Towards a computational model of the self-attribution of agency

NARCIS (Netherlands)

Hindriks, K.V.; Wiggers, P.; Jonker, C.M.; Haselager, W.F.G.; Olivier, P.; Kray, C.

2007-01-01

In this paper, a first step towards a computational model of the self-attribution of agency is presented, based on Wegner’s theory of apparent mental causation. A model to compute a feeling of doing based on first-order Bayesian network theory is introduced that incorporates the main contributing

An organizing model for recent cognitive science work on the self.

Science.gov (United States)

Pageler, Ben

2016-10-01

An organizing model of 'the self' emerges from applying various kinds of brain injury to recent cognitive science and philosophical work on 'the self'. This model unifies various contents and mechanisms central to current notions of the self. The article then highlights several criteria and aspects of this notion of self. Qualities of the right type and level of psychological significance delineate 'the self' as an organizing concept useful for recent philosophical work and cognitive science research. Copyright © 2016 Elsevier Inc. All rights reserved.

Improving public transportation systems with self-organization: A headway-based model and regulation of passenger alighting and boarding.

Science.gov (United States)

Carreón, Gustavo; Gershenson, Carlos; Pineda, Luis A

2017-01-01

The equal headway instability-the fact that a configuration with regular time intervals between vehicles tends to be volatile-is a common regulation problem in public transportation systems. An unsatisfactory regulation results in low efficiency and possible collapses of the service. Computational simulations have shown that self-organizing methods can regulate the headway adaptively beyond the theoretical optimum. In this work, we develop a computer simulation for metro systems fed with real data from the Mexico City Metro to test the current regulatory method with a novel self-organizing approach. The current model considers overall system's data such as minimum and maximum waiting times at stations, while the self-organizing method regulates the headway in a decentralized manner using local information such as the passenger's inflow and the positions of neighboring trains. The simulation shows that the self-organizing method improves the performance over the current one as it adapts to environmental changes at the timescale they occur. The correlation between the simulation of the current model and empirical observations carried out in the Mexico City Metro provides a base to calculate the expected performance of the self-organizing method in case it is implemented in the real system. We also performed a pilot study at the Balderas station to regulate the alighting and boarding of passengers through guide signs on platforms. The analysis of empirical data shows a delay reduction of the waiting time of trains at stations. Finally, we provide recommendations to improve public transportation systems.

Analyzing C2 Structures and Self-Synchronization with Simple Computational Models

Science.gov (United States)

2011-06-01

16th ICCRTS “Collective C2 in Multinational Civil-Military Operations” Analyzing C2 Structures and Self- Synchronization with Simple...Self- Synchronization with Simple Computational Models 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT...models. The Kuramoto Model, though with some serious limitations, provides a representation of information flow and self- synchronization in an

Self-Organizing Units in an Interdisciplinary Course for Pervasive Computing Design

OpenAIRE

McNair, Lisa; Newswander, Chad; Coupey, Eloise; Dorsa, Ed; Martin, Tom; Paretti, Marie

2009-01-01

We conducted a case study of a design course that focused on bringing together students from engineering, industrial design, and marketing to use pervasive computing technologies to design, coordinate, and build a “smart” dorm room for disabled individuals. The class was loosely structured to encourage innovation, critical thinking and interdisciplinarity. In this environment, teams were created, disassembled, and re-created in a self-organizing fashion. With few norms, teams were expected to...

Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata

Directory of Open Access Journals (Sweden)

Jorge L. Zapotecatl

2017-01-01

Full Text Available Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave and a similar performance (close to optimal compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.

A computational model of self-efficacy's various effects on performance: Moving the debate forward.

Science.gov (United States)

Vancouver, Jeffrey B; Purl, Justin D

2017-04-01

Self-efficacy, which is one's belief in one's capacity, has been found to both positively and negatively influence effort and performance. The reasons for these different effects have been a major topic of debate among social-cognitive and perceptual control theorists. In particular, the findings of various self-efficacy effects has been motivated by a perceptual control theory view of self-regulation that social-cognitive theorists' question. To provide more clarity to the theoretical arguments, a computational model of the multiple processes presumed to create the positive, negative, and null effects for self-efficacy is presented. Building on an existing computational model of goal choice that produces a positive effect for self-efficacy, the current article adds a symbolic processing structure used during goal striving that explains the negative self-efficacy effect observed in recent studies. Moreover, the multiple processes, operating together, allow the model to recreate the various effects found in a published study of feedback ambiguity's moderating role on the self-efficacy to performance relationship (Schmidt & DeShon, 2010). Discussion focuses on the implications of the model for the self-efficacy debate, alternative computational models, the overlap between control theory and social-cognitive theory explanations, the value of using computational models for resolving theoretical disputes, and future research and directions the model inspires. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Computational Genetic Regulatory Networks Evolvable, Self-organizing Systems

CERN Document Server

Knabe, Johannes F

2013-01-01

Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting fr...

The self-adaptation to dynamic failures for efficient virtual organization formations in grid computing context

International Nuclear Information System (INIS)

Han Liangxiu

2009-01-01

Grid computing aims to enable 'resource sharing and coordinated problem solving in dynamic, multi-institutional virtual organizations (VOs)'. However, due to the nature of heterogeneous and dynamic resources, dynamic failures in the distributed grid environment usually occur more than in traditional computation platforms, which cause failed VO formations. In this paper, we develop a novel self-adaptive mechanism to dynamic failures during VO formations. Such a self-adaptive scheme allows an individual and member of VOs to automatically find other available or replaceable one once a failure happens and therefore makes systems automatically recover from dynamic failures. We define dynamic failure situations of a system by using two standard indicators: mean time between failures (MTBF) and mean time to recover (MTTR). We model both MTBF and MTTR as Poisson distributions. We investigate and analyze the efficiency of the proposed self-adaptation mechanism to dynamic failures by comparing the success probability of VO formations before and after adopting it in three different cases: (1) different failure situations; (2) different organizational structures and scales; (3) different task complexities. The experimental results show that the proposed scheme can automatically adapt to dynamic failures and effectively improve the dynamic VO formation performance in the event of node failures, which provide a valuable addition to the field.

Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective

Directory of Open Access Journals (Sweden)

Zhicong Zhang

2018-01-01

Full Text Available We study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a control decision model for them based on the coupled reinforcement learning (RL architecture. To maximize the mean time averaged weighted throughput of the jobs through the network, we propose a reinforcement learning algorithm with time averaged reward to deal with the control decision model and obtain a control policy integrating the jobs routing selection strategy and the jobs sequencing strategy. Computational experiments verify the learning ability and the effectiveness of the proposed reinforcement learning algorithm applied in the investigated self-organizing network control problem.

Self Organization in Compensated Semiconductors

Science.gov (United States)

Berezin, Alexander A.

2004-03-01

In partially compensated semiconductor (PCS) Fermi level is pinned to donor sub-band. Due to positional randomness and almost isoenergetic hoppings, donor-spanned electronic subsystem in PCS forms fluid-like highly mobile collective state. This makes PCS playground for pattern formation, self-organization, complexity emergence, electronic neural networks, and perhaps even for origins of life, bioevolution and consciousness. Through effects of impact and/or Auger ionization of donor sites, whole PCS may collapse (spinodal decomposition) into microblocks potentially capable of replication and protobiological activity (DNA analogue). Electronic screening effects may act in RNA fashion by introducing additional length scale(s) to system. Spontaneous quantum computing on charged/neutral sites becomes potential generator of informationally loaded microstructures akin to "Carl Sagan Effect" (hidden messages in Pi in his "Contact") or informational self-organization of "Library of Babel" of J.L. Borges. Even general relativity effects at Planck scale (R.Penrose) may affect the dynamics through (e.g.) isotopic variations of atomic mass and local density (A.A.Berezin, 1992). Thus, PCS can serve as toy model (experimental and computational) at interface of physics and life sciences.

Self-Organization in Embedded Real-Time Systems

CERN Document Server

Brinkschulte, Uwe; Rettberg, Achim

2013-01-01

This book describes the emerging field of self-organizing, multicore, distributed and real-time embedded systems.  Self-organization of both hardware and software can be a key technique to handle the growing complexity of modern computing systems. Distributed systems running hundreds of tasks on dozens of processors, each equipped with multiple cores, requires self-organization principles to ensure efficient and reliable operation. This book addresses various, so-called Self-X features such as self-configuration, self-optimization, self-adaptation, self-healing and self-protection. Presents open components for embedded real-time adaptive and self-organizing applications; Describes innovative techniques in: scheduling, memory management, quality of service, communications supporting organic real-time applications; Covers multi-/many-core embedded systems supporting real-time adaptive systems and power-aware, adaptive hardware and software systems; Includes case studies of open embedded real-time self-organizi...

Modelling the self-organization and collapse of complex networks

Indian Academy of Sciences (India)

Modelling the self-organization and collapse of complex networks. Sanjay Jain Department of Physics and Astrophysics, University of Delhi Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore Santa Fe Institute, Santa Fe, New Mexico.

Investigation on Self-Organization Processes in DC Generators by Synergetic Modeling

OpenAIRE

Ion Voncilă; Mădălin Costin; Răzvan Buhosu

2014-01-01

In this paper is suggested a new mathematical model, based on which it can be justified the self-excitation DC generators, either shunt or series excitation, by self-organization phenomena that appear to overcome threshold values (self-excitation in these generators is an avalanche process, a positive feedback, considered at first glance uncontrollable).

Growing hierarchical probabilistic self-organizing graphs.

Science.gov (United States)

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.

A Data-Driven, Integrated Flare Model Based on Self-Organized Criticality

Science.gov (United States)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M.

2013-09-01

We interpret solar flares as events originating in solar active regions having reached the self-organized critical state, by alternatively using two versions of an "integrated flare model" - one static and one dynamic. In both versions the initial conditions are derived from observations aiming to investigate whether well-known scaling laws observed in the distribution functions of characteristic flare parameters are reproduced after the self-organized critical state has been reached. In the static model, we first apply a nonlinear force-free extrapolation that reconstructs the three-dimensional magnetic fields from two-dimensional vector magnetograms. We then locate magnetic discontinuities exceeding a threshold in the Laplacian of the magnetic field. These discontinuities are relaxed in local diffusion events, implemented in the form of cellular-automaton evolution rules. Subsequent loading and relaxation steps lead the system to self-organized criticality, after which the statistical properties of the simulated events are examined. In the dynamic version we deploy an enhanced driving mechanism, which utilizes the observed evolution of active regions, making use of sequential vector magnetograms. We first apply the static cellular automaton model to consecutive solar vector magnetograms until the self-organized critical state is reached. We then evolve the magnetic field inbetween these processed snapshots through spline interpolation, acting as a natural driver in the dynamic model. The identification of magnetically unstable sites as well as their relaxation follow the same rules as in the static model after each interpolation step. Subsequent interpolation/driving and relaxation steps cover all transitions until the end of the sequence. Physical requirements, such as the divergence-free condition for the magnetic field vector, are approximately satisfied in both versions of the model. We obtain robust power laws in the distribution functions of the modelled

Investigation on Self-Organization Processes in DC Generators by Synergetic Modeling

Directory of Open Access Journals (Sweden)

Ion Voncilă

2014-09-01

Full Text Available In this paper is suggested a new mathematical model, based on which it can be justified the self-excitation DC generators, either shunt or series excitation, by self-organization phenomena that appear to overcome threshold values (self-excitation in these generators is an avalanche process, a positive feedback, considered at first glance uncontrollable.

Organized versus self-organized criticality in the abelian sandpile model

OpenAIRE

Fey-den Boer, AC Anne; Redig, FHJ Frank

2005-01-01

We define stabilizability of an infinite volume height configuration and of a probability measure on height configurations. We show that for high enough densities, a probability measure cannot be stabilized. We also show that in some sense the thermodynamic limit of the uniform measures on the recurrent configurations of the abelian sandpile model (ASM) is a maximal element of the set of stabilizable measures. In that sense the self-organized critical behavior of the ASM can be understood in ...

Turbulence and Self-Organization Modeling Astrophysical Objects

CERN Document Server

Marov, Mikhail Ya

2013-01-01

This book focuses on the development of continuum models of natural turbulent media. It provides a theoretical approach to the solutions of different problems related to the formation, structure and evolution of astrophysical and geophysical objects. A stochastic modeling approach is used in the mathematical treatment of these problems, which reflects self-organization processes in open dissipative systems. The authors also consider examples of ordering for various objects in space throughout their evolutionary processes. This volume is aimed at graduate students and researchers in the fields of mechanics, astrophysics, geophysics, planetary and space science.

Democracy versus dictatorship in self-organized models of financial markets

Science.gov (United States)

D'Hulst, R.; Rodgers, G. J.

2000-06-01

Models to mimic the transmission of information in financial markets are introduced. As an attempt to generate the demand process, we distinguish between dictatorship associations, where groups of agents rely on one of them to make decision, and democratic associations, where each agent takes part in the group decision. In the dictatorship model, agents segregate into two distinct populations, while the democratic model is driven towards a critical state where groups of agents of all sizes exist. Hence, both models display a level of organization, but only the democratic model is self-organized. We show that the dictatorship model generates less-volatile markets than the democratic model.

Self-organized modularization in evolutionary algorithms.

Science.gov (United States)

Dauscher, Peter; Uthmann, Thomas

2005-01-01

The principle of modularization has proven to be extremely successful in the field of technical applications and particularly for Software Engineering purposes. The question to be answered within the present article is whether mechanisms can also be identified within the framework of Evolutionary Computation that cause a modularization of solutions. We will concentrate on processes, where modularization results only from the typical evolutionary operators, i.e. selection and variation by recombination and mutation (and not, e.g., from special modularization operators). This is what we call Self-Organized Modularization. Based on a combination of two formalizations by Radcliffe and Altenberg, some quantitative measures of modularity are introduced. Particularly, we distinguish Built-in Modularity as an inherent property of a genotype and Effective Modularity, which depends on the rest of the population. These measures can easily be applied to a wide range of present Evolutionary Computation models. It will be shown, both theoretically and by simulation, that under certain conditions, Effective Modularity (as defined within this paper) can be a selection factor. This causes Self-Organized Modularization to take place. The experimental observations emphasize the importance of Effective Modularity in comparison with Built-in Modularity. Although the experimental results have been obtained using a minimalist toy model, they can lead to a number of consequences for existing models as well as for future approaches. Furthermore, the results suggest a complex self-amplification of highly modular equivalence classes in the case of respected relations. Since the well-known Holland schemata are just the equivalence classes of respected relations in most Simple Genetic Algorithms, this observation emphasizes the role of schemata as Building Blocks (in comparison with arbitrary subsets of the search space).

Self-organized service negotiation for collaborative decision making.

Science.gov (United States)

Zhang, Bo; Huang, Zhenhua; Zheng, Ziming

2014-01-01

This paper proposes a self-organized service negotiation method for CDM in intelligent and automatic manners. It mainly includes three phases: semantic-based capacity evaluation for the CDM sponsor, trust computation of the CDM organization, and negotiation selection of the decision-making service provider (DMSP). In the first phase, the CDM sponsor produces the formal semantic description of the complex decision task for DMSP and computes the capacity evaluation values according to participator instructions from different DMSPs. In the second phase, a novel trust computation approach is presented to compute the subjective belief value, the objective reputation value, and the recommended trust value. And in the third phase, based on the capacity evaluation and trust computation, a negotiation mechanism is given to efficiently implement the service selection. The simulation experiment results show that our self-organized service negotiation method is feasible and effective for CDM.

Modeling Poroelastic Wave Propagation in a Real 2-D Complex Geological Structure Obtained via Self-Organizing Maps

Science.gov (United States)

Itzá Balam, Reymundo; Iturrarán-Viveros, Ursula; Parra, Jorge O.

2018-03-01

Two main stages of seismic modeling are geological model building and numerical computation of seismic response for the model. The quality of the computed seismic response is partly related to the type of model that is built. Therefore, the model building approaches become as important as seismic forward numerical methods. For this purpose, three petrophysical facies (sands, shales and limestones) are extracted from reflection seismic data and some seismic attributes via the clustering method called Self-Organizing Maps (SOM), which, in this context, serves as a geological model building tool. This model with all its properties is the input to the Optimal Implicit Staggered Finite Difference (OISFD) algorithm to create synthetic seismograms for poroelastic, poroacoustic and elastic media. The results show a good agreement between observed and 2-D synthetic seismograms. This demonstrates that the SOM classification method enables us to extract facies from seismic data and allows us to integrate the lithology at the borehole scale with the 2-D seismic data.

Self-organized Criticality Model for Ocean Internal Waves

International Nuclear Information System (INIS)

Wang Gang; Hou Yijun; Lin Min; Qiao Fangli

2009-01-01

In this paper, we present a simple spring-block model for ocean internal waves based on the self-organized criticality (SOC). The oscillations of the water blocks in the model display power-law behavior with an exponent of -2 in the frequency domain, which is similar to the current and sea water temperature spectra in the actual ocean and the universal Garrett and Munk deep ocean internal wave model [Geophysical Fluid Dynamics 2 (1972) 225; J. Geophys. Res. 80 (1975) 291]. The influence of the ratio of the driving force to the spring coefficient to SOC behaviors in the model is also discussed. (general)

Dynamic data-driven integrated flare model based on self-organized criticality

Science.gov (United States)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M. K.

2013-05-01

Context. We interpret solar flares as events originating in active regions that have reached the self-organized critical state. We describe them with a dynamic integrated flare model whose initial conditions and driving mechanism are derived from observations. Aims: We investigate whether well-known scaling laws observed in the distribution functions of characteristic flare parameters are reproduced after the self-organized critical state has been reached. Methods: To investigate whether the distribution functions of total energy, peak energy, and event duration follow the expected scaling laws, we first applied the previously reported static cellular automaton model to a time series of seven solar vector magnetograms of the NOAA active region 8210 recorded by the Imaging Vector Magnetograph on May 1 1998 between 18:59 UT and 23:16 UT until the self-organized critical state was reached. We then evolved the magnetic field between these processed snapshots through spline interpolation, mimicking a natural driver in our dynamic model. We identified magnetic discontinuities that exceeded a threshold in the Laplacian of the magnetic field after each interpolation step. These discontinuities were relaxed in local diffusion events, implemented in the form of cellular automaton evolution rules. Subsequent interpolation and relaxation steps covered all transitions until the end of the processed magnetograms' sequence. We additionally advanced each magnetic configuration that has reached the self-organized critical state (SOC configuration) by the static model until 50 more flares were triggered, applied the dynamic model again to the new sequence, and repeated the same process sufficiently often to generate adequate statistics. Physical requirements, such as the divergence-free condition for the magnetic field, were approximately imposed. Results: We obtain robust power laws in the distribution functions of the modeled flaring events with scaling indices that agree well

Atmospheric Convective Organization: Self-Organized Criticality or Homeostasis?

Science.gov (United States)

Yano, Jun-Ichi

2015-04-01

Atmospheric convection has a tendency organized on a hierarchy of scales ranging from the mesoscale to the planetary scales, with the latter especially manifested by the Madden-Julian oscillation. The present talk examines two major possible mechanisms of self-organization identified in wider literature from a phenomenological thermodynamic point of view by analysing a planetary-scale cloud-resolving model simulation. The first mechanism is self-organized criticality. A saturation tendency of precipitation rate with the increasing column-integrated water, reminiscence of critical phenomena, indicates self-organized criticality. The second is a self-regulation mechanism that is known as homeostasis in biology. A thermodynamic argument suggests that such self-regulation maintains the column-integrated water below a threshold by increasing the precipitation rate. Previous analyses of both observational data as well as cloud-resolving model (CRM) experiments give mixed results. A satellite data analysis suggests self-organized criticality. Some observational data as well as CRM experiments support homeostasis. Other analyses point to a combination of these two interpretations. In this study, a CRM experiment over a planetary-scale domain with a constant sea-surface temperature is analyzed. This analysis shows that the relation between the column-integrated total water and precipitation suggests self-organized criticality, whereas the one between the column-integrated water vapor and precipitation suggests homeostasis. The concurrent presence of these two mechanisms are further elaborated by detailed statistical and budget analyses. These statistics are scale invariant, reflecting a spatial scaling of precipitation processes. These self-organization mechanisms are most likely be best theoretically understood by the energy cycle of the convective systems consisting of the kinetic energy and the cloud-work function. The author has already investigated the behavior of this

Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

Science.gov (United States)

Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

2018-02-01

Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

Self-correcting quantum computers

International Nuclear Information System (INIS)

Bombin, H; Chhajlany, R W; Horodecki, M; Martin-Delgado, M A

2013-01-01

Is the notion of a quantum computer (QC) resilient to thermal noise unphysical? We address this question from a constructive perspective and show that local quantum Hamiltonian models provide self-correcting QCs. To this end, we first give a sufficient condition on the connectedness of excitations for a stabilizer code model to be a self-correcting quantum memory. We then study the two main examples of topological stabilizer codes in arbitrary dimensions and establish their self-correcting capabilities. Also, we address the transversality properties of topological color codes, showing that six-dimensional color codes provide a self-correcting model that allows the transversal and local implementation of a universal set of operations in seven spatial dimensions. Finally, we give a procedure for initializing such quantum memories at finite temperature. (paper)

Self-organized dynamics in local load-sharing fiber bundle models.

Science.gov (United States)

Biswas, Soumyajyoti; Chakrabarti, Bikas K

2013-10-01

We study the dynamics of a local load-sharing fiber bundle model in two dimensions under an external load (which increases with time at a fixed slow rate) applied at a single point. Due to the local load-sharing nature, the redistributed load remains localized along the boundary of the broken patch. The system then goes to a self-organized state with a stationary average value of load per fiber along the (increasing) boundary of the broken patch (damaged region) and a scale-free distribution of avalanche sizes and other related quantities are observed. In particular, when the load redistribution is only among nearest surviving fiber(s), the numerical estimates of the exponent values are comparable with those of the Manna model. When the load redistribution is uniform along the patch boundary, the model shows a simple mean-field limit of this self-organizing critical behavior, for which we give analytical estimates of the saturation load per fiber values and avalanche size distribution exponent. These are in good agreement with numerical simulation results.

Self-organizing sensing and actuation for automatic control

Science.gov (United States)

Cheng, George Shu-Xing

2017-07-04

A Self-Organizing Process Control Architecture is introduced with a Sensing Layer, Control Layer, Actuation Layer, Process Layer, as well as Self-Organizing Sensors (SOS) and Self-Organizing Actuators (SOA). A Self-Organizing Sensor for a process variable with one or multiple input variables is disclosed. An artificial neural network (ANN) based dynamic modeling mechanism as part of the Self-Organizing Sensor is described. As a case example, a Self-Organizing Soft-Sensor for CFB Boiler Bed Height is presented. Also provided is a method to develop a Self-Organizing Sensor.

A computational cognitive model of self-efficacy and daily adherence in mHealth.

Science.gov (United States)

Pirolli, Peter

2016-12-01

Mobile health (mHealth) applications provide an excellent opportunity for collecting rich, fine-grained data necessary for understanding and predicting day-to-day health behavior change dynamics. A computational predictive model (ACT-R-DStress) is presented and fit to individual daily adherence in 28-day mHealth exercise programs. The ACT-R-DStress model refines the psychological construct of self-efficacy. To explain and predict the dynamics of self-efficacy and predict individual performance of targeted behaviors, the self-efficacy construct is implemented as a theory-based neurocognitive simulation of the interaction of behavioral goals, memories of past experiences, and behavioral performance.

Human Inspired Self-developmental Model of Neural Network (HIM): Introducing Content/Form Computing

Science.gov (United States)

Krajíček, Jiří

This paper presents cross-disciplinary research between medical/psychological evidence on human abilities and informatics needs to update current models in computer science to support alternative methods for computation and communication. In [10] we have already proposed hypothesis introducing concept of human information model (HIM) as cooperative system. Here we continue on HIM design in detail. In our design, first we introduce Content/Form computing system which is new principle of present methods in evolutionary computing (genetic algorithms, genetic programming). Then we apply this system on HIM (type of artificial neural network) model as basic network self-developmental paradigm. Main inspiration of our natural/human design comes from well known concept of artificial neural networks, medical/psychological evidence and Sheldrake theory of "Nature as Alive" [22].

Self-organizing of critical state in granulated superconductors

International Nuclear Information System (INIS)

Ginzburg, S.L.; Savitskaya, N.E.

2000-01-01

Critical state in granulated superconductors was studied on the basis of two mathematical models - the system of differential equations for calibration and invariant difference of phases and a simplified model describing the system of associated images and equivalent to the standard models to study self-organizing criticality. The critical state of granulated superconductors in all studied cases was shown to be self-organized. Besides, it is shown that the applied models are practically equivalent ones, that is they both show similar critical behavior and lead to coincidence of noncritical phenomena. For the first time one showed that the occurrence of self-organized critically within the system of nonlinear differential equations and its equivalence to self-organized critically in the standard models [ru

Non parametric, self organizing, scalable modeling of spatiotemporal inputs: the sign language paradigm.

Science.gov (United States)

Caridakis, G; Karpouzis, K; Drosopoulos, A; Kollias, S

2012-12-01

Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost. Copyright © 2012 Elsevier Ltd. All rights reserved.

Macromolecular target prediction by self-organizing feature maps.

Science.gov (United States)

Schneider, Gisbert; Schneider, Petra

2017-03-01

Rational drug discovery would greatly benefit from a more nuanced appreciation of the activity of pharmacologically active compounds against a diverse panel of macromolecular targets. Already, computational target-prediction models assist medicinal chemists in library screening, de novo molecular design, optimization of active chemical agents, drug re-purposing, in the spotting of potential undesired off-target activities, and in the 'de-orphaning' of phenotypic screening hits. The self-organizing map (SOM) algorithm has been employed successfully for these and other purposes. Areas covered: The authors recapitulate contemporary artificial neural network methods for macromolecular target prediction, and present the basic SOM algorithm at a conceptual level. Specifically, they highlight consensus target-scoring by the employment of multiple SOMs, and discuss the opportunities and limitations of this technique. Expert opinion: Self-organizing feature maps represent a straightforward approach to ligand clustering and classification. Some of the appeal lies in their conceptual simplicity and broad applicability domain. Despite known algorithmic shortcomings, this computational target prediction concept has been proven to work in prospective settings with high success rates. It represents a prototypic technique for future advances in the in silico identification of the modes of action and macromolecular targets of bioactive molecules.

A self-taught artificial agent for multi-physics computational model personalization.

Science.gov (United States)

Neumann, Dominik; Mansi, Tommaso; Itu, Lucian; Georgescu, Bogdan; Kayvanpour, Elham; Sedaghat-Hamedani, Farbod; Amr, Ali; Haas, Jan; Katus, Hugo; Meder, Benjamin; Steidl, Stefan; Hornegger, Joachim; Comaniciu, Dorin

2016-12-01

Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious, time-consuming, model- and data-specific process. We propose to use artificial intelligence concepts to learn this task, inspired by how human experts manually perform it. The problem is reformulated in terms of reinforcement learning. In an off-line phase, Vito, our self-taught artificial agent, learns a representative decision process model through exploration of the computational model: it learns how the model behaves under change of parameters. The agent then automatically learns an optimal strategy for on-line personalization. The algorithm is model-independent; applying it to a new model requires only adjusting few hyper-parameters of the agent and defining the observations to match. The full knowledge of the model itself is not required. Vito was tested in a synthetic scenario, showing that it could learn how to optimize cost functions generically. Then Vito was applied to the inverse problem of cardiac electrophysiology and the personalization of a whole-body circulation model. The obtained results suggested that Vito could achieve equivalent, if not better goodness of fit than standard methods, while being more robust (up to 11% higher success rates) and with faster (up to seven times) convergence rate. Our artificial intelligence approach could thus make personalization algorithms generalizable and self-adaptable to any patient and any model. Copyright © 2016. Published by Elsevier B.V.

Computational design of active, self-reinforcing gels.

Science.gov (United States)

Yashin, Victor V; Kuksenok, Olga; Balazs, Anna C

2010-05-20

Many living organisms have evolved a protective mechanism that allows them to reversibly alter their stiffness in response to mechanical contact. Using theoretical modeling, we design a mechanoresponsive polymer gel that exhibits a similar self-reinforcing behavior. We focus on cross-linked gels that contain Ru(terpy)(2) units, where both terpyridine ligands are grafted to the chains. The Ru(terpy)(2) complex forms additional, chemoresponsive cross-links that break and re-form in response to a repeated oxidation and reduction of the Ru. In our model, the periodic redox variations of the anchored metal ion are generated by the Belousov-Zhabotinsky (BZ) reaction. Our computer simulations reveal that compression of the BZ gel leads to a stiffening of the sample due to an increase in the cross-link density. These findings provide guidelines for designing biomimetic, active coatings that send out a signal when the system is impacted and use this signaling process to initiate the self-protecting behavior.

Modeling of Instabilities and Self-organization at the Frictional Interface

Science.gov (United States)

Mortazavi, Vahid

frictional surface to exhibit "self-protection" and "self-healing" properties. Hence, this research is dealing with the fundamental concepts that allow the possibility of the development of a new generation of tribosystem and materials that reinforce such properties. In chapter 2, we investigate instabilities due to the temperature-dependency of the coefficient of friction. The temperature-dependency of the coefficient of friction can have a significant effect on the frictional sliding stability, by leading to the formation of "hot" and "cold" spots on the contacting surfaces. We formulate a stability criterion and perform a case study of a brake disk. In chapter 3, we study frictional running-in. Running-in is a transient period on the onset of the frictional sliding, in which friction and wear decrease to their stationary values. In this research, running-in is interpreted as friction-induced self-organization process. We introduce a theoretical model of running-in and investigate rough profile evolution assuming that its kinetics is driven by two opposite processes or events, i.e., smoothening which is typical for the deformation-driven friction and wear, and roughening which is typical for the adhesion-driven friction and wear. In chapter 4, we investigate the possibility of the so-called Turing-type pattern formation during friction. Turing or reaction-diffusion systems describe variations of spatial concentrations of chemical components with time due to local chemical reactions coupled with diffusion. During friction, the patterns can form at the sliding interface due to the mass transfer (diffusion), heat transfer, various tribochemical reactions, and wear. In chapter 5, we investigate how interfacial patterns including propagating trains of stick and slip zones form due to dynamic sliding instabilities. These can be categorized as self-organized patterns. We treat stick and slip as two phases at the interface, and study the effects related to phase transitions. Our

Instantons in Self-Organizing Logic Gates

Science.gov (United States)

Bearden, Sean R. B.; Manukian, Haik; Traversa, Fabio L.; Di Ventra, Massimiliano

2018-03-01

Self-organizing logic is a recently suggested framework that allows the solution of Boolean truth tables "in reverse"; i.e., it is able to satisfy the logical proposition of gates regardless to which terminal(s) the truth value is assigned ("terminal-agnostic logic"). It can be realized if time nonlocality (memory) is present. A practical realization of self-organizing logic gates (SOLGs) can be done by combining circuit elements with and without memory. By employing one such realization, we show, numerically, that SOLGs exploit elementary instantons to reach equilibrium points. Instantons are classical trajectories of the nonlinear equations of motion describing SOLGs and connect topologically distinct critical points in the phase space. By linear analysis at those points, we show that these instantons connect the initial critical point of the dynamics, with at least one unstable direction, directly to the final fixed point. We also show that the memory content of these gates affects only the relaxation time to reach the logically consistent solution. Finally, we demonstrate, by solving the corresponding stochastic differential equations, that, since instantons connect critical points, noise and perturbations may change the instanton trajectory in the phase space but not the initial and final critical points. Therefore, even for extremely large noise levels, the gates self-organize to the correct solution. Our work provides a physical understanding of, and can serve as an inspiration for, models of bidirectional logic gates that are emerging as important tools in physics-inspired, unconventional computing.

