supplied. This way it is possible to take into account the stochastic nature of the electric power system equipment outages. This approach enables more comprehensive ranking of contingencies and it is possible to form reliability cost values that can form the basis for hourly spot price calculations. The electric power system of Serbia is used as an example for the method proposed. (author)
A probabilistic approach to crack instability
Chudnovsky, A.; Kunin, B.
1989-01-01
A probabilistic model of brittle fracture is examined with reference to two-dimensional problems. The model is illustrated by using experimental data obtained for 25 macroscopically identical specimens made of short-fiber-reinforced composites. It is shown that the model proposed here provides a predictive formalism for the probability distributions of critical crack depth, critical loads, and crack arrest depths. It also provides similarity criteria for small-scale testing.
A probabilistic maintenance model for diesel engines
Pathirana, Shan; Abeygunawardane, Saranga Kumudu
2018-02-01
In this paper, a probabilistic maintenance model is developed for inspection based preventive maintenance of diesel engines based on the practical model concepts discussed in the literature. Developed model is solved using real data obtained from inspection and maintenance histories of diesel engines and experts' views. Reliability indices and costs were calculated for the present maintenance policy of diesel engines. A sensitivity analysis is conducted to observe the effect of inspection based preventive maintenance on the life cycle cost of diesel engines.
Probabilistic theism and the problem of evil
Directory of Open Access Journals (Sweden)
Dariusz Łukasiewicz
2017-01-01
Full Text Available I would like to present in the article an “omnipotence model of a theodicy of chance”, which is, as I believe, compatible with the view called probabilistic theism. I also would like to argue that this model satisfies the criteria of being a good theodicy. By a good theodicy I mean a reasonable and plausible theistic account of evil. A good theodicy should be: a comprehensive, b adequate, c authentic and d existentially relevant.
Probabilistic studies for safety at optimum cost
International Nuclear Information System (INIS)
Pitner, P.
1999-01-01
By definition, the risk of failure of very reliable components is difficult to evaluate. How can the best strategies for in service inspection and maintenance be defined to limit this risk to an acceptable level at optimum cost? It is not sufficient to design structures with margins, it is also essential to understand how they age. The probabilistic approach has made it possible to develop well proven concepts. (author)
Incorporating psychological influences in probabilistic cost analysis
Energy Technology Data Exchange (ETDEWEB)
Kujawski, Edouard; Alvaro, Mariana; Edwards, William
2004-01-08
Today's typical probabilistic cost analysis assumes an ''ideal'' project that is devoid of the human and organizational considerations that heavily influence the success and cost of real-world projects. In the real world ''Money Allocated Is Money Spent'' (MAIMS principle); cost underruns are rarely available to protect against cost overruns while task overruns are passed on to the total project cost. Realistic cost estimates therefore require a modified probabilistic cost analysis that simultaneously models the cost management strategy including budget allocation. Psychological influences such as overconfidence in assessing uncertainties and dependencies among cost elements and risks are other important considerations that are generally not addressed. It should then be no surprise that actual project costs often exceed the initial estimates and are delivered late and/or with a reduced scope. This paper presents a practical probabilistic cost analysis model that incorporates recent findings in human behavior and judgment under uncertainty, dependencies among cost elements, the MAIMS principle, and project management practices. Uncertain cost elements are elicited from experts using the direct fractile assessment method and fitted with three-parameter Weibull distributions. The full correlation matrix is specified in terms of two parameters that characterize correlations among cost elements in the same and in different subsystems. The analysis is readily implemented using standard Monte Carlo simulation tools such as {at}Risk and Crystal Ball{reg_sign}. The analysis of a representative design and engineering project substantiates that today's typical probabilistic cost analysis is likely to severely underestimate project cost for probability of success values of importance to contractors and procuring activities. The proposed approach provides a framework for developing a viable cost management strategy for
Characterizing the topology of probabilistic biological networks.