Self-Organizing Robots

CERN Document Server

Murata, Satoshi

2012-01-01

It is man’s ongoing hope that a machine could somehow adapt to its environment by reorganizing itself. This is what the notion of self-organizing robots is based on. The theme of this book is to examine the feasibility of creating such robots within the limitations of current mechanical engineering. The topics comprise the following aspects of such a pursuit: the philosophy of design of self-organizing mechanical systems; self-organization in biological systems; the history of self-organizing mechanical systems; a case study of a self-assembling/self-repairing system as an autonomous distributed system; a self-organizing robot that can create its own shape and robotic motion; implementation and instrumentation of self-organizing robots; and the future of self-organizing robots. All topics are illustrated with many up-to-date examples, including those from the authors’ own work. The book does not require advanced knowledge of mathematics to be understood, and will be of great benefit to students in the rob...

Self-Organization and the Self-Assembling Process in Tissue Engineering

Science.gov (United States)

Eswaramoorthy, Rajalakshmanan; Hadidi, Pasha; Hu, Jerry C.

2015-01-01

In recent years, the tissue engineering paradigm has shifted to include a new and growing subfield of scaffoldless techniques which generate self-organizing and self-assembling tissues. This review aims to provide a cogent description of this relatively new research area, with special emphasis on applications toward clinical use and research models. Particular emphasis is placed on providing clear definitions of self-organization and the self-assembling process, as delineated from other scaffoldless techniques in tissue engineering and regenerative medicine. Significantly, during formation, self-organizing and self-assembling tissues display biological processes similar to those that occur in vivo. These help lead to the recapitulation of native tissue morphological structure and organization. Notably, functional properties of these tissues also approach native tissue values; some of these engineered tissues are already in clinical trials. This review aims to provide a cohesive summary of work in this field, and to highlight the potential of self-organization and the self-assembling process to provide cogent solutions to current intractable problems in tissue engineering. PMID:23701238

DNA Self-Assembly and Computation Studied with a Coarse-grained Dynamic Bonded Model

DEFF Research Database (Denmark)

Svaneborg, Carsten; Fellermann, Harold; Rasmussen, Steen

2012-01-01

We utilize a coarse-grained directional dynamic bonding DNA model [C. Svaneborg, Comp. Phys. Comm. (In Press DOI:10.1016/j.cpc.2012.03.005)] to study DNA self-assembly and DNA computation. In our DNA model, a single nucleotide is represented by a single interaction site, and complementary sites can...

Hierarchical organization versus self-organization

OpenAIRE

Busseniers, Evo

2014-01-01

In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition.

Directory of Open Access Journals (Sweden)

Johannes Bill

Full Text Available During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

Science.gov (United States)

Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

2015-01-01

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

Self-organization of domain growth in the Ising model with impurities

DEFF Research Database (Denmark)

Andersen, Jørgen Vitting; Mouritsen, Ole G.

1992-01-01

We have studied avalanchelike rearrangements of domain patterns in the two-dimensional Ising model with static impurities, which is quenched to low temperatures. When breaking the up-down symmetry of the spins by a small applied field, the mere fluctuation of a single spin eventually results...... in a cascade of spin flips at the domain boundaries. We have analyzed the lifetime and size distribution functions for the avalanches and related the results to the general phenomena of self-organized criticality and to recent experiments on cellular magnetic domain patterns in magnetic garnet films. Our...... results suggest that the self-organized state in this system appears to be subcritical, in agreement with a recent theory....

Complexity in plasma: From self-organization to geodynamo

International Nuclear Information System (INIS)

Sato, T.

1996-01-01

A central theme of open-quote open-quote Complexity close-quote close-quote is the question of the creation of ordered structure in nature (self-organization). The assertion is made that self-organization is governed by three key processes, i.e., energy pumping, entropy expulsion and nonlinearity. Extensive efforts have been done to confirm this assertion through computer simulations of plasmas. A system exhibits markedly different features in self-organization, depending on whether the energy pumping is instantaneous or continuous, or whether the produced entropy is expulsed or reserved. The nonlinearity acts to bring a nonequilibrium state into a bifurcation, thus resulting in a new structure along with an anomalous entropy production. As a practical application of our grand view of self-organization a preferential generation of a dipole magnetic field is successfully demonstrated. copyright 1996 American Institute of Physics

Modeling financial markets by self-organized criticality

Science.gov (United States)

Biondo, Alessio Emanuele; Pluchino, Alessandro; Rapisarda, Andrea

2015-10-01

We present a financial market model, characterized by self-organized criticality, that is able to generate endogenously a realistic price dynamics and to reproduce well-known stylized facts. We consider a community of heterogeneous traders, composed by chartists and fundamentalists, and focus on the role of informative pressure on market participants, showing how the spreading of information, based on a realistic imitative behavior, drives contagion and causes market fragility. In this model imitation is not intended as a change in the agent's group of origin, but is referred only to the price formation process. We introduce in the community also a variable number of random traders in order to study their possible beneficial role in stabilizing the market, as found in other studies. Finally, we also suggest some counterintuitive policy strategies able to dampen fluctuations by means of a partial reduction of information.

Self-Organized Criticality Theory Model of Thermal Sandpile

International Nuclear Information System (INIS)

Peng Xiao-Dong; Qu Hong-Peng; Xu Jian-Qiang; Han Zui-Jiao

2015-01-01

A self-organized criticality model of a thermal sandpile is formulated for the first time to simulate the dynamic process with interaction between avalanche events on the fast time scale and diffusive transports on the slow time scale. The main characteristics of the model are that both particle and energy avalanches of sand grains are considered simultaneously. Properties of intermittent transport and improved confinement are analyzed in detail. The results imply that the intermittent phenomenon such as blobs in the low confinement mode as well as edge localized modes in the high confinement mode observed in tokamak experiments are not only determined by the edge plasma physics, but also affected by the core plasma dynamics. (paper)

Self-Organized Transport System

Science.gov (United States)

2009-09-28

This report presents the findings of the simulation model for a self-organized transport system where traffic lights communicate with neighboring traffic lights and make decisions locally to adapt to traffic conditions in real time. The model is insp...

Facilitating computer supported cooperative work with socio-technical self-descriptions

OpenAIRE

Kunau, Gabriele

2006-01-01

How can the concept of self-description from newer systems theory be used for improving the co-evolvement of software engineering and organizational change in CSCW-projects? This thesis suggests transferring the concept of self-description into a concept of socio-technical self-description allowing an organization to describe its own computer supported work processes. The presentation of results is organized in four steps: First, a theoretical foundation is elaborated; second, an initial meth...

Crossover to self-organized criticality in an inertial sandpile model

OpenAIRE

Head, DA; Rodgers, GJ

1996-01-01

We introduce a one-dimensional sandpile model which incorporates particle inertia. The inertial dynamics are governed by a new parameter which, as it passes through a threshold value, alters the toppling dynamics in such a way that the system no longer evolves to a self-organized critical state. A range of mean-field theories based on a kinetic equation approach is presented which confirm the numerical findings. We conclude by considering the physical applications of this model, particularly ...

Origin and evolution of the self-organizing cytoskeleton in the network of eukaryotic organelles.

Science.gov (United States)

Jékely, Gáspár

2014-09-02

The eukaryotic cytoskeleton evolved from prokaryotic cytomotive filaments. Prokaryotic filament systems show bewildering structural and dynamic complexity and, in many aspects, prefigure the self-organizing properties of the eukaryotic cytoskeleton. Here, the dynamic properties of the prokaryotic and eukaryotic cytoskeleton are compared, and how these relate to function and evolution of organellar networks is discussed. The evolution of new aspects of filament dynamics in eukaryotes, including severing and branching, and the advent of molecular motors converted the eukaryotic cytoskeleton into a self-organizing "active gel," the dynamics of which can only be described with computational models. Advances in modeling and comparative genomics hold promise of a better understanding of the evolution of the self-organizing cytoskeleton in early eukaryotes, and its role in the evolution of novel eukaryotic functions, such as amoeboid motility, mitosis, and ciliary swimming. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.

Parallel computing in enterprise modeling.

Energy Technology Data Exchange (ETDEWEB)

Goldsby, Michael E.; Armstrong, Robert C.; Shneider, Max S.; Vanderveen, Keith; Ray, Jaideep; Heath, Zach; Allan, Benjamin A.

2008-08-01

This report presents the results of our efforts to apply high-performance computing to entity-based simulations with a multi-use plugin for parallel computing. We use the term 'Entity-based simulation' to describe a class of simulation which includes both discrete event simulation and agent based simulation. What simulations of this class share, and what differs from more traditional models, is that the result sought is emergent from a large number of contributing entities. Logistic, economic and social simulations are members of this class where things or people are organized or self-organize to produce a solution. Entity-based problems never have an a priori ergodic principle that will greatly simplify calculations. Because the results of entity-based simulations can only be realized at scale, scalable computing is de rigueur for large problems. Having said that, the absence of a spatial organizing principal makes the decomposition of the problem onto processors problematic. In addition, practitioners in this domain commonly use the Java programming language which presents its own problems in a high-performance setting. The plugin we have developed, called the Parallel Particle Data Model, overcomes both of these obstacles and is now being used by two Sandia frameworks: the Decision Analysis Center, and the Seldon social simulation facility. While the ability to engage U.S.-sized problems is now available to the Decision Analysis Center, this plugin is central to the success of Seldon. Because Seldon relies on computationally intensive cognitive sub-models, this work is necessary to achieve the scale necessary for realistic results. With the recent upheavals in the financial markets, and the inscrutability of terrorist activity, this simulation domain will likely need a capability with ever greater fidelity. High-performance computing will play an important part in enabling that greater fidelity.

Self-organized criticality in asymmetric exclusion model with noise for freeway traffic

Science.gov (United States)

Nagatani, Takashi

1995-02-01

The one-dimensional asymmetric simple-exclusion model with open boundaries for parallel update is extended to take into account temporary stopping of particles. The model presents the traffic flow on a highway with temporary deceleration of cars. Introducing temporary stopping into the asymmetric simple-exclusion model drives the system asymptotically into a steady state exhibiting a self-organized criticality. In the self-organized critical state, start-stop waves (or traffic jams) appear with various sizes (or lifetimes). The typical interval between consecutive jams scales as ≃ Lv with v = 0.51 ± 0.05 where L is the system size. It is shown that the cumulative jam-interval distribution Ns( L) satisfies the finite-size scaling form ( Ns( L) ≃ L- vf( s/ Lv). Also, the typical lifetime ≃ Lv‧ with v‧ = 0.52 ± 0.05. The cumulative distribution Nm( L) of lifetimes satisfies the finite-size scaling form Nm( L)≃ L-1g( m/ Lv‧).

Exploring the patterns and evolution of self-organized urban street networks through modeling

Science.gov (United States)

Rui, Yikang; Ban, Yifang; Wang, Jiechen; Haas, Jan

2013-03-01

As one of the most important subsystems in cities, urban street networks have recently been well studied by using the approach of complex networks. This paper proposes a growing model for self-organized urban street networks. The model involves a competition among new centers with different values of attraction radius and a local optimal principle of both geometrical and topological factors. We find that with the model growth, the local optimization in the connection process and appropriate probability for the loop construction well reflect the evolution strategy in real-world cities. Moreover, different values of attraction radius in centers competition process lead to morphological change in patterns including urban network, polycentric and monocentric structures. The model succeeds in reproducing a large diversity of road network patterns by varying parameters. The similarity between the properties of our model and empirical results implies that a simple universal growth mechanism exists in self-organized cities.

9th Workshop on Self-Organizing Maps

CERN Document Server

Príncipe, José; Zegers, Pablo

2013-01-01

Self-organizing maps (SOMs) were developed by Teuvo Kohonen in the early eighties. Since then more than 10,000 works have been based on SOMs. SOMs are unsupervised neural networks useful for clustering and visualization purposes. Many SOM applications have been developed in engineering and science, and other fields. This book contains refereed papers presented at the 9th Workshop on Self-Organizing Maps (WSOM 2012) held at the Universidad de Chile, Santiago, Chile, on December 12-14, 2012. The workshop brought together researchers and practitioners in the field of self-organizing systems. Among the book chapters there are excellent examples of the use of SOMs in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis, and time series analysis. Other chapters present the latest theoretical work on SOMs as well as Learning Vector Quantization (LVQ) methods.

Self organized criticality

International Nuclear Information System (INIS)

Creutz, M.

1993-03-01

Self organized criticality refers to the tendency of highly dissipative systems to drive themselves to a critical state. This has been proposed to explain why observed physics often displays a wide disparity of length and time scales. The phenomenon can be studied in simple cellular automaton models

Mechanisms of self-organization and finite size effects in a minimal agent based model

International Nuclear Information System (INIS)

Alfi, V; Cristelli, M; Pietronero, L; Zaccaria, A

2009-01-01

We present a detailed analysis of the self-organization phenomenon in which the stylized facts originate from finite size effects with respect to the number of agents considered and disappear in the limit of an infinite population. By introducing the possibility that agents can enter or leave the market depending on the behavior of the price, it is possible to show that the system self-organizes in a regime with a finite number of agents which corresponds to the stylized facts. The mechanism for entering or leaving the market is based on the idea that a too stable market is unappealing for traders, while the presence of price movements attracts agents to enter and speculate on the market. We show that this mechanism is also compatible with the idea that agents are scared by a noisy and risky market at shorter timescales. We also show that the mechanism for self-organization is robust with respect to variations of the exit/entry rules and that the attempt to trigger the system to self-organize in a region without stylized facts leads to an unrealistic dynamics. We study the self-organization in a specific agent based model but we believe that the basic ideas should be of general validity

A Model of Self-Organizing Head-Centered Visual Responses in Primate Parietal Areas

Science.gov (United States)

Mender, Bedeho M. W.; Stringer, Simon M.

2013-01-01

We present a hypothesis for how head-centered visual representations in primate parietal areas could self-organize through visually-guided learning, and test this hypothesis using a neural network model. The model consists of a competitive output layer of neurons that receives afferent synaptic connections from a population of input neurons with eye position gain modulated retinal receptive fields. The synaptic connections in the model are trained with an associative trace learning rule which has the effect of encouraging output neurons to learn to respond to subsets of input patterns that tend to occur close together in time. This network architecture and synaptic learning rule is hypothesized to promote the development of head-centered output neurons during periods of time when the head remains fixed while the eyes move. This hypothesis is demonstrated to be feasible, and each of the core model components described is tested and found to be individually necessary for successful self-organization. PMID:24349064

Organic Computing

CERN Document Server

Würtz, Rolf P

2008-01-01

Organic Computing is a research field emerging around the conviction that problems of organization in complex systems in computer science, telecommunications, neurobiology, molecular biology, ethology, and possibly even sociology can be tackled scientifically in a unified way. From the computer science point of view, the apparent ease in which living systems solve computationally difficult problems makes it inevitable to adopt strategies observed in nature for creating information processing machinery. In this book, the major ideas behind Organic Computing are delineated, together with a sparse sample of computational projects undertaken in this new field. Biological metaphors include evolution, neural networks, gene-regulatory networks, networks of brain modules, hormone system, insect swarms, and ant colonies. Applications are as diverse as system design, optimization, artificial growth, task allocation, clustering, routing, face recognition, and sign language understanding.

Scaling, phase transitions, and nonuniversality in a self-organized critical cellular-automaton model

International Nuclear Information System (INIS)

Christensen, K.; Olami, Z.

1992-01-01

We present a two-dimensional continuous cellular automaton that is equivalent to a driven spring-block model. Both the conservation and the anisotropy in the model are controllable quantities. Above a critical level of conservation, the model exhibits self-organized criticality. The self-organization of this system and hence the critical exponents depend on the conservation and the boundary conditions. In the critical isotropic nonconservative phase, the exponents change continuously as a function of conservation. Furthermore, the exponents vary continuously when changing the boundary conditions smoothly. Consequently, there is no universality of the critical exponents. We discuss the relevance of this for earthquakes. Introducing anisotropy changes the scaling of the distribution function, but not the power-law exponent. We explore the phase diagram of this model. We find that at low conservation levels a localization transition occurs. We see two additional phase transitions. The first is seen when moving from the conservative into the nonconservative model. The second appears when passing from the anisotropic two-dimensional system to the purely one-dimensional system

On modeling complex interplay in small-scale self-organized socio-hydrological systems

Science.gov (United States)

Muneepeerakul, Rachata

2017-04-01

Successful and sustainable socio-hydrological systems, as in any coupled natural human-systems, require effective governance, which depends on the existence of proper infrastructure (both hard and soft). Recent work has addressed systems in which resource users and the organization responsible for maintaining the infrastructure are separate entities. However, many socio-hydrological systems, especially in developing countries, are small and without such formal division of labor; rather, such division of labor typically arises from self-organization within the population. In this work, we modify and mathematically operationalize a conceptual framework by developing a system of differential equations that capture the strategic behavior within such a self-organized population, its interplay with infrastructure characteristics and hydrological dynamics, and feedbacks between these elements. The model yields a number of insightful conditions related to long-term sustainability and collapse of the socio-hydrological system in the form of relationships between biophysical and social factors. These relationships encapsulate nonlinear interactions of these factors. The modeling framework is grounded in a solid conceptual foundation upon which additional modifications and realism can be built for potential reconciliation between socio-hydrology with other related fields and further applications.

Self-Organized Criticality and Mass Extinction in Evolutionary Algorithms

DEFF Research Database (Denmark)

Krink, Thiemo; Thomsen, Rene

2001-01-01

The gaps in the fossil record gave rise to the hypothesis that evolution proceeded in long periods of stasis, which alternated with occasional, rapid changes that yielded evolutionary progress. One mechanism that could cause these punctuated bursts is the re-colonbation of changing and deserted...... at a critical state between chaos and order, known as self-organized criticality (SOC). Based on this background, we used SOC to control the size of spatial extinction zones in a diffusion model. The SOC selection process was easy to implement and implied only negligible computational costs. Our results show...

Experimental Demonstration of a Self-organized Architecture for Emerging Grid Computing Applications on OBS Testbed

Science.gov (United States)

Liu, Lei; Hong, Xiaobin; Wu, Jian; Lin, Jintong

As Grid computing continues to gain popularity in the industry and research community, it also attracts more attention from the customer level. The large number of users and high frequency of job requests in the consumer market make it challenging. Clearly, all the current Client/Server(C/S)-based architecture will become unfeasible for supporting large-scale Grid applications due to its poor scalability and poor fault-tolerance. In this paper, based on our previous works [1, 2], a novel self-organized architecture to realize a highly scalable and flexible platform for Grids is proposed. Experimental results show that this architecture is suitable and efficient for consumer-oriented Grids.

Dynamical system with plastic self-organized velocity field as an alternative conceptual model of a cognitive system.

Science.gov (United States)

Janson, Natalia B; Marsden, Christopher J

2017-12-05

It is well known that architecturally the brain is a neural network, i.e. a collection of many relatively simple units coupled flexibly. However, it has been unclear how the possession of this architecture enables higher-level cognitive functions, which are unique to the brain. Here, we consider the brain from the viewpoint of dynamical systems theory and hypothesize that the unique feature of the brain, the self-organized plasticity of its architecture, could represent the means of enabling the self-organized plasticity of its velocity vector field. We propose that, conceptually, the principle of cognition could amount to the existence of appropriate rules governing self-organization of the velocity field of a dynamical system with an appropriate account of stimuli. To support this hypothesis, we propose a simple non-neuromorphic mathematical model with a plastic self-organized velocity field, which has no prototype in physical world. This system is shown to be capable of basic cognition, which is illustrated numerically and with musical data. Our conceptual model could provide an additional insight into the working principles of the brain. Moreover, hardware implementations of plastic velocity fields self-organizing according to various rules could pave the way to creating artificial intelligence of a novel type.

Self-organization phenomena in plasma physics

International Nuclear Information System (INIS)

Sanduloviciu, M.; Popescu, S.

2001-01-01

The self-assembling in nature and laboratory of structures in systems away from thermodynamic equilibrium is one of the problems that mostly fascinates the scientists working in all branches of science. In this context a substantial progress has been obtained by investigating the appearance of spatial and spatiotemporal patterns in plasma. These experiments revealed the presence of a scenario of self-organization able to suggest an answer to the central problem of the 'Science of Complexity', why matter transits spontaneously from a disordered into an ordered state? Based on this scenario of self-organization we present arguments proving the possibility to explain the challenging problems of nonequilibrium physics in general. These problems refer to: (i) genuine origin of phase transitions observed in gaseous conductors and semiconductors; (ii) the elucidation of the role played by self-organization in the simulation of oscillations; (iii) the physical basis of anomalous transport of matter and energy with special reference to the possibilities of improving the economical performance of fusion devices; (iv) the possibility to use self-confined gaseous space charged configurations as an alternative to the magnetically confined plasma used at present in fusion devices. In other branches of sciences, as for instance in Biology, the self-organization scenario reveals a new insight into a mechanism able to explain the appearance of the simplest possible space charge configuration able to evolve, under suitable conditions, into prebiotic structures. Referring to phenomena observed in nature, the same self-organization scenario suggests plausible answers to the appearance of ball lightening but also to the origin of the flickering phenomena observed in the light emission of the Sun and stars. For theory the described self-organization scenario offers a new physical basis for many problems of nonlinear science not solved yet and also a new model for the so-called 'self

Self-organizing networks for extracting jet features

International Nuclear Information System (INIS)

Loennblad, L.; Peterson, C.; Pi, H.; Roegnvaldsson, T.

1991-01-01

Self-organizing neural networks are briefly reviewed and compared with supervised learning algorithms like back-propagation. The power of self-organization networks is in their capability of displaying typical features in a transparent manner. This is successfully demonstrated with two applications from hadronic jet physics; hadronization model discrimination and separation of b.c. and light quarks. (orig.)

Improving Students' Understanding of Molecular Structure through Broad-Based Use of Computer Models in the Undergraduate Organic Chemistry Lecture

Science.gov (United States)

Springer, Michael T.

2014-01-01

Several articles suggest how to incorporate computer models into the organic chemistry laboratory, but relatively few papers discuss how to incorporate these models broadly into the organic chemistry lecture. Previous research has suggested that "manipulating" physical or computer models enhances student understanding; this study…

Studies on Manfred Eigen's model for the self-organization of information processing.

Science.gov (United States)

Ebeling, W; Feistel, R

2018-05-01

In 1971, Manfred Eigen extended the principles of Darwinian evolution to chemical processes, from catalytic networks to the emergence of information processing at the molecular level, leading to the emergence of life. In this paper, we investigate some very general characteristics of this scenario, such as the valuation process of phenotypic traits in a high-dimensional fitness landscape, the effect of spatial compartmentation on the valuation, and the self-organized transition from structural to symbolic genetic information of replicating chain molecules. In the first part, we perform an analysis of typical dynamical properties of continuous dynamical models of evolutionary processes. In particular, we study the mapping of genotype to continuous phenotype spaces following the ideas of Wright and Conrad. We investigate typical features of a Schrödinger-like dynamics, the consequences of the high dimensionality, the leading role of saddle points, and Conrad's extra-dimensional bypass. In the last part, we discuss in brief the valuation of compartment models and the self-organized emergence of molecular symbols at the beginning of life.

Complexity in plasma. A grand view of self-organization

International Nuclear Information System (INIS)

Sato, Tetsuya.

1994-11-01

The central theme of the Complexity is the inquest of the creation of ordered structure in nature. Extensive computer simulations on plasmas have revealed that self-organization is governed by the three key processes, i.e. energy pumping, entropy expulsion and nonlinearity. A system exhibits characteristically different self-organization, depending on whether the energy pumping is instantaneous or continuous, or whether the produced entropy is expulsed or reserved. The nonlinearity acts to bring a nonequilibrium state into a bifurcation, thus resulting in a new structure along with an anomalous entropy production. (author)

Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems

Science.gov (United States)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2017-12-01

Multiagent systems (MAS) provide a useful tool for exploring the complex dynamics and behavior of financial markets and now MAS approach has been widely implemented and documented in the empirical literature. This paper introduces the implementation of an innovative multi-scale mathematical model for a computational agent-based financial market. The paper develops a method to quantify the degree of self-organization which emerges in the system and shows that the capacity of self-organization is maximized when the agent behaviors are heterogeneous. Numerical results are presented and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.

Interconnected growing self-organizing maps for auditory and semantic acquisition modeling

Directory of Open Access Journals (Sweden)

Mengxue eCao

2014-03-01

Full Text Available Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic--semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners; a reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1 I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2 clear auditory and semantic boundaries can be found in the network representation; (3 cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4 reinforcing-by-link training leads to well-perceived auditory--semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model.

Self-guaranteed measurement-based quantum computation

Science.gov (United States)

Hayashi, Masahito; Hajdušek, Michal

2018-05-01

In order to guarantee the output of a quantum computation, we usually assume that the component devices are trusted. However, when the total computation process is large, it is not easy to guarantee the whole system when we have scaling effects, unexpected noise, or unaccounted for correlations between several subsystems. If we do not trust the measurement basis or the prepared entangled state, we do need to be worried about such uncertainties. To this end, we propose a self-guaranteed protocol for verification of quantum computation under the scheme of measurement-based quantum computation where no prior-trusted devices (measurement basis or entangled state) are needed. The approach we present enables the implementation of verifiable quantum computation using the measurement-based model in the context of a particular instance of delegated quantum computation where the server prepares the initial computational resource and sends it to the client, who drives the computation by single-qubit measurements. Applying self-testing procedures, we are able to verify the initial resource as well as the operation of the quantum devices and hence the computation itself. The overhead of our protocol scales with the size of the initial resource state to the power of 4 times the natural logarithm of the initial state's size.

Quantitative computational models of molecular self-assembly in systems biology.

Science.gov (United States)

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

75 FR 63878 - Self-Regulatory Organizations; Self-Regulatory Organizations; Notice of Filing and Immediate...

Science.gov (United States)

2010-10-18

...-Regulatory Organizations; Self-Regulatory Organizations; Notice of Filing and Immediate Effectiveness of...(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the Terms of Substance... Public Reference Room. II. Self-Regulatory Organization's Statement of the Purpose of, and Statutory...

Tree-Structured Digital Organisms Model

Science.gov (United States)

Suzuki, Teruhiko; Nobesawa, Shiho; Tahara, Ikuo

Tierra and Avida are well-known models of digital organisms. They describe a life process as a sequence of computation codes. A linear sequence model may not be the only way to describe a digital organism, though it is very simple for a computer-based model. Thus we propose a new digital organism model based on a tree structure, which is rather similar to the generic programming. With our model, a life process is a combination of various functions, as if life in the real world is. This implies that our model can easily describe the hierarchical structure of life, and it can simulate evolutionary computation through mutual interaction of functions. We verified our model by simulations that our model can be regarded as a digital organism model according to its definitions. Our model even succeeded in creating species such as viruses and parasites.

Computational Intelligence, Cyber Security and Computational Models

CERN Document Server

Anitha, R; Lekshmi, R; Kumar, M; Bonato, Anthony; Graña, Manuel

2014-01-01

This book contains cutting-edge research material presented by researchers, engineers, developers, and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security and Computational Models (ICC3) organized by PSG College of Technology, Coimbatore, India during December 19–21, 2013. The materials in the book include theory and applications for design, analysis, and modeling of computational intelligence and security. The book will be useful material for students, researchers, professionals, and academicians. It will help in understanding current research trends and findings and future scope of research in computational intelligence, cyber security, and computational models.

Self-organization of hot plasmas the canonical profile transport model

CERN Document Server

Dnestrovskij, Yu N

2015-01-01

In this monograph the author presents the Canonical Profile Transport Model or CPTM as a rather general mathematical framework to simulate plasma discharges.The description of hot plasmas in a magnetic fusion device is a very challenging task and many plasma properties still lack a physical explanation. One important property is plasma self-organization.It is very well known from experiments that the radial profile of the plasma pressure and temperature remains rather unaffected by changes of the deposited power or plasma density. The attractiveness of the CPTM is that it includes the effect o

Computational Methods for Modeling Aptamers and Designing Riboswitches

Directory of Open Access Journals (Sweden)

Sha Gong

2017-11-01

Full Text Available Riboswitches, which are located within certain noncoding RNA region perform functions as genetic “switches”, regulating when and where genes are expressed in response to certain ligands. Understanding the numerous functions of riboswitches requires computation models to predict structures and structural changes of the aptamer domains. Although aptamers often form a complex structure, computational approaches, such as RNAComposer and Rosetta, have already been applied to model the tertiary (three-dimensional (3D structure for several aptamers. As structural changes in aptamers must be achieved within the certain time window for effective regulation, kinetics is another key point for understanding aptamer function in riboswitch-mediated gene regulation. The coarse-grained self-organized polymer (SOP model using Langevin dynamics simulation has been successfully developed to investigate folding kinetics of aptamers, while their co-transcriptional folding kinetics can be modeled by the helix-based computational method and BarMap approach. Based on the known aptamers, the web server Riboswitch Calculator and other theoretical methods provide a new tool to design synthetic riboswitches. This review will represent an overview of these computational methods for modeling structure and kinetics of riboswitch aptamers and for designing riboswitches.

On micro-scale self-organization in a plasma

International Nuclear Information System (INIS)

Maluckov, A.; Jovanovic, M.S.; Skoric, M.M.; Sato, T.

1998-01-01

We concentrate on a nonlinear saturation of a stimulated Raman backscattering in an open convective weakly confined model in the context of micro-kinetic scale self-organization in plasmas. The results have led to an assertion that a long-time nonlinear saturation in an open SRBS model with phenomenological effects of anomalous dissipation, plasma heating and subsequent entropy expulsion, reveals a generic interrelation of self-organization at wave-fluid (macro) and particle-kinetic (micro) levels. (author)

Self-organizing periodicity in development: organ positioning in plants.

Science.gov (United States)

Bhatia, Neha; Heisler, Marcus G

2018-02-08

Periodic patterns during development often occur spontaneously through a process of self-organization. While reaction-diffusion mechanisms are often invoked, other types of mechanisms that involve cell-cell interactions and mechanical buckling have also been identified. Phyllotaxis, or the positioning of plant organs, has emerged as an excellent model system to study the self-organization of periodic patterns. At the macro scale, the regular spacing of organs on the growing plant shoot gives rise to the typical spiral and whorled arrangements of plant organs found in nature. In turn, this spacing relies on complex patterns of cell polarity that involve feedback between a signaling molecule - the plant hormone auxin - and its polar, cell-to-cell transport. Here, we review recent progress in understanding phyllotaxis and plant cell polarity and highlight the development of new tools that can help address the remaining gaps in our understanding. © 2018. Published by The Company of Biologists Ltd.

Self-organization via active exploration in robotic applications

Science.gov (United States)

Ogmen, H.; Prakash, R. V.

1992-01-01

We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization

Integrated multiscale modeling of molecular computing devices

International Nuclear Information System (INIS)

Cummings, Peter T; Leng Yongsheng

2005-01-01

Molecular electronics, in which single organic molecules are designed to perform the functions of transistors, diodes, switches and other circuit elements used in current siliconbased microelecronics, is drawing wide interest as a potential replacement technology for conventional silicon-based lithographically etched microelectronic devices. In addition to their nanoscopic scale, the additional advantage of molecular electronics devices compared to silicon-based lithographically etched devices is the promise of being able to produce them cheaply on an industrial scale using wet chemistry methods (i.e., self-assembly from solution). The design of molecular electronics devices, and the processes to make them on an industrial scale, will require a thorough theoretical understanding of the molecular and higher level processes involved. Hence, the development of modeling techniques for molecular electronics devices is a high priority from both a basic science point of view (to understand the experimental studies in this field) and from an applied nanotechnology (manufacturing) point of view. Modeling molecular electronics devices requires computational methods at all length scales - electronic structure methods for calculating electron transport through organic molecules bonded to inorganic surfaces, molecular simulation methods for determining the structure of self-assembled films of organic molecules on inorganic surfaces, mesoscale methods to understand and predict the formation of mesoscale patterns on surfaces (including interconnect architecture), and macroscopic scale methods (including finite element methods) for simulating the behavior of molecular electronic circuit elements in a larger integrated device. Here we describe a large Department of Energy project involving six universities and one national laboratory aimed at developing integrated multiscale methods for modeling molecular electronics devices. The project is funded equally by the Office of Basic

Research on Corporate Social Responsibility of Supply Chain System Based on the Self-organization Theory

OpenAIRE

Baoying Wang

2013-01-01

In this study, the characteristics of supply chain system are analyzed based on the Self-organization theory from the angle of view of supply chain system. The mathematical models when the system fulfilling social responsibility including self-organization evolution model and self-organization function model are developed to discuss the formation and function of self-organization in supply chain system and coordination. Some basic conditions and tactics about self-organization establishment a...

A self-consistent first-principle based approach to model carrier mobility in organic materials

International Nuclear Information System (INIS)

Meded, Velimir; Friederich, Pascal; Symalla, Franz; Neumann, Tobias; Danilov, Denis; Wenzel, Wolfgang

2015-01-01

Transport through thin organic amorphous films, utilized in OLEDs and OPVs, has been a challenge to model by using ab-initio methods. Charge carrier mobility depends strongly on the disorder strength and reorganization energy, both of which are significantly affected by the details in environment of each molecule. Here we present a multi-scale approach to describe carrier mobility in which the materials morphology is generated using DEPOSIT, a Monte Carlo based atomistic simulation approach, or, alternatively by molecular dynamics calculations performed with GROMACS. From this morphology we extract the material specific hopping rates, as well as the on-site energies using a fully self-consistent embedding approach to compute the electronic structure parameters, which are then used in an analytic expression for the carrier mobility. We apply this strategy to compute the carrier mobility for a set of widely studied molecules and obtain good agreement between experiment and theory varying over several orders of magnitude in the mobility without any freely adjustable parameters. The work focuses on the quantum mechanical step of the multi-scale workflow, explains the concept along with the recently published workflow optimization, which combines density functional with semi-empirical tight binding approaches. This is followed by discussion on the analytic formula and its agreement with established percolation fits as well as kinetic Monte Carlo numerical approaches. Finally, we skatch an unified multi-disciplinary approach that integrates materials science simulation and high performance computing, developed within EU project MMM@HPC

Calcium metabolism in the rat: A temporal self-organized model

International Nuclear Information System (INIS)

Staub, J.F.; Tracqui, P.; Brezillon, P.; Milhaud, G.; Perault-Staub, A.M.

1988-01-01

Based on consideration of rat plasma Ca and 45 Ca concentrations, the authors analyze the circadian behavior of Ca metabolism of the rat as the temporal expression of a self-organized system. They present a self-oscillatory model M for rat Ca metabolism based on a compartmental formalism, which includes a second-order autocatalytic process. M describes the entire mass of Ca as made up of eight compartments and predicts a distinction between (1) the amount of Ca deposited in zones of rapid bone growth and reutilized during bone maturation and (2) the amount of Ca in mature bone subdivided into four compartments. Two of these compartments, largely self-oscillating, may represent Ca-P associations at bone liquid/solid interface and are subject to osteoblast-osteocyte control. The other two compartments can be thought of as made up of a large expanding pool of hydroxyapatite (HA) crystals, which are largely unavailable as such, and a small pool of more available HA crystals. Bone Ca influx and rhythmic efflux play a major role in the regulation of Ca in extracellular fluid but must be dissociated from bone accretion and resorption. Application to Ca deficiency was analyzed. Conceptual consequences of the connection of Ca metabolism to a self-regulated system are discussed

Cloud Computing for Technical and Online Organizations

OpenAIRE

Hagos Tesfahun Gebremichael; Dr.Vuda Sreenivasa Rao

2016-01-01

Cloud computing is a new computing model which is based on the grid computing, distributed computing, parallel computing and virtualization technologies define the shape of a new technology.It is the core technology of the next generation of network computing platform, especially in the field of education and online.Cloud computing as an exciting development in an educational Institute and online perspective.Cloud computing services are growing necessity for business organizations as well ...

Application of computational models to estimate organ radiation dose in rainbow trout from uptake of molybdenum-99 with comparison to iodine-131

International Nuclear Information System (INIS)

Martinez, N.E.; Johnson, T.E.; Pinder, J.E.

2016-01-01

This study compares three anatomical phantoms for rainbow trout (Oncorhynchus mykiss) for the purpose of estimating organ radiation dose and dose rates from molybdenum-99 ( 99 Mo) uptake in the liver and GI tract. Model comparison and refinement is important to the process of determining accurate doses and dose rates to the whole body and the various organs. Accurate and consistent dosimetry is crucial to the determination of appropriate dose-effect relationships for use in environmental risk assessment. The computational phantoms considered are (1) a geometrically defined model employing anatomically relevant organ size and location, (2) voxel reconstruction of internal anatomy obtained from CT imaging, and (3) a new model utilizing NURBS surfaces to refine the model in (2). Dose Conversion Factors (DCFs) for whole body as well as selected organs of O. mykiss were computed using Monte Carlo modeling and combined with empirical models for predicting activity concentration to estimate dose rates and ultimately determine cumulative radiation dose (μGy) to selected organs after several half-lives of 99 Mo. The computational models provided similar results, especially for organs that were both the source and target of radiation (less than 30% difference between all models). Values in the empirical model as well as the 14 day cumulative organ doses determined from 99 Mo uptake are compared to similar models developed previously for 131 I. Finally, consideration is given to treating the GI tract as a solid organ compared to partitioning it into gut contents and GI wall, which resulted in an order of magnitude difference in estimated dose for most organs. - Highlights: • Existing computational models for the internal dosimetry of trout are applied to 99 Mo uptake. • Consideration is given to the effect of alternate source distribution in the gut. • A hybrid computational phantom is developed. • At 14 days post-release, 99 Mo and 131 I provide similar

Effects of Some Neurobiological Factors in a Self-organized Critical Model Based on Neural Networks

International Nuclear Information System (INIS)

Zhou Liming; Zhang Yingyue; Chen Tianlun

2005-01-01

Based on an integrate-and-fire mechanism, we investigate the effect of changing the efficacy of the synapse, the transmitting time-delayed, and the relative refractoryperiod on the self-organized criticality in our neural network model.

Dynamical quenching and annealing in self-organization multiagent models

Science.gov (United States)

Burgos, E.; Ceva, Horacio; Perazzo, R. P.

2001-07-01

We study the dynamics of a generalized minority game (GMG) and of the bar attendance model (BAM) in which a number of agents self-organize to match an attendance that is fixed externally as a control parameter. We compare the usual dynamics used for the minority game with one for the BAM that makes a better use of the available information. We study the asymptotic states reached in both frameworks. We show that states that can be assimilated to either thermodynamic equilibrium or quenched configurations can appear in both models, but with different settings. We discuss the relevance of the parameter G that measures the value of the prize for winning in units of the fine for losing. We also provide an annealing protocol by which the quenched configurations of the GMG can progressively be modified to reach an asymptotic equilibrium state that coincides with the one obtained with the BAM.

LSOT: A Lightweight Self-Organized Trust Model in VANETs

Directory of Open Access Journals (Sweden)

Zhiquan Liu

2016-01-01

Full Text Available With the advances in automobile industry and wireless communication technology, Vehicular Ad hoc Networks (VANETs have attracted the attention of a large number of researchers. Trust management plays an important role in VANETs. However, it is still at the preliminary stage and the existing trust models cannot entirely conform to the characteristics of VANETs. This work proposes a novel Lightweight Self-Organized Trust (LSOT model which contains trust certificate-based and recommendation-based trust evaluations. Both the supernodes and trusted third parties are not needed in our model. In addition, we comprehensively consider three factor weights to ease the collusion attack in trust certificate-based trust evaluation, and we utilize the testing interaction method to build and maintain the trust network and propose a maximum local trust (MLT algorithm to identify trustworthy recommenders in recommendation-based trust evaluation. Furthermore, a fully distributed VANET scenario is deployed based on the famous Advogato dataset and a series of simulations and analysis are conducted. The results illustrate that our LSOT model significantly outperforms the excellent experience-based trust (EBT and Lightweight Cross-domain Trust (LCT models in terms of evaluation performance and robustness against the collusion attack.

Self-organized Segregation on the Grid

Science.gov (United States)

Omidvar, Hamed; Franceschetti, Massimo

2018-02-01

We consider an agent-based model with exponentially distributed waiting times in which two types of agents interact locally over a graph, and based on this interaction and on the value of a common intolerance threshold τ , decide whether to change their types. This is equivalent to a zero-temperature ising model with Glauber dynamics, an asynchronous cellular automaton with extended Moore neighborhoods, or a Schelling model of self-organized segregation in an open system, and has applications in the analysis of social and biological networks, and spin glasses systems. Some rigorous results were recently obtained in the theoretical computer science literature, and this work provides several extensions. We enlarge the intolerance interval leading to the expected formation of large segregated regions of agents of a single type from the known size ɛ >0 to size ≈ 0.134. Namely, we show that for 0.433sites can be observed within any sufficiently large region of the occupied percolation cluster. The exponential bounds that we provide also imply that complete segregation, where agents of a single type cover the whole grid, does not occur with high probability for p=1/2 and the range of intolerance considered.

Graphical user interface based computer simulation of self-similar modes of a paraxial slow self-focusing laser beam for saturating plasma nonlinearities

International Nuclear Information System (INIS)

Batra, Karuna; Mitra, Sugata; Subbarao, D.; Sharma, R.P.; Uma, R.

2005-01-01

The task for the present study is to make an investigation of self-similarity in a self-focusing laser beam both theoretically and numerically using graphical user interface based interactive computer simulation model in MATLAB (matrix laboratory) software in the presence of saturating ponderomotive force based and relativistic electron quiver based plasma nonlinearities. The corresponding eigenvalue problem is solved analytically using the standard eikonal formalism and the underlying dynamics of self-focusing is dictated by the corrected paraxial theory for slow self-focusing. The results are also compared with computer simulation of self-focusing by the direct fast Fourier transform based spectral methods. It is found that the self-similar solution obtained analytically oscillates around the true numerical solution equating it at regular intervals. The simulation results are the main ones although a feasible semianalytical theory under many assumptions is given to understand the process. The self-similar profiles are called as self-organized profiles (not in a strict sense), which are found to be close to Laguerre-Gaussian curves for all the modes, the shape being conserved. This terminology is chosen because it has already been shown from a phase space analysis that the width of an initially Gaussian beam undergoes periodic oscillations that are damped when any absorption is added in the model, i.e., the beam width converges to a constant value. The research paper also tabulates the specific values of the normalized phase shift for solutions decaying to zero at large transverse distances for first three modes which can, however, be extended to higher order modes

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

Science.gov (United States)

Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance

Self-organized Criticality in a Modified Evolution Model on Generalized Barabasi-Albert Scale-Free Networks

International Nuclear Information System (INIS)

Lin Min; Wang Gang; Chen Tianlun

2007-01-01

A modified evolution model of self-organized criticality on generalized Barabasi-Albert (GBA) scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.

A novel self-organizing E-Learner community model with award and exchange mechanisms.

Science.gov (United States)

Yang, Fan; Shen, Rui-min; Han, Peng

2004-11-01

How to share experience and resources among learners is becoming one of the hottest topics in the field of E-Learning collaborative techniques. An intuitive way to achieve this objective is to group learners which can help each other into the same community and help them learn collaboratively. In this paper, we proposed a novel community self-organization model based on multi-agent mechanism, which can automatically group learners with similar preferences and capabilities. In particular, we proposed award and exchange schemas with evaluation and preference track records to raise the performance of this algorithm. The description of learner capability, the matchmaking process, the definition of evaluation and preference track records, the rules of award and exchange schemas and the self-organization algorithm are all discussed in this paper. Meanwhile, a prototype has been built to verify the validity and efficiency of the algorithm. Experiments based on real learner data showed that this mechanism can organize learner communities properly and efficiently; and that it has sustainable improved efficiency and scalability.

Leader-based and self-organized communication: modelling group-mass recruitment in ants.

Science.gov (United States)

Collignon, Bertrand; Deneubourg, Jean Louis; Detrain, Claire

2012-11-21

For collective decisions to be made, the information acquired by experienced individuals about resources' location has to be shared with naïve individuals through recruitment. Here, we investigate the properties of collective responses arising from a leader-based recruitment and a self-organized communication by chemical trails. We develop a generalized model based on biological data drawn from Tetramorium caespitum ant species of which collective foraging relies on the coupling of group leading and trail recruitment. We show that for leader-based recruitment, small groups of recruits have to be guided in a very efficient way to allow a collective exploitation of food while large group requires less attention from their leader. In the case of self-organized recruitment through a chemical trail, a critical value of trail amount has to be laid per forager in order to launch collective food exploitation. Thereafter, ants can maintain collective foraging by emitting signal intensity below this threshold. Finally, we demonstrate how the coupling of both recruitment mechanisms may benefit to collectively foraging species. These theoretical results are then compared with experimental data from recruitment by T. caespitum ant colonies performing group-mass recruitment towards a single food source. We evidence the key role of leaders as initiators and catalysts of recruitment before this leader-based process is overtaken by self-organised communication through trails. This model brings new insights as well as a theoretical background to empirical studies about cooperative foraging in group-living species. Copyright © 2012 Elsevier Ltd. All rights reserved.

The performance model of dynamic virtual organization (VO) formations within grid computing context

International Nuclear Information System (INIS)

Han Liangxiu

2009-01-01

Grid computing aims to enable 'resource sharing and coordinated problem solving in dynamic, multi-institutional virtual organizations (VOs)'. Within the grid computing context, successful dynamic VO formations mean a number of individuals and institutions associated with certain resources join together and form new VOs in order to effectively execute tasks within given time steps. To date, while the concept of VOs has been accepted, few research has been done on the impact of effective dynamic virtual organization formations. In this paper, we develop a performance model of dynamic VOs formation and analyze the effect of different complex organizational structures and their various statistic parameter properties on dynamic VO formations from three aspects: (1) the probability of a successful VO formation under different organizational structures and statistic parameters change, e.g. average degree; (2) the effect of task complexity on dynamic VO formations; (3) the impact of network scales on dynamic VO formations. The experimental results show that the proposed model can be used to understand the dynamic VO formation performance of the simulated organizations. The work provides a good path to understand how to effectively schedule and utilize resources based on the complex grid network and therefore improve the overall performance within grid environment.

Self-organized critical model for protein folding

Science.gov (United States)

Moret, M. A.

2011-09-01

The major factor that drives a protein toward collapse and folding is the hydrophobic effect. At the folding process a hydrophobic core is shielded by the solvent-accessible surface area of the protein. We study the fractal behavior of 5526 protein structures present in the Brookhaven Protein Data Bank. Power laws of protein mass, volume and solvent-accessible surface area are measured independently. The present findings indicate that self-organized criticality is an alternative explanation for the protein folding. Also we note that the protein packing is an independent and constant value because the self-similar behavior of the volumes and protein masses have the same fractal dimension. This power law guarantees that a protein is a complex system. From the analyzed data, q-Gaussian distributions seem to fit well this class of systems.

Self-organization comprehensive real-time state evaluation model for oil pump unit on the basis of operating condition classification and recognition

Science.gov (United States)

Liang, Wei; Yu, Xuchao; Zhang, Laibin; Lu, Wenqing

2018-05-01

In oil transmission station, the operating condition (OC) of an oil pump unit sometimes switches accordingly, which will lead to changes in operating parameters. If not taking the switching of OCs into consideration while performing a state evaluation on the pump unit, the accuracy of evaluation would be largely influenced. Hence, in this paper, a self-organization Comprehensive Real-Time State Evaluation Model (self-organization CRTSEM) is proposed based on OC classification and recognition. However, the underlying model CRTSEM is built through incorporating the advantages of Gaussian Mixture Model (GMM) and Fuzzy Comprehensive Evaluation Model (FCEM) first. That is to say, independent state models are established for every state characteristic parameter according to their distribution types (i.e. the Gaussian distribution and logistic regression distribution). Meanwhile, Analytic Hierarchy Process (AHP) is utilized to calculate the weights of state characteristic parameters. Then, the OC classification is determined by the types of oil delivery tasks, and CRTSEMs of different standard OCs are built to constitute the CRTSEM matrix. On the other side, the OC recognition is realized by a self-organization model that is established on the basis of Back Propagation (BP) model. After the self-organization CRTSEM is derived through integration, real-time monitoring data can be inputted for OC recognition. At the end, the current state of the pump unit can be evaluated by using the right CRTSEM. The case study manifests that the proposed self-organization CRTSEM can provide reasonable and accurate state evaluation results for the pump unit. Besides, the assumption that the switching of OCs will influence the results of state evaluation is also verified.

Self-organized critical pinball machine

DEFF Research Database (Denmark)

Flyvbjerg, H.

2004-01-01

The nature of self-organized criticality (SOC) is pin-pointed with a simple mechanical model: a pinball machine. Its phase space is fully parameterized by two integer variables, one describing the state of an on-going game, the other describing the state of the machine. This is the simplest...

Brain Basis of Self: Self-Organization and Lessons from Dreaming

Directory of Open Access Journals (Sweden)

David eKahn

2013-07-01

Full Text Available Through dreaming a different facet of the self is created as a result of a self-organizing process in the brain. Self-organization in biological systems often happens as an answer to an environmental change for which the existing system cannot cope; self-organization creates a system that can cope in the newly changed environment. In dreaming, self-organization serves the function of organizing disparate memories into a dream since the dreamer herself is not able to control how individual memories become weaved into a dream. The self-organized dream provides, thereby, a wide repertoire of experiences; this expanded repertoire of experience results in an expansion of the self beyond that obtainable when awake. Since expression of the self is associated with activity in specific areas of the brain, the article also discusses the brain basis of the self by reviewing studies of brain injured patients, discussing brain imaging studies in normal brain functioning when focused, when daydreaming and when asleep and dreaming.

The sensitivity of Turing self-organization to biological feedback delays: 2D models of fish pigmentation

KAUST Repository

Gaffney, E. A.; Lee, S. S.

2013-01-01

© The authors 2013. Turing morphogen models have been extensively explored in the context of large-scale self-organization in multicellular biological systems. However, reconciling the detailed biology of morphogen dynamics, while accounting

On self-organized criticality in nonconserving systems

International Nuclear Information System (INIS)

Socolar, J.E.S.; Grinstein, G.; Jayaprakash, C.

1993-01-01

Two models with nonconserving dynamics and slow continuous deterministic driving, a stick-slip model (SSM) of earthquake dynamics and a toy forest-fire model (FFM), have recently been argued to show numerical evidence of self-organized criticality (generic, scale-invariant steady states). To determine whether the observed criticality is indeed generic, we study these models as a function of a parameter γ which was implicitly tuned to a special value, γ=1, in their original definitions. In both cases, the maximum Lyapunov exponent vanishes at γ=1. We find that the FFM does not exhibit self-organized criticality for any γ, including γ=1; nor does the SSM with periodic boundary conditions. Both models show evidence of macroscopic periodic oscillations in time for some range of γ values. We suggest that such oscillations may provide a mechanism for the generation of scale-invariant structure in nonconserving systems, and, in particular, that they underlie the criticality previously observed in the SSM with open boundary conditions

Slip-Size Distribution and Self-Organized Criticality in Block-Spring Models with Quenched Randomness

Science.gov (United States)

Sakaguchi, Hidetsugu; Kadowaki, Shuntaro

2017-07-01

We study slowly pulling block-spring models in random media. Second-order phase transitions exist in a model pulled by a constant force in the case of velocity-strengthening friction. If external forces are slowly increased, nearly critical states are self-organized. Slips of various sizes occur, and the probability distributions of slip size roughly obey power laws. The exponent is close to that in the quenched Edwards-Wilkinson model. Furthermore, the slip-size distributions are investigated in cases of Coulomb friction, velocity-weakening friction, and two-dimensional block-spring models.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

Directory of Open Access Journals (Sweden)

Samreen Laghari

Full Text Available Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT implies an inherent difficulty in modeling problems.It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS. The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC framework to model a Complex communication network problem.We use Exploratory Agent-based Modeling (EABM, as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy.The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

Science.gov (United States)

Laghari, Samreen; Niazi, Muaz A

2016-01-01

Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Modeling of self-organization of two-dimensional ordered structures

Energy Technology Data Exchange (ETDEWEB)

Egorov, V V; Garmay, Y P; Shaldzhyan, A A; Vasin, A V; Kiselev, O I [Research Institute of Influenza of the Ministry of Health and Social Development of the Russian Federation, Prof. Popova st. 15/17, St-Petersburg (Russian Federation); Lebedev, D V [Department of Molecular and Radiation Biophysics Petersburg Nuclear Physics Institute of the Russian Academy of Science, Orlova Roscha, Gatchina, Leningrad Region (Russian Federation); Grudinina, N A, E-mail: toizeg@gmail.com [Institute of Experimental Medicine, North-Western Branch of the Russian Academy of Medical Science, 12, Akademika Pavlova st., St-Petersburg (Russian Federation)

2011-04-01

The problem of the search of biostructures capable to self-organization is quite urgent considering the prospects of application of nanostructured biomaterials as components of composite materials in transplantology and optics as well as 'scaffolds' for the synthesis of nanostructured materials based on inorganic particles. The given study focuses on modeling of the growth of structures using the cellular automata with a set of states of the two values (0 and 1), with the value corresponding to the state is determined by the contribution of 'the closest neighbor' (by the probability of induction of the state of the nextgeneration in the direction of the interaction) and the geometry of the field isdetermined by the vector of the direction of the particle and the direction of the interaction.

Effects of Computer Course on Computer Self-Efficacy, Computer Attitudes and Achievements of Young Individuals in Siirt, Turkey

Science.gov (United States)

Çelik, Halil Coskun

2015-01-01

The purpose of this study is to investigate the effects of computer courses on young individuals' computer self-efficacy, attitudes and achievement. The study group of this research included 60 unemployed young individuals (18-25 ages) in total; 30 in the experimental group and 30 in the control group. An experimental research model with pretest…

Self-organization of high intensity laser pulses propagating in gases

International Nuclear Information System (INIS)

Koga, James

2001-01-01

In recent years the development of high intensity short pulse lasers has opened up wide fields of science which had previously been difficult to study. Recent experiments of short pulse lasers propagating in air have shown that these laser pulses can propagate over very long distances (up to 12 km) with little or no distortion of the pulse. Here we present a model of this propagation using a modified version of the self-organized criticality model developed for sandpiles by Bak, Tang, and Weisenfeld. The additions to the sandpile model include the formation of plasma which acts as a threshold diffusion term and self-focusing by the nonlinear index of refraction which acts as a continuous inverse diffusion. Results of this simple model indicate that a strongly self-focusing laser pulse shows self-organized critical behavior. (author)

From self-organization to self-assembly: a new materialism?

Science.gov (United States)

Vincent, Bernadette Bensaude

2016-09-01

While self-organization has been an integral part of academic discussions about the distinctive features of living organisms, at least since Immanuel Kant's Critique of Judgement, the term 'self-assembly' has only been used for a few decades as it became a hot research topic with the emergence of nanotechnology. Could it be considered as an attempt at reducing vital organization to a sort of assembly line of molecules? Considering the context of research on self-assembly I argue that the shift of attention from self-organization to self-assembly does not really challenge the boundary between chemistry and biology. Self-assembly was first and foremost investigated in an engineering context as a strategy for manufacturing without human intervention and did not raise new perspectives on the emergence of vital organization itself. However self-assembly implies metaphysical assumptions that this paper tries to disentangle. It first describes the emergence of self-assembly as a research field in the context of materials science and nanotechnology. The second section outlines the metaphysical implications and will emphasize a sharp contrast between the ontology underlying two practices of self-assembly developed under the umbrella of synthetic biology. And unexpectedly, we shall see that chemists are less on the reductionist side than most synthetic biologists. Finally, the third section ventures some reflections on the kind of design involved in self-assembly practices.

Self-Organized Criticality in an Anisotropic Earthquake Model

Science.gov (United States)

Li, Bin-Quan; Wang, Sheng-Jun

2018-03-01

We have made an extensive numerical study of a modified model proposed by Olami, Feder, and Christensen to describe earthquake behavior. Two situations were considered in this paper. One situation is that the energy of the unstable site is redistributed to its nearest neighbors randomly not averagely and keeps itself to zero. The other situation is that the energy of the unstable site is redistributed to its nearest neighbors randomly and keeps some energy for itself instead of reset to zero. Different boundary conditions were considered as well. By analyzing the distribution of earthquake sizes, we found that self-organized criticality can be excited only in the conservative case or the approximate conservative case in the above situations. Some evidence indicated that the critical exponent of both above situations and the original OFC model tend to the same result in the conservative case. The only difference is that the avalanche size in the original model is bigger. This result may be closer to the real world, after all, every crust plate size is different. Supported by National Natural Science Foundation of China under Grant Nos. 11675096 and 11305098, the Fundamental Research Funds for the Central Universities under Grant No. GK201702001, FPALAB-SNNU under Grant No. 16QNGG007, and Interdisciplinary Incubation Project of SNU under Grant No. 5

Measuring the Complexity of Self-Organizing Traffic Lights

Directory of Open Access Journals (Sweden)

Darío Zubillaga

2014-04-01

Full Text Available We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.

Neural and computational processes underlying dynamic changes in self-esteem

Science.gov (United States)

Rutledge, Robb B; Moutoussis, Michael; Dolan, Raymond J

2017-01-01

Self-esteem is shaped by the appraisals we receive from others. Here, we characterize neural and computational mechanisms underlying this form of social influence. We introduce a computational model that captures fluctuations in self-esteem engendered by prediction errors that quantify the difference between expected and received social feedback. Using functional MRI, we show these social prediction errors correlate with activity in ventral striatum/subgenual anterior cingulate cortex, while updates in self-esteem resulting from these errors co-varied with activity in ventromedial prefrontal cortex (vmPFC). We linked computational parameters to psychiatric symptoms using canonical correlation analysis to identify an ‘interpersonal vulnerability’ dimension. Vulnerability modulated the expression of prediction error responses in anterior insula and insula-vmPFC connectivity during self-esteem updates. Our findings indicate that updating of self-evaluative beliefs relies on learning mechanisms akin to those used in learning about others. Enhanced insula-vmPFC connectivity during updating of those beliefs may represent a marker for psychiatric vulnerability. PMID:29061228

Neural and computational processes underlying dynamic changes in self-esteem.

Science.gov (United States)

Will, Geert-Jan; Rutledge, Robb B; Moutoussis, Michael; Dolan, Raymond J

2017-10-24

Self-esteem is shaped by the appraisals we receive from others. Here, we characterize neural and computational mechanisms underlying this form of social influence. We introduce a computational model that captures fluctuations in self-esteem engendered by prediction errors that quantify the difference between expected and received social feedback. Using functional MRI, we show these social prediction errors correlate with activity in ventral striatum/subgenual anterior cingulate cortex, while updates in self-esteem resulting from these errors co-varied with activity in ventromedial prefrontal cortex (vmPFC). We linked computational parameters to psychiatric symptoms using canonical correlation analysis to identify an 'interpersonal vulnerability' dimension. Vulnerability modulated the expression of prediction error responses in anterior insula and insula-vmPFC connectivity during self-esteem updates. Our findings indicate that updating of self-evaluative beliefs relies on learning mechanisms akin to those used in learning about others. Enhanced insula-vmPFC connectivity during updating of those beliefs may represent a marker for psychiatric vulnerability.

Programming Unconventional Computers: Dynamics, Development, Self-Reference

Directory of Open Access Journals (Sweden)

Susan Stepney

2012-10-01

Full Text Available Classical computing has well-established formalisms for specifying, refining, composing, proving, and otherwise reasoning about computations. These formalisms have matured over the past 70 years or so. Unconventional Computing includes the use of novel kinds of substrates–from black holes and quantum effects, through to chemicals, biomolecules, even slime moulds–to perform computations that do not conform to the classical model. Although many of these unconventional substrates can be coerced into performing classical computation, this is not how they “naturally” compute. Our ability to exploit unconventional computing is partly hampered by a lack of corresponding programming formalisms: we need models for building, composing, and reasoning about programs that execute in these substrates. What might, say, a slime mould programming language look like? Here I outline some of the issues and properties of these unconventional substrates that need to be addressed to find “natural” approaches to programming them. Important concepts include embodied real values, processes and dynamical systems, generative systems and their meta-dynamics, and embodied self-reference.

The sensitivity of Turing self-organization to biological feedback delays: 2D models of fish pigmentation

KAUST Repository

Gaffney, E. A.

2013-10-01

© The authors 2013. Turing morphogen models have been extensively explored in the context of large-scale self-organization in multicellular biological systems. However, reconciling the detailed biology of morphogen dynamics, while accounting for time delays associated with gene expression, reveals aberrant behaviours that are not consistent with early developmental self-organization, especially the requirement for exquisite temporal control. Attempts to reconcile the interpretation of Turing\\'s ideas with an increasing understanding of the mechanisms driving zebrafish pigmentation suggests that one should reconsider Turing\\'s model in terms of pigment cells rather than morphogens (Nakamasu et al., 2009, PNAS, 106, 8429-8434; Yamaguchi et al., 2007, PNAS, 104, 4790-4793). Here the dynamics of pigment cells is subject to response delays implicit in the cell cycle and apoptosis. Hence we explore simulations of fish skin patterning, focussing on the dynamical influence of gene expression delays in morphogen-based Turing models and response delays for cell-based Turing models. We find that reconciling the mechanisms driving the behaviour of Turing systems with observations of fish skin patterning remains a fundamental challenge.