Todor, Andrei; Dobra, Alin; Kahveci, Tamer
2013-01-01
Biological interactions are often uncertain events, that may or may not take place with some probability. This uncertainty leads to a massive number of alternative interaction topologies for each such network. The existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. In this paper, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. Using our mathematical representation, we develop a method that can accurately describe the degree distribution of such networks. We also take one more step and extend our method to accurately compute the joint-degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. Our method works quickly even for entire protein-protein interaction (PPI) networks. It also helps us find an adequate mathematical model using MLE. We perform a comparative study of node-degree and joint-degree distributions in two types of biological networks: the classical deterministic networks and the more flexible probabilistic networks. Our results confirm that power-law and log-normal models best describe degree distributions for both probabilistic and deterministic networks. Moreover, the inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected. We also show that probabilistic networks are more robust for node-degree distribution computation than the deterministic ones. all the data sets used, the software
Failure probabilistic model of CNC lathes
International Nuclear Information System (INIS)
Wang Yiqiang; Jia Yazhou; Yu Junyi; Zheng Yuhua; Yi Shangfeng
1999-01-01
A field failure analysis of computerized numerical control (CNC) lathes is described. Field failure data was collected over a period of two years on approximately 80 CNC lathes. A coding system to code failure data was devised and a failure analysis data bank of CNC lathes was established. The failure position and subsystem, failure mode and cause were analyzed to indicate the weak subsystem of a CNC lathe. Also, failure probabilistic model of CNC lathes was analyzed by fuzzy multicriteria comprehensive evaluation
Insights gained through probabilistic risk assessments
International Nuclear Information System (INIS)
Hitchler, M.J.; Burns, N.L.; Liparulo, N.J.; Mink, F.J.
1987-01-01
The insights gained through a comparison of seven probabilistic risk assessments (PRA) studies (Italian PUN, Sizewell B, Ringhals 2, Millstone 3, Zion 1 and 2, Oconee 3, and Seabrook) included insights regarding the adequacy of the PRA technology utilized in the studies and the potential areas for improvement and insights regarding the adequacy of plant designs and how PRA has been utilized to enhance the design and operation of nuclear power plants
Towards probabilistic synchronisation of local controllers
Czech Academy of Sciences Publication Activity Database
Herzallah, R.; Kárný, Miroslav
2017-01-01
Roč. 48, č. 3 (2017), s. 604-615 ISSN 0020-7721 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : cooperative control * optimal control * complex system s * stochastic system s * fully probabilistic desing Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 2.285, year: 2016
Fully probabilistic design of hierarchical Bayesian models
Czech Academy of Sciences Publication Activity Database
Quinn, A.; Kárný, Miroslav; Guy, Tatiana Valentine
2016-01-01
Roč. 369, č. 1 (2016), s. 532-547 ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Fully probabilistic design * Ideal distribution * Minimum cross-entropy principle * Bayesian conditioning * Kullback-Leibler divergence * Bayesian nonparametric modelling Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.832, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0463052.pdf
Probabilistic Extraction Of Vectors In PIV
Humphreys, William M., Jr.
1994-01-01
Probabilistic technique for extraction of velocity vectors in particle-image velocimetry (PIV) implemented with much less computation. Double-exposure photograph of particles in flow illuminated by sheet of light provides data on velocity field of flow. Photograph converted into video image then digitized and processed by computer into velocity-field data. Velocity vectors in interrogation region chosen from magnitude and angle histograms constructed from centroid map of region.
Probabilistic Models for Solar Particle Events
Adams, James H., Jr.; Dietrich, W. F.; Xapsos, M. A.; Welton, A. M.
2009-01-01
Probabilistic Models of Solar Particle Events (SPEs) are used in space mission design studies to provide a description of the worst-case radiation environment that the mission must be designed to tolerate.The models determine the worst-case environment using a description of the mission and a user-specified confidence level that the provided environment will not be exceeded. This poster will focus on completing the existing suite of models by developing models for peak flux and event-integrated fluence elemental spectra for the Z>2 elements. It will also discuss methods to take into account uncertainties in the data base and the uncertainties resulting from the limited number of solar particle events in the database. These new probabilistic models are based on an extensive survey of SPE measurements of peak and event-integrated elemental differential energy spectra. Attempts are made to fit the measured spectra with eight different published models. The model giving the best fit to each spectrum is chosen and used to represent that spectrum for any energy in the energy range covered by the measurements. The set of all such spectral representations for each element is then used to determine the worst case spectrum as a function of confidence level. The spectral representation that best fits these worst case spectra is found and its dependence on confidence level is parameterized. This procedure creates probabilistic models for the peak and event-integrated spectra.
Probabilistic Graph Layout for Uncertain Network Visualization.