Self-organized topology of recurrence-based complex networks

International Nuclear Information System (INIS)

Yang, Hui; Liu, Gang

2013-01-01

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks

Innovative Mechanism of Rural Organization Based on Self-Organization

OpenAIRE

Wang, Xing jin; Gao, Bing

2011-01-01

The paper analyzes the basic situation for the formation of innovative rural organizations with the form of self-organization; revels the features of self-organization, including the four aspects of openness of rural organization, innovation of rural organization is far away from equilibrium, the non-linear response mechanism of rural organization innovation and the random rise and fall of rural organization innovation. The evolution mechanism of rural organization innovation is reveled accor...

A continuum self organized critically model of turbulent heat transport in tokamaks

Energy Technology Data Exchange (ETDEWEB)

Tangri, V; Das, A; Kaw, P; Singh, R [Institute for Plasma Research, Gandhinagar (India)

2003-09-01

Based on the now well known and experimentally observed critical gradient length (R/L{sub Te} = RT/{nabla}T) in tokamaks, we present a continuum one dimensional model for explaining self organized heat transport in tokamaks. Key parameters of this model include a novel hysteresis parameter which ensures that the switch of heat transport coefficient {chi} upwards and downwards takes place at two different values of R/L{sub Te}. Extensive numerical simulations of this model reproduce many features of present day tokamaks such as submarginal temperature profiles, intermittent transport events, 1/f scaling of the frequency spectra, propagating fronts, etc. This model utilises a minimal set of phenomenological parameters, which may be determined from experiments and/or simulations. Analytical and physical understanding of the observed features has also been attempted. (author)

Cloud Computing and Agile Organization Development

Directory of Open Access Journals (Sweden)

Bogdan GHILIC-MICU

2014-01-01

Full Text Available In the 3rd millennium economy, defined by globalization and continuous reduction of natural resources, the economic organization becomes the main actor in the phenomenon of transfor-mation and adaptation to new conditions. Even more, the economic environment, which is closely related to the social environment, undergoes complex metamorphoses, especially in the management area. In this dynamic and complex social and environmental context, the econom-ic organization must possess the ability to adapt, becoming a flexible and agile answer to new market opportunities. Considering the spectacular evolution of information and communica-tions technology, one of the solutions to ensure organization agility is cloud computing. Just like the development of any science requires adaptation to theories and instruments specific to other fields, a cloud computing paradigm for the agile organization must appeal to models from management, cybernetics, mathematics, structuralism and information theory (or information systems theory.

Self-organized criticality paradigm

International Nuclear Information System (INIS)

Duran, I.; Stoeckel, J.; Hron, M.; Horacek, J.; Jakubka, K.; Kryska, L.

2000-01-01

According to the paradigm of the Self-Organized Criticality (SOC), the anomalous transport in tokamaks is caused by fast transient processes - avalanches. One of the manifestations of these phenomena should be 1/f decay of electrostatic fluctuations power spectra in a certain frequency range. In this paper, the frequency spectra of floating potential, density and fluctuation-induced flux, measured by poloidal and radial arrays of Langmuir probes on the CASTOR tokamak, are presented. The floating potential and the fluctuation-induced flux decay from 30 kHz up to 100 kHz as f -1 . The plasma density decays as f -1 in a more narrow band, 20 to 40 kHz. The possible limitation of SOC behavior for frequencies higher than 100 kHz due to intermittency is stressed. For this reason the Probability Distribution Functions (PDFs) of floating potential fluctuations were computed at different time scales using wavelet transform. A clear departure of the computed PDFs from Gaussianity, which is a classical signature of intermittency, is observed at time scales under 10 μs (100 kHz). (author)

Anomalous relaxation and self-organization in nonequilibrium processes

International Nuclear Information System (INIS)

Fatkullin, Ibrahim; Kladko, Konstantin; Mitkov, Igor; Bishop, A. R.

2001-01-01

We study thermal relaxation in ordered arrays of coupled nonlinear elements with external driving. We find that our model exhibits dynamic self-organization manifested in a universal stretched-exponential form of relaxation. We identify two types of self-organization, cooperative and anticooperative, which lead to fast and slow relaxation, respectively. We give a qualitative explanation for the behavior of the stretched exponent in different parameter ranges. We emphasize that this is a system exhibiting stretched-exponential relaxation without explicit disorder or frustration

New ATLAS Software & Computing Organization

CERN Multimedia

Barberis, D

Following the election by the ATLAS Collaboration Board of Dario Barberis (Genoa University/INFN) as Computing Coordinator and David Quarrie (LBNL) as Software Project Leader, it was considered necessary to modify the organization of the ATLAS Software & Computing ("S&C") project. The new organization is based upon the following principles: separation of the responsibilities for computing management from those of software development, with the appointment of a Computing Coordinator and a Software Project Leader who are both members of the Executive Board; hierarchical structure of responsibilities and reporting lines; coordination at all levels between TDAQ, S&C and Physics working groups; integration of the subdetector software development groups with the central S&C organization. A schematic diagram of the new organization can be seen in Fig.1. Figure 1: new ATLAS Software & Computing organization. Two Management Boards will help the Computing Coordinator and the Software Project...

Innovative Mechanism of Rural Organization Based on Self-Organization

Institute of Scientific and Technical Information of China (English)

2011-01-01

The paper analyzes the basic situation of the formation of innovative rural organizations with the form of self-organization;reveals the features of self-organization,including the four aspects of openness of rural organization,innovation of rural organization far away from equilibrium,the non-linear response mechanism of rural organization innovation and the random rise and fall of rural organization innovation.The evolution mechanism of rural organization innovation is revealed according to the growth stage,the ideal stage,the decline and the fall stage.The paper probes into the basic restriction mechanism of the self-organization evaluation of rural organization from three aspects,including target recognition,path dependence and knowledge sharing.The basic measures on cultivating the innovative mechanism of rural organization are put forward.Firstly,constructing the dissipative structure of rural organization innovation;secondly,cultivating the dynamic study capability of rural organization innovation system;thirdly,selecting the step-by-step evolution strategy of rural organization innovation system.

Self-organized Learning Environments

DEFF Research Database (Denmark)

Dalsgaard, Christian; Mathiasen, Helle

2007-01-01

system actively. The two groups used the system in their own way to support their specific activities and ways of working. The paper concludes that self-organized learning environments can strengthen the development of students’ academic as well as social qualifications. Further, the paper identifies......The purpose of the paper is to discuss the potentials of using a conference system in support of a project based university course. We use the concept of a self-organized learning environment to describe the shape of the course. In the paper we argue that educational technology, such as conference...... systems, has a potential to support students’ development of self-organized learning environments and facilitate self-governed activities in higher education. The paper is based on an empirical study of two project groups’ use of a conference system. The study showed that the students used the conference...

PREFACE: Self-organized nanostructures

Science.gov (United States)

Rousset, Sylvie; Ortega, Enrique

2006-04-01

In order to fabricate ordered arrays of nanostructures, two different strategies might be considered. The `top-down' approach consists of pushing the limit of lithography techniques down to the nanometre scale. However, beyond 10 nm lithography techniques will inevitably face major intrinsic limitations. An alternative method for elaborating ultimate-size nanostructures is based on the reverse `bottom-up' approach, i.e. building up nanostructures (and eventually assemble them to form functional circuits) from individual atoms or molecules. Scanning probe microscopies, including scanning tunnelling microscopy (STM) invented in 1982, have made it possible to create (and visualize) individual structures atom by atom. However, such individual atomic manipulation is not suitable for industrial applications. Self-assembly or self-organization of nanostructures on solid surfaces is a bottom-up approach that allows one to fabricate and assemble nanostructure arrays in a one-step process. For applications, such as high density magnetic storage, self-assembly appears to be the simplest alternative to lithography for massive, parallel fabrication of nanostructure arrays with regular sizes and spacings. These are also necessary for investigating the physical properties of individual nanostructures by means of averaging techniques, i.e. all those using light or particle beams. The state-of-the-art and the current developments in the field of self-organization and physical properties of assembled nanostructures are reviewed in this issue of Journal of Physics: Condensed Matter. The papers have been selected from among the invited and oral presentations of the recent summer workshop held in Cargese (Corsica, France, 17-23 July 2005). All authors are world-renowned in the field. The workshop has been funded by the Marie Curie Actions: Marie Curie Conferences and Training Courses series named `NanosciencesTech' supported by the VI Framework Programme of the European Community, by

5G heterogeneous networks self-organizing and optimization

CERN Document Server

Rong, Bo; Kadoch, Michel; Sun, Songlin; Li, Wenjing

2016-01-01

This SpringerBrief provides state-of-the-art technical reviews on self-organizing and optimization in 5G systems. It covers the latest research results from physical-layer channel modeling to software defined network (SDN) architecture. This book focuses on the cutting-edge wireless technologies such as heterogeneous networks (HetNets), self-organizing network (SON), smart low power node (LPN), 3D-MIMO, and more. It will help researchers from both the academic and industrial worlds to better understand the technical momentum of 5G key technologies.

Self-organized critical neural networks

International Nuclear Information System (INIS)

Bornholdt, Stefan; Roehl, Torsten

2003-01-01

A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

Impacts of Mothers’ Occupation Status and Parenting Styles on Levels of Self-Control, Addiction to Computer Games, and Educational Progress of Adolescents

OpenAIRE

Abedini, Yasamin; Zamani, Bibi Eshrat; Kheradmand, Ali; Rajabizadeh, Ghodratollah

2012-01-01

Background Addiction to computer (video) games in adolescents and its relationship with educational progress has recently attracted the attention of rearing and education experts as well as organizations and institutes involved in physical and mental health. The current research attempted to propose a structural model of the relationships between parenting styles, mothers’ occupation status, and addiction to computer games, self-control, and educational progress of secondary school students. ...

Anomalous relaxation and self-organization in non-equilibrium processes

OpenAIRE

Fatkullin, Ibrahim; Kladko, Konstantin; Mitkov, Igor; Bishop, A. R.

2000-01-01

We study thermal relaxation in ordered arrays of coupled nonlinear elements with external driving. We find, that our model exhibits dynamic self-organization manifested in a universal stretched-exponential form of relaxation. We identify two types of self-organization, cooperative and anti-cooperative, which lead to fast and slow relaxation, respectively. We give a qualitative explanation for the behavior of the stretched exponent in different parameter ranges. We emphasize that this is a sys...

Motivation and performance within a collaborative computer-based modeling task: Relations between students' achievement goal orientation, self-efficacy, cognitive processing and achievement

OpenAIRE

Sins, P.H.M.; van Joolingen, W.R.; Savelsbergh, E.R.; van Hout-Wolters, B.H.A.M.

2008-01-01

Purpose of the present study was to test a conceptual model of relations among achievement goal orientation, self-efficacy, cognitive processing, and achievement of students working within a particular collaborative task context. The task involved a collaborative computer-based modeling task. In order to test the model, group measures of mastery-approach goal orientation, performance-avoidance goal orientation, self-efficacy, and achievement were employed. Students’ cognitive processing was a...

Intelligent system for statistically significant expertise knowledge on the basis of the model of self-organizing nonequilibrium dissipative system

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E. A. Tatokchin

2017-01-01

Full Text Available Development of the modern educational technologies caused by broad introduction of comput-er testing and development of distant forms of education does necessary revision of methods of an examination of pupils. In work it was shown, need transition to mathematical criteria, exami-nations of knowledge which are deprived of subjectivity. In article the review of the problems arising at realization of this task and are offered approaches for its decision. The greatest atten-tion is paid to discussion of a problem of objective transformation of rated estimates of the ex-pert on to the scale estimates of the student. In general, the discussion this question is was con-cluded that the solution to this problem lies in the creation of specialized intellectual systems. The basis for constructing intelligent system laid the mathematical model of self-organizing nonequilibrium dissipative system, which is a group of students. This article assumes that the dissipative system is provided by the constant influx of new test items of the expert and non-equilibrium – individual psychological characteristics of students in the group. As a result, the system must self-organize themselves into stable patterns. This patern will allow for, relying on large amounts of data, get a statistically significant assessment of student. To justify the pro-posed approach in the work presents the data of the statistical analysis of the results of testing a large sample of students (> 90. Conclusions from this statistical analysis allowed to develop intelligent system statistically significant examination of student performance. It is based on data clustering algorithm (k-mean for the three key parameters. It is shown that this approach allows you to create of the dynamics and objective expertise evaluation.

The sensitivity of Turing self-organization to biological feedback delays: 2D models of fish pigmentation.

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Gaffney, E A; Lee, S Seirin

2015-03-01

Turing morphogen models have been extensively explored in the context of large-scale self-organization in multicellular biological systems. However, reconciling the detailed biology of morphogen dynamics, while accounting for time delays associated with gene expression, reveals aberrant behaviours that are not consistent with early developmental self-organization, especially the requirement for exquisite temporal control. Attempts to reconcile the interpretation of Turing's ideas with an increasing understanding of the mechanisms driving zebrafish pigmentation suggests that one should reconsider Turing's model in terms of pigment cells rather than morphogens (Nakamasu et al., 2009, PNAS, 106: , 8429-8434; Yamaguchi et al., 2007, PNAS, 104: , 4790-4793). Here the dynamics of pigment cells is subject to response delays implicit in the cell cycle and apoptosis. Hence we explore simulations of fish skin patterning, focussing on the dynamical influence of gene expression delays in morphogen-based Turing models and response delays for cell-based Turing models. We find that reconciling the mechanisms driving the behaviour of Turing systems with observations of fish skin patterning remains a fundamental challenge. © The Authors 2013. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Hierarchical Recursive Organization and the Free Energy Principle: From Biological Self-Organization to the Psychoanalytic Mind

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Patrick Connolly

2017-09-01

Full Text Available The present paper argues that a systems theory epistemology (and particularly the notion of hierarchical recursive organization provides the critical theoretical context within which the significance of Friston's (2010a Free Energy Principle (FEP for both evolution and psychoanalysis is best understood. Within this perspective, the FEP occupies a particular level of the hierarchical organization of the organism, which is the level of biological self-organization. This form of biological self-organization is in turn understood as foundational and pervasive to the higher levels of organization of the human organism that are of interest to both neuroscience as well as psychoanalysis. Consequently, central psychoanalytic claims should be restated, in order to be located in their proper place within a hierarchical recursive organization of the (situated organism. In light of the FEP the realization of the psychoanalytic mind by the brain should be seen in terms of the evolution of different levels of systematic organization where the concepts of psychoanalysis describe a level of hierarchical recursive organization superordinate to that of biological self-organization and the FEP. The implication of this formulation is that while “psychoanalytic” mental processes are fundamentally subject to the FEP, they nonetheless also add their own principles of process over and above that of the FEP. A model found in Grobbelaar (1989 offers a recursive bottom-up description of the self-organization of the psychoanalytic ego as dependent on the organization of language (and affect, which is itself founded upon the tendency toward autopoiesis (self-making within the organism, which is in turn described as formally similar to the FEP. Meaningful consilience between Grobbelaar's model and the hierarchical recursive description available in Friston's (2010a theory is described. The paper concludes that the valuable contribution of the FEP to psychoanalysis

Predicting Forearm Physical Exposures During Computer Work Using Self-Reports, Software-Recorded Computer Usage Patterns, and Anthropometric and Workstation Measurements.

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Huysmans, Maaike A; Eijckelhof, Belinda H W; Garza, Jennifer L Bruno; Coenen, Pieter; Blatter, Birgitte M; Johnson, Peter W; van Dieën, Jaap H; van der Beek, Allard J; Dennerlein, Jack T

2017-12-15

Alternative techniques to assess physical exposures, such as prediction models, could facilitate more efficient epidemiological assessments in future large cohort studies examining physical exposures in relation to work-related musculoskeletal symptoms. The aim of this study was to evaluate two types of models that predict arm-wrist-hand physical exposures (i.e. muscle activity, wrist postures and kinematics, and keyboard and mouse forces) during computer use, which only differed with respect to the candidate predicting variables; (i) a full set of predicting variables, including self-reported factors, software-recorded computer usage patterns, and worksite measurements of anthropometrics and workstation set-up (full models); and (ii) a practical set of predicting variables, only including the self-reported factors and software-recorded computer usage patterns, that are relatively easy to assess (practical models). Prediction models were build using data from a field study among 117 office workers who were symptom-free at the time of measurement. Arm-wrist-hand physical exposures were measured for approximately two hours while workers performed their own computer work. Each worker's anthropometry and workstation set-up were measured by an experimenter, computer usage patterns were recorded using software and self-reported factors (including individual factors, job characteristics, computer work behaviours, psychosocial factors, workstation set-up characteristics, and leisure-time activities) were collected by an online questionnaire. We determined the predictive quality of the models in terms of R2 and root mean squared (RMS) values and exposure classification agreement to low-, medium-, and high-exposure categories (in the practical model only). The full models had R2 values that ranged from 0.16 to 0.80, whereas for the practical models values ranged from 0.05 to 0.43. Interquartile ranges were not that different for the two models, indicating that only for some

MACHINE LEARNING FOR THE SELF-ORGANIZATION OF DISTRIBUTED SYSTEMS IN ECONOMIC APPLICATIONS

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Jerzy Balicki

2017-03-01

Full Text Available In this paper, an application of machine learning to the problem of self-organization of distributed systems has been discussed with regard to economic applications, with particular emphasis on supervised neural network learning to predict stock investments and some ratings of companies. In addition, genetic programming can play an important role in the preparation and testing of several financial information systems. For this reason, machine learning applications have been discussed because some software applications can be automatically constructed by genetic programming. To obtain a competitive advantage, machine learning can be used for the management of self-organizing cloud computing systems performing calculations for business. Also the use of selected economic self-organizing distributed systems has been described, including some testing methods of predicting borrower reliability. Finally, some conclusions and directions for further research have been proposed.

Self-Organization during Friction in Complex Surface Engineered Tribosystems

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Ben D. Beake

2010-02-01

Full Text Available Self-organization during friction in complex surface engineered tribosystems is investigated. The probability of self-organization in these complex tribosystems is studied on the basis of the theoretical concepts of irreversible thermodynamics. It is shown that a higher number of interrelated processes within the system result in an increased probability of self-organization. The results of this thermodynamic model are confirmed by the investigation of the wear performance of a novel Ti0.2Al0.55Cr0.2Si0.03Y0.02N/Ti0.25Al0.65Cr0.1N (PVD coating with complex nano-multilayered structure under extreme tribological conditions of dry high-speed end milling of hardened H13 tool steel.

Stability and responsiveness in a self-organized living architecture.

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Simon Garnier

Full Text Available Robustness and adaptability are central to the functioning of biological systems, from gene networks to animal societies. Yet the mechanisms by which living organisms achieve both stability to perturbations and sensitivity to input are poorly understood. Here, we present an integrated study of a living architecture in which army ants interconnect their bodies to span gaps. We demonstrate that these self-assembled bridges are a highly effective means of maintaining traffic flow over unpredictable terrain. The individual-level rules responsible depend only on locally-estimated traffic intensity and the number of neighbours to which ants are attached within the structure. We employ a parameterized computational model to reveal that bridges are tuned to be maximally stable in the face of regular, periodic fluctuations in traffic. However analysis of the model also suggests that interactions among ants give rise to feedback processes that result in bridges being highly responsive to sudden interruptions in traffic. Subsequent field experiments confirm this prediction and thus the dual nature of stability and flexibility in living bridges. Our study demonstrates the importance of robust and adaptive modular architecture to efficient traffic organisation and reveals general principles regarding the regulation of form in biological self-assemblies.

Tomographic anthropomorphic models. Pt. 2. Organ doses from computed tomographic examinations in paediatric radiology

International Nuclear Information System (INIS)

Zankl, M.; Panzer, W.; Drexler, G.

1993-11-01

This report provides a catalogue of organ dose conversion factors resulting from computed tomographic (CT) examinations of children. Two radiation qualities and two exposure geometries were simulated as well as the use of asymmetrical beams. The use of further beam shaping devices was not considered. The organ dose conversion factors are applicable to babies at the age of ca. 2 months and to children between 5 and 7 years but can be used for other ages as well with the appropriate adjustments. For the calculations, the patients were represented by the GSF tomographic anthropomorphic models BABY and CHILD. The radiation transport in the body was simulated using a Monte Carlo method. The doses are presented as conversion factors of mean organ doses per air kerma free in air on the axis of rotation. Mean organ dose conversion factors are given per organ and per scanned body section of 1 cm height. The mean dose to an organ resulting from a particular CT examination can be estimated by summing up the contributions to the organ dose from all relevant sections. To facilitate the selection of the appropriate sections, a table is given which relates the tomographic models' coordinates to certain anatomical landmarks in the human body. (orig.)

A computational model of selection by consequences.

OpenAIRE

McDowell, J J

2004-01-01

Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of computational experiments that arranged reinforcement according to random-interval (RI) schedules. The quantitative features of the model were varied o...

Self-organizing magnetic beads for biomedical applications

International Nuclear Information System (INIS)

Gusenbauer, Markus; Kovacs, Alexander; Reichel, Franz; Exl, Lukas; Bance, Simon; Özelt, Harald; Schrefl, Thomas

2012-01-01

In the field of biomedicine magnetic beads are used for drug delivery and to treat hyperthermia. Here we propose to use self-organized bead structures to isolate circulating tumor cells using lab-on-chip technologies. Typically blood flows past microposts functionalized with antibodies for circulating tumor cells. Creating these microposts with interacting magnetic beads makes it possible to tune the geometry in size, position and shape. We developed a simulation tool that combines micromagnetics and discrete particle dynamics, in order to design micropost arrays made of interacting beads. The simulation takes into account the viscous drag of the blood flow, magnetostatic interactions between the magnetic beads and gradient forces from external aligned magnets. We developed a particle–particle particle–mesh method for effective computation of the magnetic force and torque acting on the particles. - Highlights: ► We propose to use self-organized bead structures to isolate circulating tumor cells. ► Flexible ways are important to get a high probability of catching cancer cells. ► The beads make it possible to tune the geometry in size position and shape.

Measuring the Computer-Related Self-Concept

Science.gov (United States)

Langheinrich, Jessica; Schönfelder, Mona; Bogner, Franz X.

2016-01-01

A positive self-concept supposedly affects a student's well-being as well as his or her perception of individual competence at school. As computer-based learning is becoming increasingly important in school, a positive computer-related self-concept (CSC) might help to enhance cognitive achievement. Consequently, we focused on establishing a short,…

Order out of Randomness: Self-Organization Processes in Astrophysics

Science.gov (United States)

Aschwanden, Markus J.; Scholkmann, Felix; Béthune, William; Schmutz, Werner; Abramenko, Valentina; Cheung, Mark C. M.; Müller, Daniel; Benz, Arnold; Chernov, Guennadi; Kritsuk, Alexei G.; Scargle, Jeffrey D.; Melatos, Andrew; Wagoner, Robert V.; Trimble, Virginia; Green, William H.

2018-03-01

Self-organization is a property of dissipative nonlinear processes that are governed by a global driving force and a local positive feedback mechanism, which creates regular geometric and/or temporal patterns, and decreases the entropy locally, in contrast to random processes. Here we investigate for the first time a comprehensive number of (17) self-organization processes that operate in planetary physics, solar physics, stellar physics, galactic physics, and cosmology. Self-organizing systems create spontaneous " order out of randomness", during the evolution from an initially disordered system to an ordered quasi-stationary system, mostly by quasi-periodic limit-cycle dynamics, but also by harmonic (mechanical or gyromagnetic) resonances. The global driving force can be due to gravity, electromagnetic forces, mechanical forces (e.g., rotation or differential rotation), thermal pressure, or acceleration of nonthermal particles, while the positive feedback mechanism is often an instability, such as the magneto-rotational (Balbus-Hawley) instability, the convective (Rayleigh-Bénard) instability, turbulence, vortex attraction, magnetic reconnection, plasma condensation, or a loss-cone instability. Physical models of astrophysical self-organization processes require hydrodynamic, magneto-hydrodynamic (MHD), plasma, or N-body simulations. Analytical formulations of self-organizing systems generally involve coupled differential equations with limit-cycle solutions of the Lotka-Volterra or Hopf-bifurcation type.

A self-organized system of smart preys and predators

Energy Technology Data Exchange (ETDEWEB)

Rozenfeld, Alejandro F. [Instituto de Investigaciones Fisicoquimicas Teoricas y Aplicadas (INIFTA), Facultad de Ciencias Exactas, UNLP, CONICET, Suc. 4, C.C. 16 (1900) La Plata (Argentina); Albano, Ezequiel V. [Instituto de Investigaciones Fisicoquimicas Teoricas y Aplicadas (INIFTA), Facultad de Ciencias Exactas, UNLP, CONICET, Suc. 4, C.C. 16 (1900) La Plata (Argentina)]. E-mail: ealbano@inifta.unlp.edu.ar

2004-11-22

Based on the fact that, a standard prey-predator model (SPPM), exhibits irreversible phase transitions, belonging to the universality class of directed percolation (DP), between prey-predator coexistence and predator extinction [Phys. Lett. A 280 (2001) 45], a self-organized prey-predator model (SOPPM) is formulated and studied by means of extensive Monte Carlo simulations. The SOPPM is achieved defining the parameters of the SPPM as functions of the density of species. It is shown that the SOPPM self-organizes into an active state close the absorbing phase of the SPPM, and consequently their avalanche exponents also belong to the universality class of DP.

A self-organizing state-space-model approach for parameter estimation in hodgkin-huxley-type models of single neurons.

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Dimitrios V Vavoulis

Full Text Available Traditional approaches to the problem of parameter estimation in biophysical models of neurons and neural networks usually adopt a global search algorithm (for example, an evolutionary algorithm, often in combination with a local search method (such as gradient descent in order to minimize the value of a cost function, which measures the discrepancy between various features of the available experimental data and model output. In this study, we approach the problem of parameter estimation in conductance-based models of single neurons from a different perspective. By adopting a hidden-dynamical-systems formalism, we expressed parameter estimation as an inference problem in these systems, which can then be tackled using a range of well-established statistical inference methods. The particular method we used was Kitagawa's self-organizing state-space model, which was applied on a number of Hodgkin-Huxley-type models using simulated or actual electrophysiological data. We showed that the algorithm can be used to estimate a large number of parameters, including maximal conductances, reversal potentials, kinetics of ionic currents, measurement and intrinsic noise, based on low-dimensional experimental data and sufficiently informative priors in the form of pre-defined constraints imposed on model parameters. The algorithm remained operational even when very noisy experimental data were used. Importantly, by combining the self-organizing state-space model with an adaptive sampling algorithm akin to the Covariance Matrix Adaptation Evolution Strategy, we achieved a significant reduction in the variance of parameter estimates. The algorithm did not require the explicit formulation of a cost function and it was straightforward to apply on compartmental models and multiple data sets. Overall, the proposed methodology is particularly suitable for resolving high-dimensional inference problems based on noisy electrophysiological data and, therefore, a

International Conference on Computational Intelligence, Cyber Security, and Computational Models

CERN Document Server

Ramasamy, Vijayalakshmi; Sheen, Shina; Veeramani, C; Bonato, Anthony; Batten, Lynn

2016-01-01

This book aims at promoting high-quality research by researchers and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security, and Computational Models ICC3 2015 organized by PSG College of Technology, Coimbatore, India during December 17 – 19, 2015. This book enriches with innovations in broad areas of research like computational modeling, computational intelligence and cyber security. These emerging inter disciplinary research areas have helped to solve multifaceted problems and gained lot of attention in recent years. This encompasses theory and applications, to provide design, analysis and modeling of the aforementioned key areas.

Development and comparison of computational models for estimation of absorbed organ radiation dose in rainbow trout (Oncorhynchus mykiss) from uptake of iodine-131

International Nuclear Information System (INIS)

Martinez, N.E.; Johnson, T.E.; Capello, K.; Pinder, J.E.

2014-01-01

This study develops and compares different, increasingly detailed anatomical phantoms for rainbow trout (Oncorhynchus mykiss) for the purpose of estimating organ absorbed radiation dose and dose rates from 131 I uptake in multiple organs. The models considered are: a simplistic geometry considering a single organ, a more specific geometry employing additional organs with anatomically relevant size and location, and voxel reconstruction of internal anatomy obtained from CT imaging (referred to as CSUTROUT). Dose Conversion Factors (DCFs) for whole body as well as selected organs of O. mykiss were computed using Monte Carlo modeling, and combined with estimated activity concentrations, to approximate dose rates and ultimately determine cumulative radiation dose (μGy) to selected organs after several half-lives of 131 I. The different computational models provided similar results, especially for source organs (less than 30% difference between estimated doses), and whole body DCFs for each model (∼3 × 10 −3 μGy d −1 per Bq kg −1 ) were comparable to DCFs listed in ICRP 108 for 131 I. The main benefit provided by the computational models developed here is the ability to accurately determine organ dose. A conservative mass-ratio approach may provide reasonable results for sufficiently large organs, but is only applicable to individual source organs. Although CSUTROUT is the more anatomically realistic phantom, it required much more resource dedication to develop and is less flexible than the stylized phantom for similar results. There may be instances where a detailed phantom such as CSUTROUT is appropriate, but generally the stylized phantom appears to be the best choice for an ideal balance between accuracy and resource requirements. - Highlights: • Computational models (phantoms) are developed for rainbow trout internal dosimetry. • Phantoms are combined with empirical models for 131 I uptake to estimate dose. • Voxel and stylized phantoms predict

Self-organized criticality as a paradigm for transport processes in magnetically confined plasma

International Nuclear Information System (INIS)

Karreras, B.A.; N'yuman, D.; Linch, V.E.

1996-01-01

Many models of natural events prove the basic hypotheses of self-organized critically. The concept on self-organized criticality combines self similarity on a spatial and time scale, characteristic of many such events. Application of the self-organized criticality concept to plasma dynamics close to the stability limit opens new possibilities for comprehension of such events as the Bom scaling, profile selfconsistency, wide band fluctuation spectra with universal characteristics and small time scales. Refs. 51, figs. 17

Unsupervised learning via self-organization a dynamic approach

CERN Document Server

Kyan, Matthew; Jarrah, Kambiz; Guan, Ling

2014-01-01

To aid in intelligent data mining, this book introduces a new family of unsupervised algorithms that have a basis in self-organization, yet are free from many of the constraints typical of other well known self-organizing architectures. It then moves through a series of pertinent real world applications with regards to the processing of multimedia data from its role in generic image processing techniques such as the automated modeling and removal of impulse noise in digital images, to problems in digital asset management, and its various roles in feature extraction, visual enhancement, segmentation, and analysis of microbiological image data.

Surface self-organization: From wear to self-healing in biological and technical surfaces

International Nuclear Information System (INIS)

Nosonovsky, Michael; Bhushan, Bharat

2010-01-01

Wear occurs at most solid surfaces that come in contact with other solid surfaces. While biological surfaces and tissues usually have the ability for self-healing, engineered self-healing materials only started to emerge recently. These materials are currently created using the trial-and-error approach and phenomenological models, so there is a need of a general first-principles theory of self-healing. We discuss the conditions under which the self-healing occurs and provide a general theoretical framework and criteria for self-healing using the concept of multiscale organization of entropy and non-equilibrium thermodynamics. The example of epicuticular wax regeneration of plant leaves is discussed as a case study.

RM-SORN: a reward-modulated self-organizing recurrent neural network.

Science.gov (United States)

Aswolinskiy, Witali; Pipa, Gordon

2015-01-01

Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

Faults self-organized by repeated earthquakes in a quasi-static antiplane crack model

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D. Sornette

1996-01-01

Full Text Available We study a 2D quasi-static discrete crack anti-plane model of a tectonic plate with long range elastic forces and quenched disorder. The plate is driven at its border and the load is transferred to all elements through elastic forces. This model can be considered as belonging to the class of self-organized models which may exhibit spontaneous criticality, with four additional ingredients compared to sandpile models, namely quenched disorder, boundary driving, long range forces and fast time crack rules. In this 'crack' model, as in the 'dislocation' version previously studied, we find that the occurrence of repeated earthquakes organizes the activity on well-defined fault-like structures. In contrast with the 'dislocation' model, after a transient, the time evolution becomes periodic with run-aways ending each cycle. This stems from the 'crack' stress transfer rule preventing criticality to organize in favour of cyclic behaviour. For sufficiently large disorder and weak stress drop, these large events are preceded by a complex spacetime history of foreshock activity, characterized by a Gutenberg-Richter power law distribution with universal exponent B = 1±0.05. This is similar to a power law distribution of small nucleating droplets before the nucleation of the macroscopic phase in a first-order phase transition. For large disorder and large stress drop, and for certain specific initial disorder configurations, the stress field becomes frustrated in fast time: out-of-plane deformations (thrust and normal faulting and/or a genuine dynamics must be introduced to resolve this frustration.

Context-aware computing and self-managing systems

CERN Document Server

Dargie, Waltenegus

2009-01-01

Bringing together an extensively researched area with an emerging research issue, Context-Aware Computing and Self-Managing Systems presents the core contributions of context-aware computing in the development of self-managing systems, including devices, applications, middleware, and networks. The expert contributors reveal the usefulness of context-aware computing in developing autonomous systems that have practical application in the real world.The first chapter of the book identifies features that are common to both context-aware computing and autonomous computing. It offers a basic definit

Self-organization in a simple model of adaptive agents playing 2 x 2 games with arbitrary payoff matrices.

Science.gov (United States)

Fort, H; Viola, S

2004-03-01

We analyze, both analytically and numerically, the self-organization of a system of "selfish" adaptive agents playing an arbitrary iterated pairwise game (defined by a 2 x 2 payoff matrix). Examples of possible games to play are the prisoner's dilemma (PD) game, the chicken game, the hero game, etc. The agents have no memory, use strategies not based on direct reciprocity nor "tags" and are chosen at random, i.e., geographical vicinity is neglected. They can play two possible strategies: cooperate (C) or defect (D). The players measure their success by comparing their utilities with an estimate for the expected benefits and update their strategy following a simple rule. Two versions of the model are studied: (1) the deterministic version (the agents are either in definite states C or D) and (2) the stochastic version (the agents have a probability c of playing C). Using a general master equation we compute the equilibrium states into which the system self-organizes, characterized by their average probability of cooperation c(eq). Depending on the payoff matrix, we show that c(eq) can take five different values. We also consider the mixing of agents using two different payoff matrices and show that any value of c(eq) can be reached by tuning the proportions of agents using each payoff matrix. In particular, this can be used as a way to simulate the effect of a fraction d of "antisocial" individuals--incapable of realizing any value to cooperation--on the cooperative regime hold by a population of neutral or "normal" agents.

Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption

OpenAIRE

Bao, Yukun; Xiong, Tao; Hu, Zhongyi; Kibelloh, Mboni

2014-01-01

Reasons for contradictory findings regarding the gender moderate effect on computer self-efficacy in the adoption of e-learning/mobile learning are limited. Recognizing the multilevel nature of the computer self-efficacy (CSE), this study attempts to explore gender differences in the adoption of mobile learning, by extending the Technology Acceptance Model (TAM) with general and specific CSE. Data collected from 137 university students were tested against the research model using the structur...

Neurons compute internal models of the physical laws of motion.

Science.gov (United States)

Angelaki, Dora E; Shaikh, Aasef G; Green, Andrea M; Dickman, J David

2004-07-29

A critical step in self-motion perception and spatial awareness is the integration of motion cues from multiple sensory organs that individually do not provide an accurate representation of the physical world. One of the best-studied sensory ambiguities is found in visual processing, and arises because of the inherent uncertainty in detecting the motion direction of an untextured contour moving within a small aperture. A similar sensory ambiguity arises in identifying the actual motion associated with linear accelerations sensed by the otolith organs in the inner ear. These internal linear accelerometers respond identically during translational motion (for example, running forward) and gravitational accelerations experienced as we reorient the head relative to gravity (that is, head tilt). Using new stimulus combinations, we identify here cerebellar and brainstem motion-sensitive neurons that compute a solution to the inertial motion detection problem. We show that the firing rates of these populations of neurons reflect the computations necessary to construct an internal model representation of the physical equations of motion.

Spatial self-organization in a multi-strain host–pathogen system

International Nuclear Information System (INIS)

Liu, Quan-Xing; Van de Koppel, Johan; Wang, Rong-Hua; Jin, Zhen; Alonso, David

2010-01-01

We develop stochastic spatial epidemic models with the competition of two pathogenic strains. The dynamics resulting from different approaches are examined using both non-spatial and spatially explicit models. Our results show that pair approximation, well-mixed ordinary differential equations (ODEs), Gillespie-algorithm-based simulations and spatially explicit models give similar qualitative results. In particular, the temporal evolution of the spatial model can be successfully approximated by pair equations. Simulation results obtained from the spatially explicit model show that, first, mutation plays a major role in multi-strain coexistence, second, mild virulence remarkably decreases the coexistence domain of the parameter space and, third, large-scale self-organized spatial patterns emerge for a wide range of transmission and virulence parameter values, where spatial self-organized clusters reveal a power law behavior within the coexistence domain

Non-Taylor magnetohydrodynamic self-organization

International Nuclear Information System (INIS)

Zhu, Shao-ping; Horiuchi, Ritoku; Sato, Tetsuya.

1994-10-01

A self-organization process in a plasma with a finite pressure is investigated by means of a three-dimensional magnetohydrodynamic simulation. It is demonstrated that a non-Taylor finite β self-organized state is realized in which a perpendicular component of the electric current is generated and the force-free(parallel) current decreases until they reach to almost the same level. The self-organized state is described by an MHD force-balance relation, namely, j perpendicular = B x ∇p/B·B and j parallel = μB where μ is not a constant, and the pressure structure resembles the structure of the toroidal magnetic field intensity. Unless an anomalous perpendicular thermal conduction arises, the plasma cannot relax to a Taylor state but to a non-Taylor (non-force-free) self-organized state. This state becomes more prominent for a weaker resistivity condition. The non-Taylor state has a rather universal property, for example, independence of the initial β value. Another remarkable finding is that the Taylor's conjecture of helicity conservation is, in a strict sense, not valid. The helicity dissipation occurs and its rate slows down critically in accordance with the stepwise relaxation of the magnetic energy. It is confirmed that the driven magnetic reconnection caused by the nonlinearly excited plasma kink flows plays the leading role in all of these key features of the non-Taylor self-organization. (author)

How nature works the science of self-organized criticality

CERN Document Server

Bak, Per

1996-01-01

This is an acclaimed book intended for the general reader who is interested in science. The author is a physicist who is well-known for his development of the property called "self-organized criticality", a property or phenomenon that lies at the heart of large dynamical systems. It can be used to analyse systems that are complicated, and which are part of the new science of complexity. It is a unifying concept that can be used to study phenomena in fields as diverse as economics, astronomy, the earth sciences, and physics. The author discusses his discovery of self-organized criticality; its relation to the world of classical physics; computer simulations and experiments which aid scientists' understanding of the property; and the relation of the subject to popular areas such as fractal geometry and power laws; cellular automata, and a wide range of practical applications.

Self: an adaptive pressure arising from self-organization, chaotic dynamics, and neural Darwinism.

Science.gov (United States)

Bruzzo, Angela Alessia; Vimal, Ram Lakhan Pandey

2007-12-01

In this article, we establish a model to delineate the emergence of "self" in the brain making recourse to the theory of chaos. Self is considered as the subjective experience of a subject. As essential ingredients of subjective experiences, our model includes wakefulness, re-entry, attention, memory, and proto-experiences. The stability as stated by chaos theory can potentially describe the non-linear function of "self" as sensitive to initial conditions and can characterize it as underlying order from apparently random signals. Self-similarity is discussed as a latent menace of a pathological confusion between "self" and "others". Our test hypothesis is that (1) consciousness might have emerged and evolved from a primordial potential or proto-experience in matter, such as the physical attractions and repulsions experienced by electrons, and (2) "self" arises from chaotic dynamics, self-organization and selective mechanisms during ontogenesis, while emerging post-ontogenically as an adaptive pressure driven by both volume and synaptic-neural transmission and influencing the functional connectivity of neural nets (structure).

Supervised self-organization of homogeneous swarms using ergodic projections of Markov chains.

Science.gov (United States)

Chattopadhyay, Ishanu; Ray, Asok

2009-12-01

This paper formulates a self-organization algorithm to address the problem of global behavior supervision in engineered swarms of arbitrarily large population sizes. The swarms considered in this paper are assumed to be homogeneous collections of independent identical finite-state agents, each of which is modeled by an irreducible finite Markov chain. The proposed algorithm computes the necessary perturbations in the local agents' behavior, which guarantees convergence to the desired observed state of the swarm. The ergodicity property of the swarm, which is induced as a result of the irreducibility of the agent models, implies that while the local behavior of the agents converges to the desired behavior only in the time average, the overall swarm behavior converges to the specification and stays there at all times. A simulation example illustrates the underlying concept.

Topological self-organization and prediction learning support both action and lexical chains in the brain.

Science.gov (United States)

Chersi, Fabian; Ferro, Marcello; Pezzulo, Giovanni; Pirrelli, Vito

2014-07-01

A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, the network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall. Copyright © 2014 Cognitive Science Society, Inc.

The concept of self-organizing systems. Why bother?

Science.gov (United States)

Elverfeldt, Kirsten v.; Embleton-Hamann, Christine; Slaymaker, Olav

2016-04-01

Complexity theory and the concept of self-organizing systems provide a rather challenging conceptual framework for explaining earth systems change. Self-organization - understood as the aggregate processes internal to an environmental system that lead to a distinctive spatial or temporal organization - reduces the possibility of implicating a specific process as being causal, and it poses some restrictions on the idea that external drivers cause a system to change. The concept of self-organizing systems suggests that many phenomena result from an orchestration of different mechanisms, so that no causal role can be assigned to an individual factor or process. The idea that system change can be due to system-internal processes of self-organization thus proves a huge challenge to earth system research, especially in the context of global environmental change. In order to understand the concept's implications for the Earth Sciences, we need to know the characteristics of self-organizing systems and how to discern self-organizing systems. Within the talk, we aim firstly at characterizing self-organizing systems, and secondly at highlighting the advantages and difficulties of the concept within earth system sciences. The presentation concludes that: - The concept of self-organizing systems proves especially fruitful for small-scale earth surface systems. Beach cusps and patterned ground are only two of several other prime examples of self-organizing earth surface systems. They display characteristics of self-organization like (i) system-wide order from local interactions, (ii) symmetry breaking, (iii) distributed control, (iv) robustness and resilience, (v) nonlinearity and feedbacks, (vi) organizational closure, (vii) adaptation, and (viii) variation and selection. - It is comparatively easy to discern self-organization in small-scale systems, but to adapt the concept to larger scale systems relevant to global environmental change research is more difficult: Self-organizing

MIANN models in medicinal, physical and organic chemistry.

Science.gov (United States)

González-Díaz, Humberto; Arrasate, Sonia; Sotomayor, Nuria; Lete, Esther; Munteanu, Cristian R; Pazos, Alejandro; Besada-Porto, Lina; Ruso, Juan M

2013-01-01

Reducing costs in terms of time, animal sacrifice, and material resources with computational methods has become a promising goal in Medicinal, Biological, Physical and Organic Chemistry. There are many computational techniques that can be used in this sense. In any case, almost all these methods focus on few fundamental aspects including: type (1) methods to quantify the molecular structure, type (2) methods to link the structure with the biological activity, and others. In particular, MARCH-INSIDE (MI), acronym for Markov Chain Invariants for Networks Simulation and Design, is a well-known method for QSAR analysis useful in step (1). In addition, the bio-inspired Artificial-Intelligence (AI) algorithms called Artificial Neural Networks (ANNs) are among the most powerful type (2) methods. We can combine MI with ANNs in order to seek QSAR models, a strategy which is called herein MIANN (MI & ANN models). One of the first applications of the MIANN strategy was in the development of new QSAR models for drug discovery. MIANN strategy has been expanded to the QSAR study of proteins, protein-drug interactions, and protein-protein interaction networks. In this paper, we review for the first time many interesting aspects of the MIANN strategy including theoretical basis, implementation in web servers, and examples of applications in Medicinal and Biological chemistry. We also report new applications of the MIANN strategy in Medicinal chemistry and the first examples in Physical and Organic Chemistry, as well. In so doing, we developed new MIANN models for several self-assembly physicochemical properties of surfactants and large reaction networks in organic synthesis. In some of the new examples we also present experimental results which were not published up to date.

Effect of prediction on the self-organization of pedestrian counter flow

International Nuclear Information System (INIS)

Wang Ziyang; Zhao Hui; Ma Jian; Qin Yong; Jia Limin

2012-01-01

Pedestrians may predict the behavior of others and then adjust their movement accordingly to avoid potential conflicts in advance. Motivated by this fact, we propose a predictive control theory-based pedestrian counter flow model, which describes the predictive mechanism underlying pedestrian self-organization phenomena. In this model, a pedestrian will make in-advance-avoid behavior based on the estimation of future moving gain within a given predictive length to reduce potential conflicts. The future gain in the present model is affected by three factors, i.e. the predictive length, the smooth degree of entrance and the influential area of coming pedestrians. Simulation results of the model show that increasing predictive length has a remarkable effect on reducing conflicts, improving pedestrian velocity, smoothing pedestrian movement and stabilizing the self-organized lanes. When enlarging the influential area of coming pedestrians, pedestrians tend to aggregate to the formed self-organized lanes, which makes the lanes wider and the lane number reduced. Interestingly, moderate enlargement (of the influential area) will reduce conflicts significantly, while excessive enlargement will lead to an increase in conflicts. We also discuss the predictive effect toward the smooth degree of entrance. When there are some formed self-organized lanes in the system, the effect is significant, and it will make the lanes more regular and stable, while when the existing lanes are unstable, the effect has little impact on the system. (paper)

Self-Organizing Neural Circuits for Sensory-Guided Motor Control

National Research Council Canada - National Science Library

Grossberg, Stephen

1999-01-01

The reported projects developed mathematical models to explain how self-organizing neural circuits that operate under continuous or intermittent sensory guidance achieve flexible and accurate control of human movement...

Impacts of mothers' occupation status and parenting styles on levels of self-control, addiction to computer games, and educational progress of adolescents.

Science.gov (United States)

Abedini, Yasamin; Zamani, Bibi Eshrat; Kheradmand, Ali; Rajabizadeh, Ghodratollah

2012-01-01

Addiction to computer (video) games in adolescents and its relationship with educational progress has recently attracted the attention of rearing and education experts as well as organizations and institutes involved in physical and mental health. The current research attempted to propose a structural model of the relationships between parenting styles, mothers' occupation status, and addiction to computer games, self-control, and educational progress of secondary school students. Using multistage cluster random sampling, 500 female and male secondary school students in Kerman (Iran) were selected and studied. The research tools included self-control, parenting styles, and addiction to computer games questionnaires and a self-made questionnaire containing demographic details. The data was analyzed using exploratory factor analysis, Cronbach's alpha coefficient and route analysis (in LISREL). We found self-control to have a linking role in the relationship between four parenting styles and educational progress. Mothers' occupation status was directly and significantly correlated with addiction to computer games. Although four parenting styles directly and significantly affected addiction to computer games, the findings did not support the linking role of addiction to computer games in the relationship between four parenting styles and educational progress. In agreement with previous studies, the current research reflected the impact of four parenting styles on self-control, addiction to computer games, and educational progress of students. Among the parenting styles, authoritative style can affect the severity of addiction to computer games through self-control development. It can thus indirectly influence the educational progress of students. Parents are recommended to use authoritative parenting style to help both self-management and psychological health of their children. The employed mothers are also recommended to have more supervision and control on the degree

Impacts of Mothers’ Occupation Status and Parenting Styles on Levels of Self-Control, Addiction to Computer Games, and Educational Progress of Adolescents

Science.gov (United States)

Abedini, Yasamin; Zamani, Bibi Eshrat; Kheradmand, Ali; Rajabizadeh, Ghodratollah

2012-01-01

Background Addiction to computer (video) games in adolescents and its relationship with educational progress has recently attracted the attention of rearing and education experts as well as organizations and institutes involved in physical and mental health. The current research attempted to propose a structural model of the relationships between parenting styles, mothers’ occupation status, and addiction to computer games, self-control, and educational progress of secondary school students. Methods Using multistage cluster random sampling, 500 female and male secondary school students in Kerman (Iran) were selected and studied. The research tools included self-control, parenting styles, and addiction to computer games questionnaires and a self-made questionnaire containing demographic details. The data was analyzed using exploratory factor analysis, Cronbach’s alpha coefficient and route analysis (in LISREL). Findings We found self-control to have a linking role in the relationship between four parenting styles and educational progress. Mothers’ occupation status was directly and significantly correlated with addiction to computer games. Although four parenting styles directly and significantly affected addiction to computer games, the findings did not support the linking role of addiction to computer games in the relationship between four parenting styles and educational progress. Conclusion In agreement with previous studies, the current research reflected the impact of four parenting styles on self-control, addiction to computer games, and educational progress of students. Among the parenting styles, authoritative style can affect the severity of addiction to computer games through self-control development. It can thus indirectly influence the educational progress of students. Parents are recommended to use authoritative parenting style to help both self-management and psychological health of their children. The employed mothers are also recommended to

Motivation and performance within a collaborative computer-based modeling task: Relations between student's achievement goal orientation, self-efficiacy, cognitive processing and achievement.

NARCIS (Netherlands)

Sins, Patrick H.M.; van Joolingen, Wouter; Savelsbergh, Elwin R.; van Hout-Wolters, Bernadette

2008-01-01

Purpose of the present study was to test a conceptual model of relations among achievement goal orientation, self-efficacy, cognitive processing, and achievement of students working within a particular collaborative task context. The task involved a collaborative computer-based modeling task. In

Motivation and performance within a collaborative computer-based modeling task: Relations between students' achievement goal orientation, self-efficacy, cognitive processing and achievement

NARCIS (Netherlands)

Sins, P.H.M.; van Joolingen, W.R.; Savelsbergh, E.R.; van Hout-Wolters, B.H.A.M.

2008-01-01

Purpose of the present study was to test a conceptual model of relations among achievement goal orientation, self-efficacy, cognitive processing, and achievement of students working within a particular collaborative task context. The task involved a collaborative computer-based modeling task. In

Do's and Don'ts of Computer Models for Planning

Science.gov (United States)

Hammond, John S., III

1974-01-01

Concentrates on the managerial issues involved in computer planning models. Describes what computer planning models are and the process by which managers can increase the likelihood of computer planning models being successful in their organizations. (Author/DN)

Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

Science.gov (United States)

Hortos, William S.

2006-05-01

A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the

Automatic lithofacies segmentation from well-logs data. A comparative study between the Self-Organizing Map (SOM) and Walsh transform

Science.gov (United States)

Aliouane, Leila; Ouadfeul, Sid-Ali; Rabhi, Abdessalem; Rouina, Fouzi; Benaissa, Zahia; Boudella, Amar

2013-04-01

The main goal of this work is to realize a comparison between two lithofacies segmentation techniques of reservoir interval. The first one is based on the Kohonen's Self-Organizing Map neural network machine. The second technique is based on the Walsh transform decomposition. Application to real well-logs data of two boreholes located in the Algerian Sahara shows that the Self-organizing map is able to provide more lithological details that the obtained lithofacies model given by the Walsh decomposition. Keywords: Comparison, Lithofacies, SOM, Walsh References: 1)Aliouane, L., Ouadfeul, S., Boudella, A., 2011, Fractal analysis based on the continuous wavelet transform and lithofacies classification from well-logs data using the self-organizing map neural network, Arabian Journal of geosciences, doi: 10.1007/s12517-011-0459-4 2) Aliouane, L., Ouadfeul, S., Djarfour, N., Boudella, A., 2012, Petrophysical Parameters Estimation from Well-Logs Data Using Multilayer Perceptron and Radial Basis Function Neural Networks, Lecture Notes in Computer Science Volume 7667, 2012, pp 730-736, doi : 10.1007/978-3-642-34500-5_86 3)Ouadfeul, S. and Aliouane., L., 2011, Multifractal analysis revisited by the continuous wavelet transform applied in lithofacies segmentation from well-logs data, International journal of applied physics and mathematics, Vol01 N01. 4) Ouadfeul, S., Aliouane, L., 2012, Lithofacies Classification Using the Multilayer Perceptron and the Self-organizing Neural Networks, Lecture Notes in Computer Science Volume 7667, 2012, pp 737-744, doi : 10.1007/978-3-642-34500-5_87 5) Weisstein, Eric W. "Fast Walsh Transform." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/FastWalshTransform.html

Computer self-efficacy - is there a gender gap in tertiary level introductory computing classes?

Directory of Open Access Journals (Sweden)

Shirley Gibbs

Full Text Available This paper explores the relationship between introductory computing students, self-efficacy, and gender. Since the use of computers has become more common there has been speculation that the confidence and ability to use them differs between genders. Self-efficacy is an important and useful concept used to describe how a student may perceive their own ability or confidence in using and learning new technology. A survey of students in an introductory computing class has been completed intermittently since the late 1990\\'s. Although some questions have been adapted to meet the changing technology the aim of the survey has remain unchanged. In this study self-efficacy is measured using two self-rating questions. Students are asked to rate their confidence using a computer and also asked to give their perception of their computing knowledge. This paper examines these two aspects of a person\\'s computer self-efficacy in order to identify any differences that may occur between genders in two introductory computing classes, one in 1999 and the other in 2012. Results from the 1999 survey are compared with those from the survey completed in 2012 and investigated to ascertain if the perception that males were more likely to display higher computer self-efficacy levels than their female classmates does or did exist in a class of this type. Results indicate that while overall there has been a general increase in self-efficacy levels in 2012 compared with 1999, there is no significant gender gap.

Long-time tails do not necessarily imply self-organized criticality or the breakdown of the standard transport paradigm

International Nuclear Information System (INIS)

Krommes, J.A.; Ottaviani, M.

2000-01-01

Numerical measurements and analytical studies are performed on a stochastic model with features relevant to plasma confinement. Although the model lacks crucial features of self-organized criticality (SOC) and its transport can be computed by standard techniques, it nevertheless exhibits intermittency and algebraic time correlations. This suggests that SOC need not be the explanation for observed long-time tails in experimental fluctuation data. Arguments based on the renormalized spectral balance equation, and simulation of a standard nonlinear paradigm, predict a range of Hurst exponents in reasonable agreement with the observations without invoking submarginal dynamics

Can government be self-organized? A mathematical model of the collective social organization of ancient Teotihuacan, central Mexico.

Directory of Open Access Journals (Sweden)

Tom Froese

Full Text Available Teotihuacan was the first urban civilization of Mesoamerica and one of the largest of the ancient world. Following a tradition in archaeology to equate social complexity with centralized hierarchy, it is widely believed that the city's origin and growth was controlled by a lineage of powerful individuals. However, much data is indicative of a government of co-rulers, and artistic traditions expressed an egalitarian ideology. Yet this alternative keeps being marginalized because the problems of collective action make it difficult to conceive how such a coalition could have functioned in principle. We therefore devised a mathematical model of the city's hypothetical network of representatives as a formal proof of concept that widespread cooperation was realizable in a fully distributed manner. In the model, decisions become self-organized into globally optimal configurations even though local representatives behave and modify their relations in a rational and selfish manner. This self-optimization crucially depends on occasional communal interruptions of normal activity, and it is impeded when sections of the network are too independent. We relate these insights to theories about community-wide rituals at Teotihuacan and the city's eventual disintegration.

Can government be self-organized? A mathematical model of the collective social organization of ancient Teotihuacan, central Mexico.

Science.gov (United States)

Froese, Tom; Gershenson, Carlos; Manzanilla, Linda R

2014-01-01

Teotihuacan was the first urban civilization of Mesoamerica and one of the largest of the ancient world. Following a tradition in archaeology to equate social complexity with centralized hierarchy, it is widely believed that the city's origin and growth was controlled by a lineage of powerful individuals. However, much data is indicative of a government of co-rulers, and artistic traditions expressed an egalitarian ideology. Yet this alternative keeps being marginalized because the problems of collective action make it difficult to conceive how such a coalition could have functioned in principle. We therefore devised a mathematical model of the city's hypothetical network of representatives as a formal proof of concept that widespread cooperation was realizable in a fully distributed manner. In the model, decisions become self-organized into globally optimal configurations even though local representatives behave and modify their relations in a rational and selfish manner. This self-optimization crucially depends on occasional communal interruptions of normal activity, and it is impeded when sections of the network are too independent. We relate these insights to theories about community-wide rituals at Teotihuacan and the city's eventual disintegration.

Temporal organization of cellular self-replication

Science.gov (United States)

Alexandrov, Victor; Pugatch, Rami

Recent experiments demonstrate that single cells grow exponentially in time. A coarse grained model of cellular self-replication is presented based on a novel concept - the cell is viewed as a self-replicating queue. This allows to have a more fundamental look into various temporal organizations and, importantly, the inherent non-Markovianity of noise distributions. As an example, the distribution of doubling times can be inferred and compared to single cell experiments in bacteria. We observe data collapse upon scaling by the average doubling time for different environments and present an inherent task allocation trade-off. Support from the Simons Center for Systems Biology, IAS, Princeon.

Self-Testing Computer Memory

Science.gov (United States)

Chau, Savio, N.; Rennels, David A.

1988-01-01

Memory system for computer repeatedly tests itself during brief, regular interruptions of normal processing of data. Detects and corrects transient faults as single-event upsets (changes in bits due to ionizing radiation) within milliseconds after occuring. Self-testing concept surpasses conventional by actively flushing latent defects out of memory and attempting to correct before accumulating beyond capacity for self-correction or detection. Cost of improvement modest increase in complexity of circuitry and operating time.

MultiSIMNRA: A computational tool for self-consistent ion beam analysis using SIMNRA

International Nuclear Information System (INIS)

Silva, T.F.; Rodrigues, C.L.; Mayer, M.; Moro, M.V.; Trindade, G.F.; Aguirre, F.R.; Added, N.; Rizzutto, M.A.; Tabacniks, M.H.

2016-01-01

Highlights: • MultiSIMNRA enables the self-consistent analysis of multiple ion beam techniques. • Self-consistent analysis enables unequivocal and reliable modeling of the sample. • Four different computational algorithms available for model optimizations. • Definition of constraints enables to include prior knowledge into the analysis. - Abstract: SIMNRA is widely adopted by the scientific community of ion beam analysis for the simulation and interpretation of nuclear scattering techniques for material characterization. Taking advantage of its recognized reliability and quality of the simulations, we developed a computer program that uses multiple parallel sessions of SIMNRA to perform self-consistent analysis of data obtained by different ion beam techniques or in different experimental conditions of a given sample. In this paper, we present a result using MultiSIMNRA for a self-consistent multi-elemental analysis of a thin film produced by magnetron sputtering. The results demonstrate the potentialities of the self-consistent analysis and its feasibility using MultiSIMNRA.

Computer Self-Efficacy: A Practical Indicator of Student Computer Competency in Introductory IS Courses

Directory of Open Access Journals (Sweden)

Rex Karsten

1998-01-01

Full Text Available Students often receive their first college-level computer training in introductory information systems courses. Students and faculty frequently expect this training to develop a level of student computer competence that will support computer use in future courses. In this study, we applied measures of computer self-efficacy to students in a typical introductory IS course. The measures provided useful evidence that student perceptions of their ability to use computers effectively in the future significantly improved as a result of their training experience. The computer self-efficacy measures also provided enhanced insight into course-related factors of practical concern to IS educators. Study results also suggest computer self-efficacy measures may be a practical and informative means of assessing computer-training outcomes in the introductory IS course context

An Analysis on the Effect of Computer Self-Efficacy over Scientific Research Self-Efficacy and Information Literacy Self-Efficacy

Science.gov (United States)

Tuncer, Murat

2013-01-01

Present research investigates reciprocal relations amidst computer self-efficacy, scientific research and information literacy self-efficacy. Research findings have demonstrated that according to standardized regression coefficients, computer self-efficacy has a positive effect on information literacy self-efficacy. Likewise it has been detected…

Physics of far-from-equilibrium systems and self-organization

International Nuclear Information System (INIS)

Nicolis, G.

1993-01-01

The status of self-organization phenomena from the stand point of the physical sciences are analyzed. Non linear dynamics and the presence of constraints maintaining the system far from equilibrium are shown to be the basic mechanism involved in the emergence of these phenomena. Some particularly representative experiments are first presented: thermal conversion, chemical reactions (Benard problem), biological systems, and their explanation through order, disorder, non-linearity, irreversibility, stability, bifurcation, symmetry breaking, etc., concepts. Then it is shown how the self-organization paradigm allows to model problems outside the traditional realm of the physical sciences. 29 figs., 27 refs

Perceptual organization in computer vision - A review and a proposal for a classificatory structure

Science.gov (United States)

Sarkar, Sudeep; Boyer, Kim L.

1993-01-01

The evolution of perceptual organization in biological vision, and its necessity in advanced computer vision systems, arises from the characteristic that perception, the extraction of meaning from sensory input, is an intelligent process. This is particularly so for high order organisms and, analogically, for more sophisticated computational models. The role of perceptual organization in computer vision systems is explored. This is done from four vantage points. First, a brief history of perceptual organization research in both humans and computer vision is offered. Next, a classificatory structure in which to cast perceptual organization research to clarify both the nomenclature and the relationships among the many contributions is proposed. Thirdly, the perceptual organization work in computer vision in the context of this classificatory structure is reviewed. Finally, the array of computational techniques applied to perceptual organization problems in computer vision is surveyed.

Influence of Selective Edge Removal and Refractory Period in a Self-Organized Critical Neuron Model

International Nuclear Information System (INIS)

Lin Min; Gang, Zhao; Chen Tianlun

2009-01-01

A simple model for a set of integrate-and-fire neurons based on the weighted network is introduced. By considering the neurobiological phenomenon in brain development and the difference of the synaptic strength, we construct weighted networks develop with link additions and followed by selective edge removal. The network exhibits the small-world and scale-free properties with high network efficiency. The model displays an avalanche activity on a power-law distribution. We investigate the effect of selective edge removal and the neuron refractory period on the self-organized criticality of the system. (condensed matter: structural, mechanical, and thermal properties)

Computer self-efficacy and computer attitude as correlates of ...

African Journals Online (AJOL)

The Internet as a useful tool that supports teaching and learning is not in full use in most secondary schools in Nigeria hence limiting the students from maximizing the potentials of Internet in advancing their academic pursuits. This study, therefore, examined the extent to which computer self-efficacy and computer attitude ...