Schulz, Christoph; Nocaj, Arlind; Goertler, Jochen; Deussen, Oliver; Brandes, Ulrik; Weiskopf, Daniel
2017-01-01
We present a novel uncertain network visualization technique based on node-link diagrams. Nodes expand spatially in our probabilistic graph layout, depending on the underlying probability distributions of edges. The visualization is created by computing a two-dimensional graph embedding that combines samples from the probabilistic graph. A Monte Carlo process is used to decompose a probabilistic graph into its possible instances and to continue with our graph layout technique. Splatting and edge bundling are used to visualize point clouds and network topology. The results provide insights into probability distributions for the entire network-not only for individual nodes and edges. We validate our approach using three data sets that represent a wide range of network types: synthetic data, protein-protein interactions from the STRING database, and travel times extracted from Google Maps. Our approach reveals general limitations of the force-directed layout and allows the user to recognize that some nodes of the graph are at a specific position just by chance.
Probabilistic safety analysis and interpretation thereof
International Nuclear Information System (INIS)
Steininger, U.; Sacher, H.
1999-01-01
Increasing use of the instrumentation of PSA is being made in Germany for quantitative technical safety assessment, for example with regard to incidents which must be reported and forwarding of information, especially in the case of modification of nuclear plants. The Commission for Nuclear Reactor Safety recommends regular execution of PSA on a cycle period of ten years. According to the PSA guidance instructions, probabilistic analyses serve for assessing the degree of safety of the entire plant, expressed as the expectation value for the frequency of endangering conditions. The authors describe the method, action sequence and evaluation of the probabilistic safety analyses. The limits of probabilistic safety analyses arise in the practical implementation. Normally the guidance instructions for PSA are confined to the safety systems, so that in practice they are at best suitable for operational optimisation only to a limited extent. The present restriction of the analyses has a similar effect on power output operation of the plant. This seriously degrades the utilitarian value of these analyses for the plant operators. In order to further develop PSA as a supervisory and operational optimisation instrument, both authors consider it to be appropriate to bring together the specific know-how of analysts, manufacturers, plant operators and experts. (orig.) [de
PRECIS -- A probabilistic risk assessment system
International Nuclear Information System (INIS)
Peterson, D.M.; Knowlton, R.G. Jr.
1996-01-01
A series of computer tools has been developed to conduct the exposure assessment and risk characterization phases of human health risk assessments within a probabilistic framework. The tools are collectively referred to as the Probabilistic Risk Evaluation and Characterization Investigation System (PRECIS). With this system, a risk assessor can calculate the doses and risks associated with multiple environmental and exposure pathways, for both chemicals and radioactive contaminants. Exposure assessment models in the system account for transport of contaminants to receptor points from a source zone originating in unsaturated soils above the water table. In addition to performing calculations of dose and risk based on initial concentrations, PRECIS can also be used in an inverse manner to compute soil concentrations in the source area that must not be exceeded if prescribed limits on dose or risk are to be met. Such soil contaminant levels, referred to as soil guidelines, are computed for both single contaminants and chemical mixtures and can be used as action levels or cleanup levels. Probabilistic estimates of risk, dose and soil guidelines are derived using Monte Carlo techniques
Applications of probabilistic techniques at NRC
International Nuclear Information System (INIS)
Thadani, A.; Rowsome, F.; Speis, T.
1984-01-01
The NRC is currently making extensive use of probabilistic safety assessment in the reactor regulation. Most of these applications have been introduced in the regulatory activities in the past few years. Plant Probabilistic Safety Studies are being utilized as a design tool for applications for standard designs and for assessment of plants located in regions of particularly high population density. There is considerable motivation for licenses to perform plant-specific probabilistic studies for many, if not all, of the existing operating nuclear power plants as a tool for prioritizing the implementation of the many outstanding licensing actions of these plants as well as recommending the elimination of a number of these issues which are judged to be insignificant in terms of their contribution to safety and risk. Risk assessment perspectives are being used in the priorization of generic safety issues, development of technical resolution of unresolved safety issues, assessing safety significance of proposed new regulatory requirements, assessment of safety significance of some of the occurrences at operating facilities and in environmental impact analyses of license applicants as required by the National Environmental Policy Act. (orig.)