Elementary EFL Teachers' Computer Phobia and Computer Self-Efficacy in Taiwan

Science.gov (United States)

Chen, Kate Tzuching

2012-01-01

The advent and application of computer and information technology has increased the overall success of EFL teaching; however, such success is hard to assess, and teachers prone to computer avoidance face negative consequences. Two major obstacles are high computer phobia and low computer self-efficacy. However, little research has been carried out…

Computer Self-Efficacy, Computer Anxiety, Performance and Personal Outcomes of Turkish Physical Education Teachers

Science.gov (United States)

Aktag, Isil

2015-01-01

The purpose of this study is to determine the computer self-efficacy, performance outcome, personal outcome, and affect and anxiety level of physical education teachers. Influence of teaching experience, computer usage and participation of seminars or in-service programs on computer self-efficacy level were determined. The subjects of this study…

On the self-organizing process of large scale shear flows

Energy Technology Data Exchange (ETDEWEB)

Newton, Andrew P. L. [Department of Applied Maths, University of Sheffield, Sheffield, Yorkshire S3 7RH (United Kingdom); Kim, Eun-jin [School of Mathematics and Statistics, University of Sheffield, Sheffield, Yorkshire S3 7RH (United Kingdom); Liu, Han-Li [High Altitude Observatory, National Centre for Atmospheric Research, P. O. BOX 3000, Boulder, Colorado 80303-3000 (United States)

2013-09-15

Self organization is invoked as a paradigm to explore the processes governing the evolution of shear flows. By examining the probability density function (PDF) of the local flow gradient (shear), we show that shear flows reach a quasi-equilibrium state as its growth of shear is balanced by shear relaxation. Specifically, the PDFs of the local shear are calculated numerically and analytically in reduced 1D and 0D models, where the PDFs are shown to converge to a bimodal distribution in the case of finite correlated temporal forcing. This bimodal PDF is then shown to be reproduced in nonlinear simulation of 2D hydrodynamic turbulence. Furthermore, the bimodal PDF is demonstrated to result from a self-organizing shear flow with linear profile. Similar bimodal structure and linear profile of the shear flow are observed in gulf stream, suggesting self-organization.

Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

Science.gov (United States)

Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

2016-02-01

A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration.

A Computational Model of Selection by Consequences

Science.gov (United States)

McDowell, J. J.

2004-01-01

Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of…

Feedback, Lineages and Self-Organizing Morphogenesis.

Directory of Open Access Journals (Sweden)

Sameeran Kunche

2016-03-01

Full Text Available Feedback regulation of cell lineage progression plays an important role in tissue size homeostasis, but whether such feedback also plays an important role in tissue morphogenesis has yet to be explored. Here we use mathematical modeling to show that a particular feedback architecture in which both positive and negative diffusible signals act on stem and/or progenitor cells leads to the appearance of bistable or bi-modal growth behaviors, ultrasensitivity to external growth cues, local growth-driven budding, self-sustaining elongation, and the triggering of self-organization in the form of lamellar fingers. Such behaviors arise not through regulation of cell cycle speeds, but through the control of stem or progenitor self-renewal. Even though the spatial patterns that arise in this setting are the result of interactions between diffusible factors with antagonistic effects, morphogenesis is not the consequence of Turing-type instabilities.

Feedback, Lineages and Self-Organizing Morphogenesis

Science.gov (United States)

Calof, Anne L.; Lowengrub, John S.; Lander, Arthur D.

2016-01-01

Feedback regulation of cell lineage progression plays an important role in tissue size homeostasis, but whether such feedback also plays an important role in tissue morphogenesis has yet to be explored. Here we use mathematical modeling to show that a particular feedback architecture in which both positive and negative diffusible signals act on stem and/or progenitor cells leads to the appearance of bistable or bi-modal growth behaviors, ultrasensitivity to external growth cues, local growth-driven budding, self-sustaining elongation, and the triggering of self-organization in the form of lamellar fingers. Such behaviors arise not through regulation of cell cycle speeds, but through the control of stem or progenitor self-renewal. Even though the spatial patterns that arise in this setting are the result of interactions between diffusible factors with antagonistic effects, morphogenesis is not the consequence of Turing-type instabilities. PMID:26989903

Self-organizing representations

Energy Technology Data Exchange (ETDEWEB)

Kohonen, T.

1983-01-01

A property which is commonplace in the brain but which has always been ignored in learning machines is the spatial order of the processing units. This order is clearly highly significant and in nature it develops gradually during the lifetime of the organism. It then serves as the basis for perceptual and cognitive processes, and memory, too. The spatial order in biological organisms is often believed to be genetically determined. It is therefore intriguing to learn that a meaningful and optimal spatial order is formed in an extremely simple self-organizing process whereby certain feature maps are formed automatically. 8 references.

Self-organizing biochemical cycle in dynamic feedback with soil structure

Science.gov (United States)

Vasilyeva, Nadezda; Vladimirov, Artem; Smirnov, Alexander; Matveev, Sergey; Tyrtyshnikov, Evgeniy; Yudina, Anna; Milanovskiy, Evgeniy; Shein, Evgeniy

2016-04-01

In the present study we perform bifurcation analysis of a physically-based mathematical model of self-organized structures in soil (Vasilyeva et al., 2015). The state variables in this model included microbial biomass, two organic matter types, oxygen, carbon dioxide, water content and capillary pore size. According to our previous experimental studies, organic matter affinity to water is an important property affecting soil structure. Therefore, organic matter wettability was taken as principle distinction between organic matter types in this model. It considers general known biological feedbacks with soil physical properties formulated as a system of parabolic type non-linear partial differential equations with elements of discrete modeling for water and pore formation. The model shows complex behavior, involving emergence of temporal and spatial irregular auto-oscillations from initially homogeneous distributions. The energy of external impact on a system was defined by a constant oxygen level on the boundary. Non-linear as opposed to linear oxygen diffusion gives possibility of modeling anaerobic micro-zones formation (organic matter conservation mechanism). For the current study we also introduced population competition of three different types of microorganisms according to their mobility/feeding (diffusive, moving and fungal growth). The strongly non-linear system was solved and parameterized by time-optimized algorithm combining explicit and implicit (matrix form of Thomas algorithm) methods considering the time for execution of the evaluated time-step according to accuracy control. The integral flux of the CO2 state variable was used as a macroscopic parameter to describe system as a whole and validation was carried out on temperature series of moisture dependence for soil heterotrophic respiration data. Thus, soil heterotrophic respiration can be naturally modeled as an integral result of complex dynamics on microscale, arising from biological processes

Information and Self-Organization A Macroscopic Approach to Complex Systems

CERN Document Server

Haken, Hermann

2006-01-01

This book presents the concepts needed to deal with self-organizing complex systems from a unifying point of view that uses macroscopic data. The various meanings of the concept "information" are discussed and a general formulation of the maximum information (entropy) principle is used. With the aid of results from synergetics, adequate objective constraints for a large class of self-organizing systems are formulated and examples are given from physics, life and computer science. The relationship to chaos theory is examined and it is further shown that, based on possibly scarce and noisy data, unbiased guesses about processes of complex systems can be made and the underlying deterministic and random forces determined. This allows for probabilistic predictions of processes, with applications to numerous fields in science, technology, medicine and economics. The extensions of the third edition are essentially devoted to an introduction to the meaning of information in the quantum context. Indeed, quantum inform...

Quantification of Hepatorenal Index for Computer-Aided Fatty Liver Classification with Self-Organizing Map and Fuzzy Stretching from Ultrasonography

Directory of Open Access Journals (Sweden)

Kwang Baek Kim

2015-01-01

Full Text Available Accurate measures of liver fat content are essential for investigating hepatic steatosis. For a noninvasive inexpensive ultrasonographic analysis, it is necessary to validate the quantitative assessment of liver fat content so that fully automated reliable computer-aided software can assist medical practitioners without any operator subjectivity. In this study, we attempt to quantify the hepatorenal index difference between the liver and the kidney with respect to the multiple severity status of hepatic steatosis. In order to do this, a series of carefully designed image processing techniques, including fuzzy stretching and edge tracking, are applied to extract regions of interest. Then, an unsupervised neural learning algorithm, the self-organizing map, is designed to establish characteristic clusters from the image, and the distribution of the hepatorenal index values with respect to the different levels of the fatty liver status is experimentally verified to estimate the differences in the distribution of the hepatorenal index. Such findings will be useful in building reliable computer-aided diagnostic software if combined with a good set of other characteristic feature sets and powerful machine learning classifiers in the future.

Autonomous distributed self-organizing and self-healing hardware architecture - The eDNA concept

DEFF Research Database (Denmark)

Boesen, Michael Reibel; Madsen, Jan; Keymeulen, Didier

2011-01-01

This paper presents the current state of the autonomous distributed self-organizing and self-healing electronic DNA (eDNA) hardware architecture (patent pending). In its current prototype state, the eDNA architecture is capable of responding to multiple injected faults by autonomously reconfiguring...... itself to accommodate the fault and keep the application running. This paper will also disclose advanced features currently available in the simulation model only. These features are future work and will soon be implemented in hardware. Finally we will describe step-by-step how an application...

Inducing self-organized criticality in a network toy model by neighborhood assortativity.

Science.gov (United States)

Allen-Perkins, Alfonso; Galeano, Javier; Pastor, Juan Manuel

2016-11-01

Complex networks are a recent type of framework used to study complex systems with many interacting elements, such as self-organized criticality (SOC). The network nodes' tendency to link to other nodes of similar type is characterized by assortative mixing. Real networks exhibit assortative mixing by vertex degree, however, typical random network models, such as the Erdős-Rényi or the Barabási-Albert model, show no assortative arrangements. In this paper we introduce the notion of neighborhood assortativity as the tendency of a node to belong to a community (its neighborhood) showing an average property similar to its own. Imposing neighborhood assortative mixing by degree in a network toy model, SOC dynamics can be found. These dynamics are driven only by the network topology. The long-range correlations resulting from criticality have been characterized by means of fluctuation analysis and show an anticorrelation in the node's activity. The model contains only one parameter and its statistics plots for different values of the parameter can be collapsed into a single curve. The simplicity of the model allows us to perform numerical simulations and also to study analytically the statistics for a specific value of the parameter, making use of the Markov chains.

Emergent organization in a model market

Science.gov (United States)

Yadav, Avinash Chand; Manchanda, Kaustubh; Ramaswamy, Ramakrishna

2017-09-01

We study the collective behaviour of interacting agents in a simple model of market economics that was originally introduced by Nørrelykke and Bak. A general theoretical framework for interacting traders on an arbitrary network is presented, with the interaction consisting of buying (namely consumption) and selling (namely production) of commodities. Extremal dynamics is introduced by having the agent with least profit in the market readjust prices, causing the market to self-organize. In addition to examining this model market on regular lattices in two-dimensions, we also study the cases of random complex networks both with and without community structures. Fluctuations in an activity signal exhibit properties that are characteristic of avalanches observed in models of self-organized criticality, and these can be described by power-law distributions when the system is in the critical state.

Self-Organization of Motor-Propelled Cytoskeletal Filaments at Topographically Defined Borders

Directory of Open Access Journals (Sweden)

Alf Månsson

2012-01-01

Full Text Available Self-organization phenomena are of critical importance in living organisms and of great interest to exploit in nanotechnology. Here we describe in vitro self-organization of molecular motor-propelled actin filaments, manifested as a tendency of the filaments to accumulate in high density close to topographically defined edges on nano- and microstructured surfaces. We hypothesized that this “edge-tracing” effect either (1 results from increased motor density along the guiding edges or (2 is a direct consequence of the asymmetric constraints on stochastic changes in filament sliding direction imposed by the edges. The latter hypothesis is well captured by a model explicitly defining the constraints of motility on structured surfaces in combination with Monte-Carlo simulations [cf. Nitta et al. (2006] of filament sliding. In support of hypothesis 2 we found that the model reproduced the edge tracing effect without the need to assume increased motor density at the edges. We then used model simulations to elucidate mechanistic details. The results are discussed in relation to nanotechnological applications and future experiments to test model predictions.

Application of self-organizing competition artificial neural network to logging data explanation of sandstone-hosted uranium deposits

International Nuclear Information System (INIS)

Xu Jianguo; Xu Xianli; Wang Weiguo

2008-01-01

The article describes the model construction of self-organizing competition artificial neural network, its principle and automatic recognition process of borehole lithology in detail, and then proves the efficiency of the neural network model for automatically recognizing the borehole lithology with some cases. The self-organizing competition artificial neural network has the ability of self- organization, self-adjustment and high permitting errors. Compared with the BP algorithm, it takes less calculation quantity and more rapidly converges. Furthermore, it can automatically confirm the category without the known sample information. Trial results based on contrasting the identification results of the borehole lithology with geological documentations, indicate that self-organizing artificial neural network can be well applied to automatically performing the category of borehole lithology, during the logging data explanation of sandstone-hosted uranium deposits. (authors)

Interfacial self-organization of bolaamphiphiles bearing mesogenic groups: relationships between the molecular structures and their self-organized morphologies.

Science.gov (United States)

Song, Bo; Liu, Guanqing; Xu, Rui; Yin, Shouchun; Wang, Zhiqiang; Zhang, Xi

2008-04-15

This article discusses the relationship between the molecular structure of bolaamphiphiles bearing mesogenic groups and their interfacial self-organized morphology. On the basis of the molecular structures of bolaamphiphiles, we designed and synthesized a series of molecules with different hydrophobic alkyl chain lengths, hydrophilic headgroups, mesogenic groups, and connectors between the alkyl chains and the mesogenic group. Through investigating their interfacial self-organization behavior, some experiential rules are summarized: (1) An appropriate alkyl chain length is necessary to form stable surface micelles; (2) different categories of headgroups have a great effect on the interfacial self-organized morphology; (3) different types of mesogenic groups have little effect on the structure of the interfacial assembly when it is changed from biphenyl to azobenzene or stilbene; (4) the orientation of the ester linker between the mesogenic group and alkyl chain can greatly influence the interfacial self-organization behavior. It is anticipated that this line of research may be helpful for the molecular engineering of bolaamphiphiles to form tailor-made morphologies.

Kinetic Monte Carlo Modeling of Charge Carriers in Organic Electronic Devices: Suppression of the Self-Interaction Error

KAUST Repository

Li, Haoyuan

2017-05-18

Kinetic Monte Carlo (KMC) simulations have emerged as an important tool to help improve the efficiency of organic electronic devices by providing a better understanding of their device physics. In the KMC simulation of an organic device, the reliability of the results depends critically on the accuracy of the chosen charge-transfer rates, which are themselves strongly influenced by the site-energy differences. These site-energy differences include components coming from the electrostatic forces present in the system, which are often evaluated through electric potentials described by the Poisson equation. Here we show that the charge-carrier self-interaction errors that appear when evaluating the site-energy differences can lead to unreliable simulation results. To eliminate these errors, we propose two approaches that are also found to reduce the impact of finite-size effects. As a consequence, reliable results can be obtained at reduced computational costs. The proposed methodologies can be extended to other device simulation techniques as well.

Self-organization in metal complexes

International Nuclear Information System (INIS)

Radecka-Paryzek, W.

1999-01-01

Inorganic self-organization involves the spontaneous generation of well-defined supramolecular architectures from metal ions and organic ligands. The basic concept of supramolecular chemistry is a molecular recognition. When the substrate are metal ions, recognition is expressed in the stability and selectivity of metal ion complexation by organic ligands and depends on the geometry of the ligand and on their binding sites that it contains. The combination of the geometric features of the ligand units and the coordination geometries of the metal ions provides very efficient tool for the synthesis of novel, intriguing and highly sophisticated species such as catenanes, box structures, double and triple helicates with a variety of interesting properties. The article will focus on the examples of inorganic self-organization involving the templating as a first step for the assembly of supramolecular structures of high complexity. (author)

Quantitative Study on Computer Self-Efficacy and Computer Anxiety Differences in Academic Major and Residential Status

Science.gov (United States)

Binkley, Zachary Wayne McClellan

2017-01-01

This study investigates computer self-efficacy and computer anxiety within 61 students across two academic majors, Aviation and Sports and Exercise Science, while investigating the impact residential status, age, and gender has on those two psychological constructs. The purpose of the study is to find if computer self-efficacy and computer anxiety…

Applied Mathematics, Modelling and Computational Science

CERN Document Server

Kotsireas, Ilias; Makarov, Roman; Melnik, Roderick; Shodiev, Hasan

2015-01-01

The Applied Mathematics, Modelling, and Computational Science (AMMCS) conference aims to promote interdisciplinary research and collaboration. The contributions in this volume cover the latest research in mathematical and computational sciences, modeling, and simulation as well as their applications in natural and social sciences, engineering and technology, industry, and finance. The 2013 conference, the second in a series of AMMCS meetings, was held August 26–30 and organized in cooperation with AIMS and SIAM, with support from the Fields Institute in Toronto, and Wilfrid Laurier University. There were many young scientists at AMMCS-2013, both as presenters and as organizers. This proceedings contains refereed papers contributed by the participants of the AMMCS-2013 after the conference. This volume is suitable for researchers and graduate students, mathematicians and engineers, industrialists, and anyone who would like to delve into the interdisciplinary research of applied and computational mathematics ...

Developing and validating an instrument for measuring mobile computing self-efficacy.

Science.gov (United States)

Wang, Yi-Shun; Wang, Hsiu-Yuan

2008-08-01

IT-related self-efficacy has been found to have a critical influence on system use. However, traditional measures of computer self-efficacy and Internet-related self-efficacy are perceived to be inapplicable in the context of mobile computing and commerce because they are targeted primarily at either desktop computer or wire-based technology contexts. Based on previous research, this study develops and validates a multidimensional instrument for measuring mobile computing self-efficacy (MCSE). This empirically validated instrument will be useful to researchers in developing and testing the theories of mobile user behavior, and to practitioners in assessing the mobile computing self-efficacy of users and promoting the use of mobile commerce systems.

Self-esteem: models and implications for management

OpenAIRE

Becker, Manfred R.

1993-01-01

Approved for public release; distribution unlimited. This thesis presents a literature review of self-esteem, primarily as it relates to organizations and management. Based on this literature review, self-esteem is defined as the emotional valuation individuals have of themselves and the degree of certainty of this valuation. Several models of self-esteem are presented. The relationship of coping and avoidance to self-esteem is considered. Coping is presented as being one of the primary so...

Self-organizing networks

DEFF Research Database (Denmark)

Marchetti, Nicola; Prasad, Neeli R.; Johansson, Johan

2010-01-01

In this paper, a general overview of Self-Organizing Networks (SON), and the rationale and state-of-the-art of wireless SON are first presented. The technical and business requirements are then briefly treated, and the research challenges within the field of SON are highlighted. Thereafter, the r...

Organ burdens and excretion rates of inhaled uranium - computations using ICRP model

International Nuclear Information System (INIS)

Abani, M.C.; Murthy, K.B.S.; Sunta, C.M.

1988-01-01

Uranium being a highly toxic material, proper estimation of the body burden is very important. During manufacture of uranium fuel, it is likely to enter the body by inhalation. By the body burden and excretion measurements, one should be able to assess whether the intake is within the safe limits or not. This is possible if one performs theoretical calculations and estimates the amount of uranium which builds up in the body as a function of time. Similarly theoretical estimates in case of excretion have to be made. For this purpose, a computer programme has been developed to find out organ burdens and excretion rates resulting from exposure to a radioactive nuclide. ICRP-30 lung model has been used and cases of single instantaneous inhalation of 1 ALI as well as inhalation at a steady rate of ALI/365 per day have been considered. Using this programme, results for uranium aerosols of classes D, W and Y and sizes 0.2, 1 and 5 microns are generated by ND computers in tabular as well as graphical forms. These will be useful in conjunction with body burden measurements by direct counting or excretion analysis. (author). 7 tabs., 56 figs

Domination, self-determination and circular organizing

NARCIS (Netherlands)

Romme, A.G.L.

2002-01-01

The emergence of self-organizing forms of control, based on the idea of self-determination, have challenged traditional forms of control based on the concept of domination. As such, self-determination has been put forward as an alternative rather than as a complement to domination. This paper

Consumer attitudes towards computer-assisted self-care of the common cold.

Science.gov (United States)

Reis, J; Wrestler, F

1994-04-01

Knowledge of colds and flu and attitudes towards use of computers for self-care are compared for 260 young adult users and 194 young adult non-users of computer-assisted self-care for colds and flu. Participants completed a knowledge questionnaire on colds and flu, used a computer program designed to enhance self-care for colds and flu, and then completed a questionnaire on their attitudes towards using a computer for self-care for colds and flu, and then completed a questionnaire on their attitudes towards using a computer for self-care for colds and flu, perceived importance of physician interactions, physician expertise, and patient-physician communication. Compared with users, non-users preferred personal contact with their physicians and felt that computerized health assessments would be limited in vocabulary and range of current medical information. Non-users were also more likely to agree that people could not be trusted to do an accurate computerized health assessment and that the average person was too computer illiterate to use computers for self-care.

Computing Moment-Based Probability Tables for Self-Shielding Calculations in Lattice Codes

International Nuclear Information System (INIS)

Hebert, Alain; Coste, Mireille

2002-01-01

As part of the self-shielding model used in the APOLLO2 lattice code, probability tables are required to compute self-shielded cross sections for coarse energy groups (typically with 99 or 172 groups). This paper describes the replacement of the multiband tables (typically with 51 subgroups) with moment-based tables in release 2.5 of APOLLO2. An improved Ribon method is proposed to compute moment-based probability tables, allowing important savings in CPU resources while maintaining the accuracy of the self-shielding algorithm. Finally, a validation is presented where the absorption rates obtained with each of these techniques are compared with exact values obtained using a fine-group elastic slowing-down calculation in the resolved energy domain. Other results, relative to the Rowland's benchmark and to three assembly production cases, are also presented

A strategy for tissue self-organization that is robust to cellular heterogeneity and plasticity.

Science.gov (United States)

Cerchiari, Alec E; Garbe, James C; Jee, Noel Y; Todhunter, Michael E; Broaders, Kyle E; Peehl, Donna M; Desai, Tejal A; LaBarge, Mark A; Thomson, Matthew; Gartner, Zev J

2015-02-17

Developing tissues contain motile populations of cells that can self-organize into spatially ordered tissues based on differences in their interfacial surface energies. However, it is unclear how self-organization by this mechanism remains robust when interfacial energies become heterogeneous in either time or space. The ducts and acini of the human mammary gland are prototypical heterogeneous and dynamic tissues comprising two concentrically arranged cell types. To investigate the consequences of cellular heterogeneity and plasticity on cell positioning in the mammary gland, we reconstituted its self-organization from aggregates of primary cells in vitro. We find that self-organization is dominated by the interfacial energy of the tissue-ECM boundary, rather than by differential homo- and heterotypic energies of cell-cell interaction. Surprisingly, interactions with the tissue-ECM boundary are binary, in that only one cell type interacts appreciably with the boundary. Using mathematical modeling and cell-type-specific knockdown of key regulators of cell-cell cohesion, we show that this strategy of self-organization is robust to severe perturbations affecting cell-cell contact formation. We also find that this mechanism of self-organization is conserved in the human prostate. Therefore, a binary interfacial interaction with the tissue boundary provides a flexible and generalizable strategy for forming and maintaining the structure of two-component tissues that exhibit abundant heterogeneity and plasticity. Our model also predicts that mutations affecting binary cell-ECM interactions are catastrophic and could contribute to loss of tissue architecture in diseases such as breast cancer.

10th Workshop on Self-Organizing Maps

CERN Document Server

Schleif, Frank-Michael; Kaden, Marika; Lange, Mandy

2014-01-01

The book collects the scientific contributions presented at the 10th Workshop on Self-Organizing Maps (WSOM 2014) held at the University of Applied Sciences Mittweida, Mittweida (Germany, Saxony), on July 2–4, 2014. Starting with the first WSOM-workshop 1997 in Helsinki this workshop focuses on newest results in the field of supervised and unsupervised vector quantization like self-organizing maps for data mining and data classification.   This 10th WSOM brought together more than 50 researchers, experts and practitioners in the beautiful small town Mittweida in Saxony (Germany) nearby the mountains Erzgebirge to discuss new developments in the field of unsupervised self-organizing vector quantization systems and learning vector quantization approaches for classification. The book contains the accepted papers of the workshop after a careful review process as well as summaries of the invited talks.   Among these book chapters there are excellent examples of the use of self-organizing maps in agriculture, ...

Self-Inhibiting Modules Can Self-Organize as a Brain of a Robot: A Conjecture

Directory of Open Access Journals (Sweden)

J. Negrete-Martínez

2006-01-01

Full Text Available In this article we describe a new robot control architecture on the basis of self-organization of self-inhibiting modules. The architecture can generate a complex behaviour repertoire. The repertoire can be performance-enhanced or increased by modular poly-functionality and/or by addition of new modules. This architecture is illustrated in a robot consisting of a car carrying an arm with a grasping tool. In the robot, each module drives either a joint motor or a pair of wheel motors. Every module estimates the distance from a sensor placed in the tool to a beacon. If the distance is smaller than a previously measured distance, the module drives its motor in the same direction of its prior movement. If the distance is larger, the next movement will be in the opposite direction; but, if the movement produces no significant change in distance, the module self-inhibits. A self-organization emerges: any module can be the next to take control of the motor activity of the robot once one module self-inhibits. A single module is active at a given time. The modules are implemented as computer procedures and their turn for participation scheduled by an endless program. The overall behaviour of the robot corresponds to a reaching attention behaviour. It is easily switched to a running-away attention behaviour by changing the sign of the same parameter in each module. The addition of a “sensor-gain attenuation reflex” module and of a “light-orientation reflex” module provides an increase of the behavioural attention repertoire and performance enhancement. Since scheduling a module does not necessarily produce its sustained intervention, the architecture of the “brain” is actually providing action induction rather than action selection.

Proposing an Environmental Excellence Self-Assessment Model

DEFF Research Database (Denmark)

Meulengracht Jensen, Peter; Johansen, John; Wæhrens, Brian Vejrum

2013-01-01

that the EEA model can be used in global organizations to differentiate environmental efforts depending on the maturity stage of the individual sites. Furthermore, the model can be used to support the decision-making process regarding when organizations should embark on more complex environmental efforts......This paper presents an Environmental Excellence Self-Assessment (EEA) model based on the structure of the European Foundation of Quality Management Business Excellence Framework. Four theoretical scenarios for deploying the model are presented as well as managerial implications, suggesting...

Self-Organization Activities of College Students: Challenges and Opportunities

Science.gov (United States)

Shmurygina, Natalia; Bazhenova, Natalia; Bazhenov, Ruslan; Nikolaeva, Natalia; Tcytcarev, Andrey

2016-01-01

The article provides the analysis of self-organization activities of college students related to their participation in youth associations activities. The purpose of research is to disclose a degree of students' activities demonstration based on self-organization processes, assessment of existing self-organization practices of the youth,…

Self-Organized Patterns Induced by Neimark-Sacker, Flip and Turing Bifurcations in a Discrete Predator-Prey Model with Lesie-Gower Functional Response

Directory of Open Access Journals (Sweden)

Feifan Zhang

2017-06-01

Full Text Available The formation of self-organized patterns in predator-prey models has been a very hot topic recently. The dynamics of these models, bifurcations and pattern formations are so complex that studies are urgently needed. In this research, we transformed a continuous predator-prey model with Lesie-Gower functional response into a discrete model. Fixed points and stability analyses were studied. Around the stable fixed point, bifurcation analyses including: flip, Neimark-Sacker and Turing bifurcation were done and bifurcation conditions were obtained. Based on these bifurcation conditions, parameters values were selected to carry out numerical simulations on pattern formation. The simulation results showed that Neimark-Sacker bifurcation induced spots, spirals and transitional patterns from spots to spirals. Turing bifurcation induced labyrinth patterns and spirals coupled with mosaic patterns, while flip bifurcation induced many irregular complex patterns. Compared with former studies on continuous predator-prey model with Lesie-Gower functional response, our research on the discrete model demonstrated more complex dynamics and varieties of self-organized patterns.

Optimality and self-organization in river deltas

Science.gov (United States)

Tejedor, A.; Longjas, A.; Edmonds, D. A.; Zaliapin, I. V.; Georgiou, T. T.; Rinaldo, A.; Foufoula-Georgiou, E.

2017-12-01

Deltas are nourished by channel networks, whose connectivity constrains, if not drives, the evolution, functionality and resilience of these systems. Understanding the coevolution of deltaic channels and their flux organization is crucial for guiding maintenance strategies of these highly stressed systems from a range of anthropogenic activities. However, in contrast to tributary channel networks, to date, no theory has been proposed to explain how deltas self-organize to distribute water and sediment to the delta top and the shoreline. Here, we hypothesize the existence of an optimality principle underlying the self-organized partition of fluxes in delta channel networks. Specifically, we hypothesize that deltas distribute water and sediment fluxes on a given delta topology such as to maximize the diversity of flux delivery to the shoreline. By introducing the concept of nonlocal Entropy Rate (nER) and analyzing ten field deltas in diverse environments, we present evidence that supports our hypothesis, suggesting that delta networks achieve dynamically accessible maxima of their nER. Furthermore, by analyzing six simulated deltas using the Delf3D model and following their topologic and flux re-organization before and after major avulsions, we further study the evolution of nER and confirm our hypothesis. We discuss how optimal flux distributions in terms of nER, when interpreted in terms of resilience, are configurations that reflect an increased ability to withstand perturbations.

Self-similarly evolving and minimally dissipated stable states of plasmas realized after relaxation and self-organization processes

International Nuclear Information System (INIS)

Kondoh, Yoshiomi; Hakoiwa, Toru; Okada, Akihito; Kobayashi, Naohiro; Takahashi, Toshiki

2006-01-01

A novel set of simultaneous eigenvalue equations having dissipative terms are derived to find self-similarly evolving and minimally dissipated stable states of plasmas realized after relaxation and self-organization processes. By numerically solving the set of eigenvalue equations in a cylindrical model, typical spatial profiles of plasma parameters, electric and magnetic fields and diffusion factors are presented, all of which determine self-consistently with each other by physical laws and mutual relations among them, just as in experimental plasmas. (author)

Improving Charge Injection in Organic Electronic Devices Using Self-Assembled Monolayers

Science.gov (United States)

Campbell, I. H.; Kress, J. D.; Martin, R. L.; Smith, D. L.; Barashkov, N. N.; Ferraris, J. P.

1997-03-01

Organic electronic devices consist of one or more insulating organic layers contacted by metallic conductors. The Schottky energy barrier between the metal and the organic material is determined by the work function of the metal contact as described in the ideal Schottky model. The magnitude of the metal/organic Schottky energy barrier controls charge injection from the metal into the organic layer. Previously, polar alkane-thiol based self-assembled monolayers (SAMs) were used to change the Schottky energy barrier between the metal and an organic film by more than 1 eV. In these SAMs, the large energy gap of the alkane molecules blocks charge injection into the organic layer despite the decrease of the Schottky energy barrier. Here, we demonstrate improved charge injection into the organic material by using conjugated self-assembled monolayers. The conjugated SAMs have modest energy gaps which allow improved charge injection into the organic layer. We present measurements of current-voltage characteristics and metal/organic Schottky energy barriers for device structures both with and without conjugated SAMs.

Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models.

Science.gov (United States)

Mahony, Shaun; McInerney, James O; Smith, Terry J; Golden, Aaron

2004-03-05

Many current gene prediction methods use only one model to represent protein-coding regions in a genome, and so are less likely to predict the location of genes that have an atypical sequence composition. It is likely that future improvements in gene finding will involve the development of methods that can adequately deal with intra-genomic compositional variation. This work explores a new approach to gene-prediction, based on the Self-Organizing Map, which has the ability to automatically identify multiple gene models within a genome. The current implementation, named RescueNet, uses relative synonymous codon usage as the indicator of protein-coding potential. While its raw accuracy rate can be less than other methods, RescueNet consistently identifies some genes that other methods do not, and should therefore be of interest to gene-prediction software developers and genome annotation teams alike. RescueNet is recommended for use in conjunction with, or as a complement to, other gene prediction methods.

Validity of two methods to assess computer use: Self-report by questionnaire and computer use software

NARCIS (Netherlands)

Douwes, M.; Kraker, H.de; Blatter, B.M.

2007-01-01

A long duration of computer use is known to be positively associated with Work Related Upper Extremity Disorders (WRUED). Self-report by questionnaire is commonly used to assess a worker's duration of computer use. The aim of the present study was to assess the validity of self-report and computer

Factors Influencing Organization Adoption Decision On Cloud Computing

OpenAIRE

Ailar Rahimli

2013-01-01

Cloud computing is a developing field, using by organization that require to computing resource to provide the organizational computing needs. The goal of this research is evaluate the factors that influence on organization decision to adopt the cloud computing in Malaysia. Factors that relate to cloud computing adoption that include : need for cloud computing, cost effectiveness, security effectiveness of cloud computing and reliability. This paper evaluated the factors that influence on ado...

Attitudes towards Computer and Computer Self-Efficacy as Predictors of Preservice Mathematics Teachers' Computer Anxiety

Science.gov (United States)

Awofala, Adeneye O. A.; Akinoso, Sabainah O.; Fatade, Alfred O.

2017-01-01

The study investigated attitudes towards computer and computer self-efficacy as predictors of computer anxiety among 310 preservice mathematics teachers from five higher institutions of learning in Lagos and Ogun States of Nigeria using the quantitative research method within the blueprint of the descriptive survey design. Data collected were…

Self-Organized Construction with Continuous Building Material

DEFF Research Database (Denmark)

Heinrich, Mary Katherine; Wahby, Mostafa; Divband Soorati, Mohammad

2016-01-01

Self-organized construction with continuous, structured building material, as opposed to modular units, offers new challenges to the robot-based construction process and lends the opportunity for increased flexibility in constructed artifact properties, such as shape and deformation. As an example...... investigation, we look at continuous filaments organized into braided structures, within the context of bio-hybrids constructing architectural artifacts. We report the result of an early swarm robot experiment. The robots successfully constructed a braid in a self-organized process. The construction process can...... be extended by using different materials and by embedding sensors during the self-organized construction directly into the braided structure. In future work, we plan to apply dedicated braiding robot hardware and to construct sophisticated 3-d structures with local variability in patterns of filament...

Role of cell division and self-propulsion in self-organization of 2D cell co-cultures

Science.gov (United States)

Das, Moumita; Dey, Supravat; Wu, Mingming; Ma, Minglin

Self-organization of cells is a key process in developmental and cancer biology. The differential adhesion hypothesis (DAH), which assumes cells as equilibrium liquid droplets and relates the self-assembly of cells to differences in inter-cellular adhesiveness, has been very successful in explaining cellular organization during morphogenesis where neighboring cells have the same non-equilibrium properties (motility, proliferation rate). However, recently it has been experimentally shown that for a co-culture of two different cell types proliferating at different rates, the resulting spatial morphologies cannot be explained using the DAH alone. Motivated by this, we develop and study a two-dimensional model of a cell co-culture that includes cell division and self-propulsion in addition to cell-cell adhesion, and systemically study how cells with significantly different adhesion, motility, and proliferation rate dynamically organize themselves in a spatiotemporal and context-dependent manner. Our results may help to understand how differential equilibrium and non-equilibrium properties cooperate and compete leading to different morphologies during tumor development, with important consequences for invasion and metastasis

INREM II: a computer implementation of recent models for estimating the dose equivalent to organs of man from an inhaled or ingested radionuclide

International Nuclear Information System (INIS)

Killough, G.G.; Dunning, D.E. Jr.; Pleasant, J.C.

1978-01-01

This report describes a computer code, INREM II, which calculates the internal radiation dose equivalent to organs of man which results from the intake of a radionuclide by inhalation or ingestion. Deposition and removal of radioactivity from the respiratory tract is represented by the ICRP Task Group Lung Model. A four-segment catenary model of the GI tract is used to estimate movement of radioactive material that is ingested or swallowed after being cleared from the respiratory tract. Retention of radioactivity in other organs is specified by linear combinations of decaying exponential functions. The formation and decay of radioactive daughters is treated explicitly, with each radionuclide species in the chain having its own uptake and retention parameters, as supplied by the user. The dose equivalent to a target organ is computed as the sum of contributions from each source organ in which radioactivity is assumed to be situated. This calculation utilizes a matrix of S-factors (rem/μCi-day) supplied by the user for the particular choice of source and target organs. Output permits the evaluation of crossfire components of dose when penetrating radiations are present. INREM II is coded in FORTRAN IV and has been compiled and executed on an IBM-360 computer

Simulating land-use changes by incorporating spatial autocorrelation and self-organization in CLUE-S modeling: a case study in Zengcheng District, Guangzhou, China

Science.gov (United States)

Mei, Zhixiong; Wu, Hao; Li, Shiyun

2018-06-01

The Conversion of Land Use and its Effects at Small regional extent (CLUE-S), which is a widely used model for land-use simulation, utilizes logistic regression to estimate the relationships between land use and its drivers, and thus, predict land-use change probabilities. However, logistic regression disregards possible spatial autocorrelation and self-organization in land-use data. Autologistic regression can depict spatial autocorrelation but cannot address self-organization, while logistic regression by considering only self-organization (NElogistic regression) fails to capture spatial autocorrelation. Therefore, this study developed a regression (NE-autologistic regression) method, which incorporated both spatial autocorrelation and self-organization, to improve CLUE-S. The Zengcheng District of Guangzhou, China was selected as the study area. The land-use data of 2001, 2005, and 2009, as well as 10 typical driving factors, were used to validate the proposed regression method and the improved CLUE-S model. Then, three future land-use scenarios in 2020: the natural growth scenario, ecological protection scenario, and economic development scenario, were simulated using the improved model. Validation results showed that NE-autologistic regression performed better than logistic regression, autologistic regression, and NE-logistic regression in predicting land-use change probabilities. The spatial allocation accuracy and kappa values of NE-autologistic-CLUE-S were higher than those of logistic-CLUE-S, autologistic-CLUE-S, and NE-logistic-CLUE-S for the simulations of two periods, 2001-2009 and 2005-2009, which proved that the improved CLUE-S model achieved the best simulation and was thereby effective to a certain extent. The scenario simulation results indicated that under all three scenarios, traffic land and residential/industrial land would increase, whereas arable land and unused land would decrease during 2009-2020. Apparent differences also existed in the

Predicting spiral wave patterns from cell properties in a model of biological self-organization.

Science.gov (United States)

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Computational 17O-NMR spectroscopy of organic acids and peracids: comparison of solvation models

International Nuclear Information System (INIS)

Baggioli, Alberto; Castiglione, Franca; Raos, Guido; Crescenzi, Orlando; Field, Martin J.

2013-01-01

We examine several computational strategies for the prediction of the 17 O-NMR shielding constants for a selection of organic acids and peracids in aqueous solution. In particular, we consider water (the solvent and reference for the chemical shifts), hydrogen peroxide, acetic acid, lactic acid and peracetic acid. First of all, we demonstrate that the PBE0 density functional in combination with the 6-311+G(d,p) basis set provides an excellent compromise between computational cost and accuracy in the calculation of the shielding constants. Next, we move on to the problem of the solvent representation. Our results confirm the shortcomings of the Polarizable Continuum Model (PCM) in the description of systems susceptible to strong hydrogen bonding interactions, while at the same time they demonstrate its usefulness within a molecular-continuum approach, whereby PCM is applied to describe the solvation of the solute surrounded by some explicit solvent molecules. We examine different models of the solvation shells, sampling their configurations using both energy minimizations of finite clusters and molecular dynamics simulations of bulk systems. Hybrid molecular dynamics simulations, in which the solute is described at the PM6 semiempirical level and the solvent by the TIP3P model, prove to be a promising sampling method for medium-to-large sized systems. The roles of solvent shell size and structure are also briefly discussed. (authors)

A distance weighted-based approach for self-organized aggregation in robot swarms

KAUST Repository

Khaldi, Belkacem

2017-12-14

In this paper, a Distance-Weighted K Nearest Neighboring (DW-KNN) topology is proposed to study self-organized aggregation as an emergent swarming behavior within robot swarms. A virtual physics approach is applied among the proposed neighborhood topology to keep the robots together. A distance-weighted function based on a Smoothed Particle Hydrodynamic (SPH) interpolation approach is used as a key factor to identify the K-Nearest neighbors taken into account when aggregating the robots. The intra virtual physical connectivity among these neighbors is achieved using a virtual viscoelastic-based proximity model. With the ARGoS based-simulator, we model and evaluate the proposed approach showing various self-organized aggregations performed by a swarm of N foot-bot robots.

Transformation-invariant visual representations in self-organizing spiking neural networks.

Science.gov (United States)

Evans, Benjamin D; Stringer, Simon M

2012-01-01

The ventral visual pathway achieves object and face recognition by building transformation-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transformation-invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT) learning. However, it has not previously been investigated how transformation-invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP) where the change in synaptic strength is dependent on the relative times of the spikes emitted by the presynaptic and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF) neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model parameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Transform-invariant visual representations in self-organizing spiking neural networks

Directory of Open Access Journals (Sweden)

Benjamin eEvans

2012-07-01

Full Text Available The ventral visual pathway achieves object and face recognition by building transform-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transform invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT learning. However, it has not previously been investigated how transform invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP where the change in synaptic strength is dependent on the relative times of the spikes emitted by the pre- and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model pa- rameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Computer self efficacy as correlate of on-line public access ...

African Journals Online (AJOL)

The use of Online Public Access Catalogue (OPAC) by students has a lot of advantages and computer self-efficacy is a factor that could determine its effective utilization. Little appears to be known about colleges of education students‟ use of OPAC, computer self-efficacy and the relationship between OPAC and computer ...

Quantum self-organization and nuclear collectivities

Science.gov (United States)

Otsuka, T.; Tsunoda, Y.; Togashi, T.; Shimizu, N.; Abe, T.

2018-02-01

The quantum self-organization is introduced as one of the major underlying mechanisms of the quantum many-body systems. In the case of atomic nuclei as an example, two types of the motion of nucleons, single-particle states and collective modes, dominate the structure of the nucleus. The outcome of the collective mode is determined basically by the balance between the effect of the mode-driving force (e.g., quadrupole force for the ellipsoidal deformation) and the resistance power against it. The single-particle energies are one of the sources to produce such resistance power: a coherent collective motion is more hindered by larger gaps between relevant single particle states. Thus, the single-particle state and the collective mode are “enemies” each other. However, the nuclear forces are demonstrated to be rich enough so as to enhance relevant collective mode by reducing the resistance power by changing singleparticle energies for each eigenstate through monopole interactions. This will be verified with the concrete example taken from Zr isotopes. Thus, when the quantum self-organization occurs, single-particle energies can be self-organized, being enhanced by (i) two quantum liquids, e.g., protons and neutrons, (ii) two major force components, e.g., quadrupole interaction (to drive collective mode) and monopole interaction (to control resistance). In other words, atomic nuclei are not necessarily like simple rigid vases containing almost free nucleons, in contrast to the naïve Fermi liquid picture. Type II shell evolution is considered to be a simple visible case involving excitations across a (sub)magic gap. The quantum self-organization becomes more important in heavier nuclei where the number of active orbits and the number of active nucleons are larger. The quantum self-organization is a general phenomenon, and is expected to be found in other quantum systems.

On the nature and shape of tubulin trails: implications on microtubule self-organization.

Science.gov (United States)

Glade, Nicolas

2012-06-01

Microtubules, major elements of the cell skeleton are, most of the time, well organized in vivo, but they can also show self-organizing behaviors in time and/or space in purified solutions in vitro. Theoretical studies and models based on the concepts of collective dynamics in complex systems, reaction-diffusion processes and emergent phenomena were proposed to explain some of these behaviors. In the particular case of microtubule spatial self-organization, it has been advanced that microtubules could behave like ants, self-organizing by 'talking to each other' by way of hypothetic (because never observed) concentrated chemical trails of tubulin that are expected to be released by their disassembling ends. Deterministic models based on this idea yielded indeed like-looking spatio-temporal self-organizing behaviors. Nevertheless the question remains of whether microscopic tubulin trails produced by individual or bundles of several microtubules are intense enough to allow microtubule self-organization at a macroscopic level. In the present work, by simulating the diffusion of tubulin in microtubule solutions at the microscopic scale, we measure the shape and intensity of tubulin trails and discuss about the assumption of microtubule self-organization due to the production of chemical trails by disassembling microtubules. We show that the tubulin trails produced by individual microtubules or small microtubule arrays are very weak and not elongated even at very high reactive rates. Although the variations of concentration due to such trails are not significant compared to natural fluctuations of the concentration of tubuline in the chemical environment, the study shows that heterogeneities of biochemical composition can form due to microtubule disassembly. They could become significant when produced by numerous microtubule ends located in the same place. Their possible formation could play a role in certain conditions of reaction. In particular, it gives a mesoscopic

Relativistic fluid theories - Self organization

International Nuclear Information System (INIS)

Mahajan, S.M.; Hazeltine, R.D.; Yoshida, Z.

2003-01-01

Developments in two distinct but related subjects are reviewed: 1) Formulation and investigation of closed fluid theories which transcend the limitations of standard magnetohydrodynamics (MHD), in particular, theories which are valid in the long mean free path limit and in which pressure anisotropy, heat flow, and arbitrarily strong sheared flows are treated consistently, and 2) Exploitation of the two-fluid theories to derive new plasma configurations in which the flow-field is a co-determinant of the overall dynamics; some of these states belong to the category of self-organized relaxed states. Physical processes which may provide a route to self-organization and complexity are also explored. (author)

Computations Underlying Social Hierarchy Learning: Distinct Neural Mechanisms for Updating and Representing Self-Relevant Information.

Science.gov (United States)

Kumaran, Dharshan; Banino, Andrea; Blundell, Charles; Hassabis, Demis; Dayan, Peter

2016-12-07

Knowledge about social hierarchies organizes human behavior, yet we understand little about the underlying computations. Here we show that a Bayesian inference scheme, which tracks the power of individuals, better captures behavioral and neural data compared with a reinforcement learning model inspired by rating systems used in games such as chess. We provide evidence that the medial prefrontal cortex (MPFC) selectively mediates the updating of knowledge about one's own hierarchy, as opposed to that of another individual, a process that underpinned successful performance and involved functional interactions with the amygdala and hippocampus. In contrast, we observed domain-general coding of rank in the amygdala and hippocampus, even when the task did not require it. Our findings reveal the computations underlying a core aspect of social cognition and provide new evidence that self-relevant information may indeed be afforded a unique representational status in the brain. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Delocalized organic pollutant destruction through a self-sustaining supercritical water oxidation process

International Nuclear Information System (INIS)

Lavric, E.D.; Weyten, H.; Ruyck, J. de; Plesu, V.; Lavric, V.

2005-01-01

Supercritical water oxidation (SCWO) is a recent development aiming at the destruction of organic pollutants present with low concentrations in waste waters. The present paper focuses on the process simulation of SCWO with emphasis on the proper modelling of supercritical thermodynamic conditions and on the possibility to make the SCWO process self-sufficient from the energetic viewpoint. Self-sufficiency may be of interest to encourage more delocalization of waste water treatment. The process of SCWO for dilute waste water (no more than 5 wt.%) is modelled through the ASPEN Plus copyright process simulator. Studies were made to search for energetic self-sufficiency conditions using various technologies for power production from the heat of reaction, like supercritical water expansion in a turbine, use of a closed Brayton cycle (CBC) and use of an organic Rankine cycle (ORC). The results obtained showed that the process is energetically self-sufficient using either a small supercritical turbine, or an ORC. In less restrictive conditions regarding the component efficiencies, the CBC, in theory, also leads to self-sufficiency, but from the analysis, it appears that this solution is less realistic

Self-organization processes and nanocluster formation in crystal lattices by low-energy ion irradiation

International Nuclear Information System (INIS)

Tereshko, I.; Abidzina, V.; Tereshko, A.; Glushchenko, V.; Elkin, I.

2007-01-01

The goal of this paper is to study self-organization processes that cause nanostructural evolution in nonlinear crystal media. The subjects of the investigation were nonlinear homogeneous and heterogeneous atom chains. The method of computer simulation was used to investigate the interaction between low-energy ions and crystal lattices. It was based on the conception of three-dimensional lattice as a nonlinear atom chain system. We showed that that in homogeneous atom chains critical energy needed for self-organization processes development is less than for nonlinear atom chain with already embedded clusters. The possibility of nanostructure formation was studied by a molecular dynamics method of nonlinear oscillations in atomic oscillator systems of crystal lattices after their low-energy ion irradiation. (authors)

Optical electronics self-organized integration and applications

CERN Document Server

Yoshimura, Tetsuzo

2012-01-01

IntroductionFrom Electronics to Optical ElectronicsAnalysis Tools for Optical CircuitsSelf-Organized Optical Waveguides: Theoretical AnalysisSelf-Organized Optical Waveguides: Experimental DemonstrationsOptical Waveguide Films with Vertical Mirrors 3-D Optical Circuits with Stacked Waveguide Films Heterogeneous Thin-Film Device IntegrationOptical Switches OE Hardware Built by Optical ElectronicsIntegrated Solar Energy Conversion SystemsFuture Challenges.

Weighted Evolving Networks with Self-organized Communities

International Nuclear Information System (INIS)

Xie Zhou; Wang Xiaofan; Li Xiang

2008-01-01

In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned in different levels according to community sizes and node strengths, respectively. Theoretical analyses and numerical simulations show that our model captures power-law distributions of community sizes, node strengths, and link weights, with tunable exponents of ν ≥ 1, γ > 2, and α > 2, respectively, sharing large clustering coefficients and scaling clustering spectra, and covering the range from disassortative networks to assortative networks. Finally, we apply our new model to the scientific co-authorship networks with both their weighted and unweighted datasets to verify its effectiveness

Models of parallel computation :a survey and classification

Institute of Scientific and Technical Information of China (English)

ZHANG Yunquan; CHEN Guoliang; SUN Guangzhong; MIAO Qiankun

2007-01-01

In this paper,the state-of-the-art parallel computational model research is reviewed.We will introduce various models that were developed during the past decades.According to their targeting architecture features,especially memory organization,we classify these parallel computational models into three generations.These models and their characteristics are discussed based on three generations classification.We believe that with the ever increasing speed gap between the CPU and memory systems,incorporating non-uniform memory hierarchy into computational models will become unavoidable.With the emergence of multi-core CPUs,the parallelism hierarchy of current computing platforms becomes more and more complicated.Describing this complicated parallelism hierarchy in future computational models becomes more and more important.A semi-automatic toolkit that can extract model parameters and their values on real computers can reduce the model analysis complexity,thus allowing more complicated models with more parameters to be adopted.Hierarchical memory and hierarchical parallelism will be two very important features that should be considered in future model design and research.

Self-organized criticality revisited: non-local transport by turbulent amplification

DEFF Research Database (Denmark)

Milovanov, Alexander V.; Rasmussen, Jens Juul

2015-01-01

We revise the applications of self-organized criticality (SOC) as a paradigmatic model for tokamak plasma turbulence. The work, presented here, is built around the idea that some systems do not develop a pure critical state associable with SOC, since their dynamical evolution involves as a compet......We revise the applications of self-organized criticality (SOC) as a paradigmatic model for tokamak plasma turbulence. The work, presented here, is built around the idea that some systems do not develop a pure critical state associable with SOC, since their dynamical evolution involves...... as a competing key factor an inverse cascade of the energy in reciprocal space. Then relaxation of slowly increasing stresses will give rise to intermittent bursts of transport in real space and outstanding transport events beyond the range of applicability of the 'conventional' SOC. Also, we are concerned...... with the causes and origins of non-local transport in magnetized plasma, and show that this type of transport occurs naturally in self-consistent strong turbulence via a complexity coupling to the inverse cascade. We expect these coupling phenomena to occur in the parameter range of strong nonlinearity and time...

Workplace Spirituality, Computer Self-Efficacy And Emotional ...

African Journals Online (AJOL)

There should therefore, be an ongoing facilitation of self-development for lecturers through opportunities for computer skills acquisition, role identification and role performance to manage emotional labour and the cold fact that spirituality is a key player in human functioning. Keywords: Workplace Spirituality, Computer ...

Autonomous Dynamically Self-Organizing and Self-Healing Distributed Hardware Architecture - the eDNA Concept

Science.gov (United States)

Boesen, Michael Reibel; Madsen, Jan; Keymeulen, Didier

2011-01-01

This paper presents the current state of the autonomous dynamically self-organizing and self-healing electronic DNA (eDNA) hardware architecture (patent pending). In its current prototype state, the eDNA architecture is capable of responding to multiple injected faults by autonomously reconfiguring itself to accommodate the fault and keep the application running. This paper will also disclose advanced features currently available in the simulation model only. These features are future work and will soon be implemented in hardware. Finally we will describe step-by-step how an application is implemented on the eDNA architecture.

An EGS4-ready tomographic computational model of a 14-year-old female torso for calculating organ doses from CT examinations

International Nuclear Information System (INIS)

Caon, M.; School of Physics and Electronic Systems Engineering, University of South Australia, The Levels Campus, Mawson Lakes, South Australia, 5095; Pattison, J.

1999-01-01

Fifty-four consecutive CT scans have been used to construct a tomographic computational model of a 14-year-old female torso suitable for the determination of organ doses from CT. The model, known as ADELAIDE, is in the form of an input file compatible with user codes based on XYZDOS.MOR from the readily available EGS4 Monte Carlo radiation transport code. ADELAIDE's dimensions are close to the Australian averages for her age so the model is representative of a 14-year-old girl. The realistic anatomy in the model differs considerably from that in Cristy's 15-year-old mathematical computational model by having realistically shaped organs that are appropriately located within a real external contour. Average absorbed dose to organs from simulated CT examinations of the chest and abdomen have been calculated for ADELAIDE using EGS4 within a geometry specific to the General Electric Hi-Speed Advantage CT scanner and using an x-ray spectrum calculated using data from the scanner's x-ray tube. The simulations include the scanner's beam shaping filter and patient table. It is suggested that the resulting values have fewer possible sources of uncertainty than organ doses derived from dose coefficients calculated for a MIRD style model with mathematical anatomy and a spectrum that may not match that of the scanner. The organ doses were normalized using the scanner's CTDI measured free-in-air and an EGS4 simulation of the CTDI measurement. Effective dose to the torso from 26-slice chest and 24-slice abdomen examinations (at 120 kV, 200 mAs, 7 mm slices) is 4.6±0.1mSv and 4.3±0.1mSv respectively. (author)

Classification of perovskites with supervised self-organizing maps

International Nuclear Information System (INIS)

Kuzmanovski, Igor; Dimitrovska-Lazova, Sandra; Aleksovska, Slobotka

2007-01-01

In this work supervised self-organizing maps were used for structural classification of perovskites. For this purpose, structural data for total number of 286 perovskites, belonging to ABO 3 and/or A 2 BB'O 6 types, were collected from literature: 130 of these are cubic, 85 orthorhombic and 71 monoclinic. For classification purposes, the effective ionic radii of the cations, electronegativities of the cations in B-position, as well as, the oxidation states of these cations, were used as input variables. The parameters of the developed models, as well as, the most suitable variables for classification purposes were selected using genetic algorithms. Two-third of all the compounds were used in the training phase. During the optimization process the performances of the models were checked using cross-validation leave-1/10-out. The performances of obtained solutions were checked using the test set composed of the remaining one-third of the compounds. The obtained models for classification of these three classes of perovskite compounds show very good results. Namely, the classification of the compounds in the test set resulted in small number of discrepancies (4.2-6.4%) between the actual crystallographic class and the one predicted by the models. All these results are strong arguments for the validity of supervised self-organizing maps for performing such types of classification. Therefore, the proposed procedure could be successfully used for crystallographic classification of perovskites in one of these three classes

The role of hierarchy in self-organizing systems

NARCIS (Netherlands)

Ollfen, van W.; Romme, A.G.L.

1995-01-01

This paper discusses the role of hierarchy in human systems. Two kinds of self-organizing processes are distinguished: conservative and dissipative self-organization. The former leads to rather stable, specialistic systems, whereas the latter leads to continuously changing generalistic systems. When

Formation of Virtual Organizations in Grids: A Game-Theoretic Approach

Science.gov (United States)

Carroll, Thomas E.; Grosu, Daniel

The execution of large scale grid applications requires the use of several computational resources owned by various Grid Service Providers (GSPs). GSPs must form Virtual Organizations (VOs) to be able to provide the composite resource to these applications. We consider grids as self-organizing systems composed of autonomous, self-interested GSPs that will organize themselves into VOs with every GSP having the objective of maximizing its profit. We formulate the resource composition among GSPs as a coalition formation problem and propose a game-theoretic framework based on cooperation structures to model it. Using this framework, we design a resource management system that supports the VO formation among GSPs in a grid computing system.

Examining the Computer Self-Efficacy Perceptions of Gifted Students

Science.gov (United States)

Kaplan, Abdullah; Öztürk, Mesut; Doruk, Muhammet; Yilmaz, Alper

2013-01-01

This study was conducted in order to determine the computer self-efficacy perceptions of gifted students. The research group of this study is composed of gifted students (N = 36) who were studying at the Science and Arts Center in Gümüshane province in the spring semester of the 2012-2013 academic year. The "Computer Self-Efficacy Perception…

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

Science.gov (United States)

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

Science.gov (United States)

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

High-resolution Self-Organizing Maps for advanced visualization and dimension reduction.

Science.gov (United States)

Saraswati, Ayu; Nguyen, Van Tuc; Hagenbuchner, Markus; Tsoi, Ah Chung

2018-05-04

Kohonen's Self Organizing feature Map (SOM) provides an effective way to project high dimensional input features onto a low dimensional display space while preserving the topological relationships among the input features. Recent advances in algorithms that take advantages of modern computing hardware introduced the concept of high resolution SOMs (HRSOMs). This paper investigates the capabilities and applicability of the HRSOM as a visualization tool for cluster analysis and its suitabilities to serve as a pre-processor in ensemble learning models. The evaluation is conducted on a number of established benchmarks and real-world learning problems, namely, the policeman benchmark, two web spam detection problems, a network intrusion detection problem, and a malware detection problem. It is found that the visualization resulted from an HRSOM provides new insights concerning these learning problems. It is furthermore shown empirically that broad benefits from the use of HRSOMs in both clustering and classification problems can be expected. Copyright © 2018 Elsevier Ltd. All rights reserved.

Structures in plasmas and their self-organizations

International Nuclear Information System (INIS)

Yoshida, Zensho

1989-01-01

This paper is a concise review of the physics of structures. The progress of the structure theory was motivated by the appearances of many different ordered structures that are self-organized through spontaneous dynamics. For typical examples in plasma physics, cited are the MHD equilibria (Taylor relaxed state), the ion acoustic solitons, and the van Kampen modes of continuous-spectrum Langmuir waves. A static theory for the intrinsic structures is developed to clarify the basic difference between the classical orders and the self-organized structures. In linear models, an intrinsic structure is characterized by a singular spectrum of a certain eigenvalue problem. The Taylor relaxed state is characterized by the continuum of the point spectra of the rotational operator. The general MHD equilibrium is related to a nonlinear eigenvalue problem. The soliton is a nonlinear eigenfunction of the Helmholtz-type Bohm equation. The variational expression of an intrinsic structure is characterized by restrictive functionals, which in a dynamical theory, is related to selective conservations. The Taylor relaxed state is obtained by minimizing the magnetic-field energy with conserving the magnetic helicity. This selective dissipation occurs in the fluctuations of kink modes. The soliton is self-organized by the dissipation of the Hamiltonian with keeping the energy approximately constant. The principle of the selective dissipation is logically a generalization of the ergodic hypothesis for the classical order and could be proved in a rigorous way by analyzing the attractor of the dynamical systems, just as the proof the ergodic theorem is obtained by the time-asymptotic analysis of a class of semigroups. (J.P.N.) 85 refs

Self-Organized Criticality and $1/f$ Noise in Traffic

OpenAIRE

Paczuski, Maya; Nagel, Kai

1996-01-01

Phantom traffic jams may emerge ``out of nowhere'' from small fluctuations rather than being triggered by large, exceptional events. We show how phantom jams arise in a model of single lane highway traffic, which mimics human driving behavior. Surprisingly, the optimal state of highest efficiency, with the largest throughput, is a critical state with traffic jams of all sizes. We demonstrate that open systems self-organize to the most efficient state. In the model we study, this critical stat...

Cardiac Electromechanical Models: From Cell to Organ

Directory of Open Access Journals (Sweden)

Natalia A Trayanova

2011-08-01

Full Text Available The heart is a multiphysics and multiscale system that has driven the development of the most sophisticated mathematical models at the frontiers of computation physiology and medicine. This review focuses on electromechanical (EM models of the heart from the molecular level of myofilaments to anatomical models of the organ. Because of the coupling in terms of function and emergent behaviors at each level of biological hierarchy, separation of behaviors at a given scale is difficult. Here, a separation is drawn at the cell level so that the first half addresses subcellular/single cell models and the second half addresses organ models. At the subcelluar level, myofilament models represent actin-myosin interaction and Ca-based activation. Myofilament models and their refinements represent an overview of the development in the field. The discussion of specific models emphasizes the roles of cooperative mechanisms and sarcomere length dependence of contraction force, considered the cellular basis of the Frank-Starling law. A model of electrophysiology and Ca handling can be coupled to a myofilament model to produce an EM cell model, and representative examples are summarized to provide an overview of the progression of field. The second half of the review covers organ-level models that require solution of the electrical component as a reaction-diffusion system and the mechanical component, in which active tension generated by the myocytes produces deformation of the organ as described by the equations of continuum mechanics. As outlined in the review, different organ-level models have chosen to use different ionic and myofilament models depending on the specific application; this choice has been largely dictated by compromises between model complexity and computational tractability. The review also addresses application areas of EM models such as cardiac resynchronization therapy and the role of mechano-electric coupling in arrhythmias and

Computational modeling of Metal-Organic Frameworks

Science.gov (United States)

Sung, Jeffrey Chuen-Fai

In this work, the metal-organic frameworks MIL-53(Cr), DMOF-2,3-NH 2Cl, DMOF-2,5-NH2Cl, and HKUST-1 were modeled using molecular mechanics and electronic structure. The effect of electronic polarization on the adsorption of water in MIL-53(Cr) was studied using molecular dynamics simulations of water-loaded MIL-53 systems with both polarizable and non-polarizable force fields. Molecular dynamics simulations of the full systems and DFT calculations on representative framework clusters were utilized to study the difference in nitrogen adsorption between DMOF-2,3-NH2Cl and DMOF-2,5-NH 2Cl. Finally, the control of proton conduction in HKUST-1 by complexation of molecules to the Cu open metal site was investigated using the MS-EVB methodology.