Symbolic Computing in Probabilistic and Stochastic Analysis
Directory of Open Access Journals (Sweden)
Kamiński Marcin
2015-12-01
Full Text Available The main aim is to present recent developments in applications of symbolic computing in probabilistic and stochastic analysis, and this is done using the example of the well-known MAPLE system. The key theoretical methods discussed are (i analytical derivations, (ii the classical Monte-Carlo simulation approach, (iii the stochastic perturbation technique, as well as (iv some semi-analytical approaches. It is demonstrated in particular how to engage the basic symbolic tools implemented in any system to derive the basic equations for the stochastic perturbation technique and how to make an efficient implementation of the semi-analytical methods using an automatic differentiation and integration provided by the computer algebra program itself. The second important illustration is probabilistic extension of the finite element and finite difference methods coded in MAPLE, showing how to solve boundary value problems with random parameters in the environment of symbolic computing. The response function method belongs to the third group, where interference of classical deterministic software with the non-linear fitting numerical techniques available in various symbolic environments is displayed. We recover in this context the probabilistic structural response in engineering systems and show how to solve partial differential equations including Gaussian randomness in their coefficients.
Probabilistic safety analysis vs probabilistic fracture mechanics -relation and necessary merging
International Nuclear Information System (INIS)
Nilsson, Fred
1997-01-01
A comparison is made between some general features of probabilistic fracture mechanics (PFM) and probabilistic safety assessment (PSA) in its standard form. We conclude that: Result from PSA is a numerically expressed level of confidence in the system based on the state of current knowledge. It is thus not any objective measure of risk. It is important to carefully define the precise nature of the probabilistic statement and relate it to a well defined situation. Standardisation of PFM methods is necessary. PFM seems to be the only way to obtain estimates of the pipe break probability. Service statistics are of doubtful value because of scarcity of data and statistical inhomogeneity. Collection of service data should be directed towards the occurrence of growing cracks
Nonvolatile “AND,” “OR,” and “NOT” Boolean logic gates based on phase-change memory
Energy Technology Data Exchange (ETDEWEB)
Li, Y.; Zhong, Y. P.; Deng, Y. F.; Zhou, Y. X.; Xu, L.; Miao, X. S., E-mail: miaoxs@mail.hust.edu.cn [Wuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology (HUST), Wuhan 430074 (China); School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074 (China)
2013-12-21
Electronic devices or circuits that can implement both logic and memory functions are regarded as the building blocks for future massive parallel computing beyond von Neumann architecture. Here we proposed phase-change memory (PCM)-based nonvolatile logic gates capable of AND, OR, and NOT Boolean logic operations verified in SPICE simulations and circuit experiments. The logic operations are parallel computing and results can be stored directly in the states of the logic gates, facilitating the combination of computing and memory in the same circuit. These results are encouraging for ultralow-power and high-speed nonvolatile logic circuit design based on novel memory devices.
Nonvolatile “AND,” “OR,” and “NOT” Boolean logic gates based on phase-change memory
International Nuclear Information System (INIS)
Li, Y.; Zhong, Y. P.; Deng, Y. F.; Zhou, Y. X.; Xu, L.; Miao, X. S.
2013-01-01
Electronic devices or circuits that can implement both logic and memory functions are regarded as the building blocks for future massive parallel computing beyond von Neumann architecture. Here we proposed phase-change memory (PCM)-based nonvolatile logic gates capable of AND, OR, and NOT Boolean logic operations verified in SPICE simulations and circuit experiments. The logic operations are parallel computing and results can be stored directly in the states of the logic gates, facilitating the combination of computing and memory in the same circuit. These results are encouraging for ultralow-power and high-speed nonvolatile logic circuit design based on novel memory devices
On probabilistic forecasting of wind power time-series
DEFF Research Database (Denmark)
Pinson, Pierre
power dynamics. In both cases, the model parameters are adaptively and recursively estimated, time-adaptativity being the result of exponential forgetting of past observations. The probabilistic forecasting methodology is applied at the Horns Rev wind farm in Denmark, for 10-minute ahead probabilistic...... forecasting of wind power generation. Probabilistic forecasts generated from the proposed methodology clearly have higher skill than those obtained from a classical Gaussian assumption about wind power predictive densities. Corresponding point forecasts also exhibit significantly lower error criteria....
Volume 2. Probabilistic analysis of HTGR application studies. Supporting data
International Nuclear Information System (INIS)
1980-09-01
Volume II, Probabilistic Analysis of HTGR Application Studies - Supporting Data, gives the detail data, both deterministic and probabilistic, employed in the calculation presented in Volume I. The HTGR plants and the fossil plants considered in the study are listed. GCRA provided the technical experts from which the data were obtained by MAC personnel. The names of the technical experts (interviewee) and the analysts (interviewer) are given for the probabilistic data