Self-organizing weights for Internet AS-graphs and surprisingly simple routing metrics

DEFF Research Database (Denmark)

Scholz, Jan Carsten; Greiner, Martin

2011-01-01

The transport capacity of Internet-like communication networks and hence their efficiency may be improved by a factor of 5–10 through the use of highly optimized routing metrics, as demonstrated previously. The numerical determination of such routing metrics can be computationally demanding...... to an extent that prohibits both investigation of and application to very large networks. In an attempt to find a numerically less expensive way of constructing a metric with a comparable performance increase, we propose a local, self-organizing iteration scheme and find two surprisingly simple and efficient...... metrics. The new metrics have negligible computational cost and result in an approximately 5-fold performance increase, providing distinguished competitiveness with the computationally costly counterparts. They are applicable to very large networks and easy to implement in today's Internet routing...

Singularity spectrum of self-organized criticality

International Nuclear Information System (INIS)

Canessa, E.

1992-10-01

I introduce a simple continuous probability theory based on the Ginzburg-Landau equation that provides for the first time a common analytical basis to relate and describe the main features of two seemingly different phenomena of condensed-matter physics, namely self-organized criticality and multifractality. Numerical support is given by a comparison with reported simulation data. Within the theory the origin of self-organized critical phenomena is analysed in terms of a nonlinear singularity spectrum different form the typical convex shape due to multifractal measures. (author). 29 refs, 5 figs

Self-organized perturbations enhance class IV behavior and 1/f power spectrum in elementary cellular automata.

Science.gov (United States)

Nakajima, Kohei; Haruna, Taichi

2011-09-01

In this paper, we propose a new class of cellular automata based on the modification of its state space. It is introduced to model a computation which is exposed to an environment. We formalized the computation as extension and projection processes of its state space and resulting misidentifications of the state. This is motivated to embed the role of an environment into the system itself, which naturally induces self-organized internal perturbations rather than the usual external perturbations. Implementing this structure into the elementary cellular automata, we characterized its effect by means of input entropy and power spectral analysis. As a result, the cellular automata with this structure showed robust class IV behavior and a 1/f power spectrum in a wide range of rule space comparative to the notion of the edge of chaos. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

The dynamics of marginality and self-organized criticality as a paradigm for turbulent transport

International Nuclear Information System (INIS)

Newman, D.E.; Carreras, B.A.; Diamond, P.H.; Hahm, T.S.

1995-01-01

A general paradigm, based on the concept of self-organized criticality (SOC), for turbulent transport in magnetically confined plasmas has been recently suggested as an explanation for some of the apparent discrepancies between most theoretical models of turbulent transport and experimental observations of the transport in magnetically confined plasmas. This model describes the dynamics of the transport without relying on the underlying local fluctuation mechanisms. Computations based on a cellular automata realization of such a model have found that noise driven SOC systems can maintain average profiles that are linearly stable (submarginal) and yet are able to sustain active transport dynamics. It is also found that the dominant scales in the transport dynamics in the absence of sheared flow are system scales rather than the underlying local fluctuation scales. The addition of sheared flow into the dynamics leads to a large reduction of the system-scale transport events and a commensurate increase in the fluctuation-scale transport events needed to maintain the constant flux. The dynamics of these models and the potential ramifications for transport studies are discussed

Disciplines, models, and computers: the path to computational quantum chemistry.

Science.gov (United States)

Lenhard, Johannes

2014-12-01

Many disciplines and scientific fields have undergone a computational turn in the past several decades. This paper analyzes this sort of turn by investigating the case of computational quantum chemistry. The main claim is that the transformation from quantum to computational quantum chemistry involved changes in three dimensions. First, on the side of instrumentation, small computers and a networked infrastructure took over the lead from centralized mainframe architecture. Second, a new conception of computational modeling became feasible and assumed a crucial role. And third, the field of computa- tional quantum chemistry became organized in a market-like fashion and this market is much bigger than the number of quantum theory experts. These claims will be substantiated by an investigation of the so-called density functional theory (DFT), the arguably pivotal theory in the turn to computational quantum chemistry around 1990.

Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

Directory of Open Access Journals (Sweden)

Sheng-Jun Wang

2011-06-01

Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

The Relationship between Sources of Self-Efficacy in Classroom Environments and the Strength of Computer Self-Efficacy Beliefs

Science.gov (United States)

Srisupawong, Yuwarat; Koul, Ravinder; Neanchaleay, Jariya; Murphy, Elizabeth; Francois, Emmanuel Jean

2018-01-01

Motivation and success in computer-science courses are influenced by the strength of students' self-efficacy (SE) beliefs in their learning abilities. Students with weak SE may struggle to be successful in a computer-science course. This study investigated the factors that enhance or impede the computer self-efficacy (CSE) of computer-science…

Information Driven Ecohydrologic Self-Organization

Directory of Open Access Journals (Sweden)

Benjamin L. Ruddell

2010-09-01

Full Text Available Variability plays an important role in the self-organized interaction between vegetation and its environment, yet the principles that characterize the role of the variability in these interactions remain elusive. To address this problem, we study the dependence between a number of variables measured at flux towers by quantifying the information flow between the different variables along with the associated time lag. By examining this network of feedback loops for seven ecosystems in different climate regions, we find that: (1 the feedback tends to maximize information production in the entire system, and the latter increases with increasing variability within the whole system; and (2 variables that participate in feedback exhibit moderated variability. Self-organization arises as a tradeoff where the ability of the total system to maximize information production through feedback is limited by moderate variability of the participating variables. This relationship between variability and information production leads to the emergence of ordered organization.

Formation of self-organized anode patterns in arc discharge simulations

International Nuclear Information System (INIS)

Trelles, Juan Pablo

2013-01-01

Pattern formation and self-organization are phenomena commonly observed experimentally in diverse types of plasma systems, including atmospheric-pressure electric arc discharges. However, numerical simulations reproducing anode pattern formation in arc discharges have proven exceedingly elusive. Time-dependent three-dimensional thermodynamic non-equilibrium simulations reveal the spontaneous formation of self-organized patterns of anode attachment spots in the free-burning arc, a canonical thermal plasma flow established by a constant dc current between an axi-symmetric electrode configuration in the absence of external forcing. The number of spots, their size and distribution within the pattern depend on the applied total current and on the resolution of the spatial discretization, whereas the main properties of the plasma flow, such as maximum temperatures, velocity and voltage drop, depend only on the former. The sensibility of the solution to the spatial discretization stresses the computational requirements for comprehensive arc discharge simulations. The obtained anode patterns qualitatively agree with experimental observations and confirm that the spots originate at the fringes of the arc–anode attachment. The results imply that heavy-species–electron energy equilibration, in addition to thermal instability, has a dominant role in the formation of anode spots in arc discharges. (paper)

Exploitation of Self Organization in UAV Swarms for Optimization in Combat Environments

National Research Council Canada - National Science Library

Nowak, Dustin J

2008-01-01

...) swarms using autonomous self-organized cooperative control. This development required the design of a new abstract UAV swarm control model which flows from an abstract Markov structure, a Partially Observable Markov Decision Process...

Organizing the History of Computing

Science.gov (United States)

Misa, Thomas J.

This paper tries to distill some of the ‘lessons learned’ from the Charles Babbage Institute’s quarter-century experience (1980-present) in organizing the history of computing. It draws on the author’s (recent) experience as CBI director; conversations with Arthur Norberg, CBI’s long-time founding director; and papers delivered at a special symposium appraising CBI’s role in computing history, which appeared in the IEEE Annals of the History of Computing 29 no. 4 (October-December 2007).

Self-Organization and Annealed Disorder in a Fracturing Process

DEFF Research Database (Denmark)

Caldarelli, Guido; Di Tolla, Francesco; Petri, Alberto

1996-01-01

We show that a vectorial model for inhomogeneous elastic media self-organizes under external stress. An onset of crack avalanches of every duration and length scale compatible with the lattice size is observed. The behavior is driven by the introduction of annealed disorder, i.e., by lowering...... condition for reproducing the algebraic distribution of the energy released during cracks formation....

Self-organized complex space charge configurations at the origin of flicker noise

International Nuclear Information System (INIS)

Popescu, S.; Lozneanu, E.; Sanduloviciu, M.

2003-01-01

Based on experimental results obtained from a plasma diode we explain the fluctuations of the voltage supported by a non-linear gaseous conductor by the dynamical behavior of spatiotemporal patterns, in the form of moving double layers, formed after self-organization. Such phenomena appear when the system is subjected to an external constraint that creates and maintains a local gradient of electron kinetic energy. The described phenomenology suggests a plausible explanation for the appearance of flicker noise also in other physical systems, as for example semiconductors and, implicitly, offers a new model for the so-called self-organized criticality concept

Organization, maturation and plasticity of multisensory integration: Insights from computational modelling studies

Directory of Open Access Journals (Sweden)

Cristiano eCuppini

2011-05-01

Full Text Available In this paper, we present two neural network models - devoted to two specific and widely investigated aspects of multisensory integration - in order to evidence the potentialities of computational models to gain insight into the neural mechanisms underlying organization, development and plasticity of multisensory integration in the brain. The first model considers visual-auditory interaction in a midbrain structure named Superior Colliculus (SC. The model is able to reproduce and explain the main physiological features of multisensory integration in SC neurons and to describe how SC integrative capability – not present at birth - develops gradually during postnatal life depending on sensory experience with cross-modal stimuli. The second model tackles the problem of how tactile stimuli on a body part and visual (or auditory stimuli close to the same body part are integrated in multimodal parietal neurons to form the perception of peripersonal (i.e., near space. The model investigates how the extension of peripersonal space - where multimodal integration occurs - may be modified by experience such as use of a tool to interact with the far space. The utility of the modelling approach relies on several aspects: i The two models, although devoted to different problems and simulating different brain regions, share some common mechanisms (lateral inhibition and excitation, non-linear neuron characteristics, recurrent connections, competition, Hebbian rules of potentiation and depression that may govern more generally the fusion of senses in the brain, and the learning and plasticity of multisensory integration. ii The models may help interpretation of behavioural and psychophysical responses in terms of neural activity and synaptic connections. iii The models can make testable predictions that can help guiding future experiments in order to validate, reject, or modify the main assumptions.

Self-Organization during Friction of Slide Bearing Antifriction Materials

Directory of Open Access Journals (Sweden)

Iosif S. Gershman

2015-12-01

Full Text Available This article discusses the peculiarities of self-organization behavior and formation of dissipative structures during friction of antifriction alloys for slide bearings against a steel counterbody. It shows that during self-organization, the moment of friction in a tribosystem may be decreasing with the load growth and in the bifurcations of the coefficient of friction with respect to load. Self-organization and the formation of dissipative structures lead to an increase in the seizure load.

Concept and Feasibility Study of Self-Organized Electrochemical Devices

National Research Council Canada - National Science Library

Moorehead, William

2002-01-01

.... In this work, using attractive and repulsive London-van der Waals forces, a self-organized, interpenetrating, separator-free rechargeable lithium ion battery called a self-organized battery system (SBS) is proposed...

Self-organization of spatial patterning in human embryonic stem cells

Science.gov (United States)

Deglincerti, Alessia; Etoc, Fred; Ozair, M. Zeeshan; Brivanlou, Ali H.

2017-01-01

The developing embryo is a remarkable example of self-organization, where functional units are created in a complex spatio-temporal choreography. Recently, human embryonic stem cells (ESCs) have been used to recapitulate in vitro the self-organization programs that are executed in the embryo in vivo. This represents a unique opportunity to address self-organization in humans that is otherwise not addressable with current technologies. In this essay, we review the recent literature on self-organization of human ESCs, with a particular focus on two examples: formation of embryonic germ layers and neural rosettes. Intriguingly, both activation and elimination of TGFβ signaling can initiate self-organization, albeit with different molecular underpinnings. We discuss the mechanisms underlying the formation of these structures in vitro and explore future challenges in the field. PMID:26970615

Self-Organization, Resilience and Robustness of Complex Systems Through an Application to Financial Market from an Agent-Based Approach

Science.gov (United States)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

This paper introduces the implementation of a computational agent-based financial market model in which the system is described on both microscopic and macroscopic levels. This artificial financial market model is used to study the system response when a shock occurs. Indeed, when a market experiences perturbations, financial systems behavior can exhibit two different properties: resilience and robustness. Through simulations and different scenarios of market shocks, these system properties are studied. The results notably show that the emergence of collective herding behavior when market shock occurs leads to a temporary disruption of the system self-organization. Numerical simulations highlight that the market can absorb strong mono-shocks but can also be led to rupture by low but repeated perturbations.

Emergence or self-organization?: Look to the soil population.

Science.gov (United States)

Addiscott, Tom

2011-07-01

EMERGENCE IS NOT WELL DEFINED, BUT ALL EMERGENT SYSTEMS HAVE THE FOLLOWING CHARACTERISTICS: the whole is more than the sum of the parts, they show bottom-up rather top-down organization and, if biological, they involve chemical signaling. Self-organization can be understood in terms of the second and third stages of thermodynamics enabling these stages used as analogs of ecosystem functioning. The second stage system was suggested earlier to provide a useful analog of the behavior of natural and agricultural ecosystems subjected to perturbations, but for this it needs the capacity for self-organization. Considering the hierarchy of the ecosystem suggests that this self-organization is provided by the third stage, whose entropy maximization acts as an analog of that of the soil population when it releases small molecules from much larger molecules in dead plant matter. This it does as vigorously as conditions allow. Through this activity, the soil population confers self-organization at both the ecosystem and the global level. The soil population has been seen as both emergent and self-organizing, supporting the suggestion that the two concepts are are so closely linked as to be virtually interchangeable. If this idea is correct one of the characteristics of a biological emergent system seems to be the ability to confer self-organization on an ecosystem or other entity which may be larger than itself. The beehive and the termite colony are emergent systems which share this ability.

Deterministic self-organization: Ordered positioning of InAs quantum dots by self-organized anisotropic strain engineering on patterned GaAs(311)B

International Nuclear Information System (INIS)

Selcuk, E.; Hamhuis, G.J.; Noetzel, R.

2009-01-01

Laterally ordered InGaAs quantum dot (QD) arrays, InAs QD molecules, and single InAs QDs in a spot-like periodic arrangement are created by self-organized anisotropic strain engineering of InGaAs/GaAs superlattice (SL) templates on planar GaAs (311)B substrates in molecular beam epitaxy. On shallow- and deep-patterned substrates the respectively generated steps and facets guide the self-organization process during SL template formation to create more complex ordering such as periodic stripes, depending on pattern design. Here we demonstrate for patterns such as shallow- and deepetched round holes and deep-etched zigzag mesas that the self-organized periodic arrangement of QD molecules and single QDs is spatially locked to the pattern sidewalls and corners. This extends the concept of guided self-organization to deterministic self-organization. Absolute position control of the QDs is achieved without one-to-one pattern definition. This guarantees the excellent arrangement control of the ordered QD molecules and single QDs with strong photoluminescence emission up to room temperature, which is required for future quantum functional devices. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Human brain as the model of a new computer system. II

Energy Technology Data Exchange (ETDEWEB)

Holtz, K; Langheld, E

1981-12-09

For Pt. I see IBID., Vol. 29, No. 22, P. 13 (1981). The authors describe the self-generating system of connections of a self-teaching no-program associative computer. The self-generating systems of connections are regarded as simulation models of the human brain and compared with the brain structure. The system hardware comprises microprocessor, PROM, memory, VDU, keyboard unit.

Nonlinear dynamics analysis of a self-organizing recurrent neural network: chaos waning.

Science.gov (United States)

Eser, Jürgen; Zheng, Pengsheng; Triesch, Jochen

2014-01-01

Self-organization is thought to play an important role in structuring nervous systems. It frequently arises as a consequence of plasticity mechanisms in neural networks: connectivity determines network dynamics which in turn feed back on network structure through various forms of plasticity. Recently, self-organizing recurrent neural network models (SORNs) have been shown to learn non-trivial structure in their inputs and to reproduce the experimentally observed statistics and fluctuations of synaptic connection strengths in cortex and hippocampus. However, the dynamics in these networks and how they change with network evolution are still poorly understood. Here we investigate the degree of chaos in SORNs by studying how the networks' self-organization changes their response to small perturbations. We study the effect of perturbations to the excitatory-to-excitatory weight matrix on connection strengths and on unit activities. We find that the network dynamics, characterized by an estimate of the maximum Lyapunov exponent, becomes less chaotic during its self-organization, developing into a regime where only few perturbations become amplified. We also find that due to the mixing of discrete and (quasi-)continuous variables in SORNs, small perturbations to the synaptic weights may become amplified only after a substantial delay, a phenomenon we propose to call deferred chaos.

Guided self-organization inception

CERN Document Server

2014-01-01

Is it possible to guide the process of self-organisation towards specific patterns and outcomes?  Wouldn’t this be self-contradictory?   After all, a self-organising process assumes a transition into a more organised form, or towards a more structured functionality, in the absence of centralised control.  Then how can we place the guiding elements so that they do not override rich choices potentially discoverable by an uncontrolled process?  This book presents different approaches to resolving this paradox.  In doing so, the presented studies address a broad range of phenomena, ranging from autopoietic systems to morphological computation, and from small-world networks to information cascades in swarms.  A large variety of methods is employed, from spontaneous symmetry breaking to information dynamics to evolutionary algorithms, creating a rich spectrum reflecting this emerging field. Demonstrating several foundational theories and frameworks, as well as innovative practical implementations, Guided S...

Computer organization and design the hardware/software interface

CERN Document Server

Hennessy, John L

1994-01-01

Computer Organization and Design: The Hardware/Software Interface presents the interaction between hardware and software at a variety of levels, which offers a framework for understanding the fundamentals of computing. This book focuses on the concepts that are the basis for computers.Organized into nine chapters, this book begins with an overview of the computer revolution. This text then explains the concepts and algorithms used in modern computer arithmetic. Other chapters consider the abstractions and concepts in memory hierarchies by starting with the simplest possible cache. This book di

Self-organized amniogenesis by human pluripotent stem cells in a biomimetic implantation-like niche

Science.gov (United States)

Shao, Yue; Taniguchi, Kenichiro; Gurdziel, Katherine; Townshend, Ryan F.; Xue, Xufeng; Yong, Koh Meng Aw; Sang, Jianming; Spence, Jason R.; Gumucio, Deborah L.; Fu, Jianping

2017-04-01

Amniogenesis--the development of amnion--is a critical developmental milestone for early human embryogenesis and successful pregnancy. However, human amniogenesis is poorly understood due to limited accessibility to peri-implantation embryos and a lack of in vitro models. Here we report an efficient biomaterial system to generate human amnion-like tissue in vitro through self-organized development of human pluripotent stem cells (hPSCs) in a bioengineered niche mimicking the in vivo implantation environment. We show that biophysical niche factors act as a switch to toggle hPSC self-renewal versus amniogenesis under self-renewal-permissive biochemical conditions. We identify a unique molecular signature of hPSC-derived amnion-like cells and show that endogenously activated BMP-SMAD signalling is required for the amnion-like tissue development by hPSCs. This study unveils the self-organizing and mechanosensitive nature of human amniogenesis and establishes the first hPSC-based model for investigating peri-implantation human amnion development, thereby helping advance human embryology and reproductive medicine.

Self-Organization of Spatial Patterning in Human Embryonic Stem Cells.

Science.gov (United States)

Deglincerti, Alessia; Etoc, Fred; Ozair, M Zeeshan; Brivanlou, Ali H

2016-01-01

The developing embryo is a remarkable example of self-organization, where functional units are created in a complex spatiotemporal choreography. Recently, human embryonic stem cells (ESCs) have been used to recapitulate in vitro the self-organization programs that are executed in the embryo in vivo. This represents an unique opportunity to address self-organization in humans that is otherwise not addressable with current technologies. In this chapter, we review the recent literature on self-organization of human ESCs, with a particular focus on two examples: formation of embryonic germ layers and neural rosettes. Intriguingly, both activation and elimination of TGFβ signaling can initiate self-organization, albeit with different molecular underpinnings. We discuss the mechanisms underlying the formation of these structures in vitro and explore future challenges in the field. © 2016 Elsevier Inc. All rights reserved.

Computer technology for self-management: a scoping review.

Science.gov (United States)

Jacelon, Cynthia S; Gibbs, Molly A; Ridgway, John Ve

2016-05-01

The purpose of this scoping review of literature is to explore the types of computer-based systems used for self-management of chronic disease, the goals and success of these systems, the value added by technology integration and the target audience for these systems. Technology is changing the way health care is provided and the way that individuals manage their health. Individuals with chronic diseases are now able to use computer-based systems to self-manage their health. These systems have the ability to remind users of daily activities, and to help them recognise when symptoms are worsening and intervention is indicated. However, there are many questions about the types of systems available, the goals of these systems and the success with which individuals with chronic illness are using them. This is a scoping review in which the Cumulative Index of Nursing and Allied Health Literature, PubMed and IEEE Xplore databases were searched. A total of 303 articles were reviewed, 89 articles were read in-depth and 30 were included in the scoping review. The Substitution, Augmentation, Modification, Redefinition model was used to evaluate the value added by the technology integration. Research on technology for self-management was conducted in 13 countries. Data analysis identified five kinds of platforms on which the systems were based, some systems were focused on a specific disease management processes, others were not. For individuals to effectively use systems to maintain maximum wellness, the systems must have a strong component of self-management and provide the user with meaningful information regarding their health states. Clinicians should choose systems for their clients based on the design, components and goals of the systems. © 2016 John Wiley & Sons Ltd.

Understanding Emergency Care Delivery Through Computer Simulation Modeling.

Science.gov (United States)

Laker, Lauren F; Torabi, Elham; France, Daniel J; Froehle, Craig M; Goldlust, Eric J; Hoot, Nathan R; Kasaie, Parastu; Lyons, Michael S; Barg-Walkow, Laura H; Ward, Michael J; Wears, Robert L

2018-02-01

In 2017, Academic Emergency Medicine convened a consensus conference entitled, "Catalyzing System Change through Health Care Simulation: Systems, Competency, and Outcomes." This article, a product of the breakout session on "understanding complex interactions through systems modeling," explores the role that computer simulation modeling can and should play in research and development of emergency care delivery systems. This article discusses areas central to the use of computer simulation modeling in emergency care research. The four central approaches to computer simulation modeling are described (Monte Carlo simulation, system dynamics modeling, discrete-event simulation, and agent-based simulation), along with problems amenable to their use and relevant examples to emergency care. Also discussed is an introduction to available software modeling platforms and how to explore their use for research, along with a research agenda for computer simulation modeling. Through this article, our goal is to enhance adoption of computer simulation, a set of methods that hold great promise in addressing emergency care organization and design challenges. © 2017 by the Society for Academic Emergency Medicine.

Ultrametricity and memory in a solvable model of self-organized criticality

International Nuclear Information System (INIS)

Boettcher, S.; Paczuski, M.

1996-01-01

Slowly driven dissipative systems may evolve to a critical state where long periods of apparent equilibrium are punctuated by intermittent avalanches of activity. We present a self-organized critical model of punctuated equilibrium behavior in the context of biological evolution, and solve it in the limit that the number of independent traits for each species diverges. We derive an exact equation of motion for the avalanche dynamics from the microscopic rules. In the continuum limit, avalanches propagate via a diffusion equation with a nonlocal, history dependent potential representing memory. This nonlocal potential gives rise to a non-Gaussian (fat) tail for the subdiffusive spreading of activity. The probability for the activity to spread beyond a distance r in time s decays as √(24/π)s -3/2 x 1/3 exp[-3/4x 1/3 ] for x=r 4 /s>1. The potential represents a hierarchy of time scales that is dynamically generated by the ultrametric structure of avalanches, which can be quantified in terms of open-quote open-quote backward close-quote close-quote avalanches. In addition, a number of other correlation functions characterizing the punctuated equilibrium dynamics are determined exactly

Self-organization at the frictional interface for green tribology.

Science.gov (United States)

Nosonovsky, Michael

2010-10-28

Despite the fact that self-organization during friction has received relatively little attention from tribologists so far, it has the potential for the creation of self-healing and self-lubricating materials, which are important for green or environment-friendly tribology. The principles of the thermodynamics of irreversible processes and of the nonlinear theory of dynamical systems are used to investigate the formation of spatial and temporal structures during friction. The transition to the self-organized state with low friction and wear occurs through destabilization of steady-state (stationary) sliding. The criterion for destabilization is formulated and several examples are discussed: the formation of a protective film, microtopography evolution and slip waves. The pattern formation may involve self-organized criticality and reaction-diffusion systems. A special self-healing mechanism may be embedded into the material by coupling the corresponding required forces. The analysis provides the structure-property relationship, which can be applied for the design optimization of composite self-lubricating and self-healing materials for various ecologically friendly applications and green tribology.

Landscapes of facilitation: how self-organized patchiness of aquatic macrophytes promotes diversity in streams.

Science.gov (United States)

Cornacchia, Loreta; van de Koppel, Johan; van der Wal, Daphne; Wharton, Geraldene; Puijalon, Sara; Bouma, Tjeerd J

2018-04-01

Spatial heterogeneity plays a crucial role in the coexistence of species. Despite recognition of the importance of self-organization in creating environmental heterogeneity in otherwise uniform landscapes, the effects of such self-organized pattern formation in promoting coexistence through facilitation are still unknown. In this study, we investigated the effects of pattern formation on species interactions and community spatial structure in ecosystems with limited underlying environmental heterogeneity, using self-organized patchiness of the aquatic macrophyte Callitriche platycarpa in streams as a model system. Our theoretical model predicted that pattern formation in aquatic vegetation - due to feedback interactions between plant growth, water flow and sedimentation processes - could promote species coexistence, by creating heterogeneous flow conditions inside and around the plant patches. The spatial plant patterns predicted by our model agreed with field observations at the reach scale in naturally vegetated rivers, where we found a significant spatial aggregation of two macrophyte species around C. platycarpa. Field transplantation experiments showed that C. platycarpa had a positive effect on the growth of both beneficiary species, and the intensity of this facilitative effect was correlated with the heterogeneous hydrodynamic conditions created within and around C. platycarpa patches. Our results emphasize the importance of self-organized patchiness in promoting species coexistence by creating a landscape of facilitation, where new niches and facilitative effects arise in different locations. Understanding the interplay between competition and facilitation is therefore essential for successful management of biodiversity in many ecosystems. © 2018 The Authors Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

Self-organization of physical fields and spin

International Nuclear Information System (INIS)

Pestov, I.B.

2008-01-01

The subject of the present investigation is the laws of intrinsic self-organization of fundamental physical fields. In the framework of the Theory of Self-Organization the geometrical and physical nature of spin phenomena is uncovered. The key points are spin symmetry (the fundamental realization of the concept of geometrical internal symmetry) and the spinning field (space of defining representation of spin symmetry). It is shown that the essence of spin is the bipolar structure of spin symmetry induced by the gravitational potentials. The bipolar structure provides natural violation of spin symmetry and leads to spinstatics (theory of spinning field outside the time) and spindynamics. The equations of spinstatics and spindynamics are derived. It is shown that Sommerfeld's formula can be derived from the equations of spindynamics and hence the correspondence principle is valid. This means that the Theory of Self-Organization provides the new understanding of spin phenomena

Distributed Fast Self-Organized Maps for Massive Spectrophotometric Data Analysis †.

Science.gov (United States)

Dafonte, Carlos; Garabato, Daniel; Álvarez, Marco A; Manteiga, Minia

2018-05-03

Analyzing huge amounts of data becomes essential in the era of Big Data, where databases are populated with hundreds of Gigabytes that must be processed to extract knowledge. Hence, classical algorithms must be adapted towards distributed computing methodologies that leverage the underlying computational power of these platforms. Here, a parallel, scalable, and optimized design for self-organized maps (SOM) is proposed in order to analyze massive data gathered by the spectrophotometric sensor of the European Space Agency (ESA) Gaia spacecraft, although it could be extrapolated to other domains. The performance comparison between the sequential implementation and the distributed ones based on Apache Hadoop and Apache Spark is an important part of the work, as well as the detailed analysis of the proposed optimizations. Finally, a domain-specific visualization tool to explore astronomical SOMs is presented.

Formal modeling and verification of systems with self-x properties

OpenAIRE

Reif, Wolfgang

2006-01-01

Formal modeling and verification of systems with self-x properties / Matthias Güdemann, Frank Ortmeier and Wolfgang Reif. - In: Autonomic and trusted computing : third international conference, ATC 2006, Wuhan, China, September 3-6, 2006 ; proceedings / Laurence T. Yang ... (eds.). - Berlin [u.a.] : Springer, 2006. - S. 38-47. - (Lecture notes in computer science ; 4158)

Self-organized control in cooperative robots using a pattern formation principle

International Nuclear Information System (INIS)

Starke, Jens; Ellsaesser, Carmen; Fukuda, Toshio

2011-01-01

Self-organized modular approaches proved in nature to be robust and optimal and are a promising strategy to control future concepts of flexible and modular manufacturing processes. We show how this can be applied to a model of flexible manufacturing based on time-dependent robot-target assignment problems where robot teams have to serve manufacturing targets such that an objective function is optimized. Feasibility of the self-organized solutions can be guaranteed even for unpredictable situations like sudden changes in the demands or breakdowns of robots. As example an uncrewed space mission is visualized in a simulation where robots build a space station. - Highlights: → Adapting a pattern formation principle to control cooperative robots in a robust way. → Flexible manufacturing systems are modelled by time-dependent assignment problems. → Coupled selection equations guarantee feasibility of solutions. → Solution structure (permutations) is not destroyed by inhomogeneous growth rates. → Example of an uncrewed space mission shows effectivity and robustness.

Firm Size, a Self-Organized Critical Phenomenon: Evidence from the Dynamical Systems Theory

Science.gov (United States)

Chandra, Akhilesh

This research draws upon a recent innovation in the dynamical systems literature called the theory of self -organized criticality (SOC) (Bak, Tang, and Wiesenfeld 1988) to develop a computational model of a firm's size by relating its internal and the external sub-systems. As a holistic paradigm, the theory of SOC implies that a firm as a composite system of many degrees of freedom naturally evolves to a critical state in which a minor event starts a chain reaction that can affect either a part or the system as a whole. Thus, the global features of a firm cannot be understood by analyzing its individual parts separately. The causal framework builds upon a constant capital resource to support a volume of production at the existing level of efficiency. The critical size is defined as the production level at which the average product of a firm's factors of production attains its maximum value. The non -linearity is inferred by a change in the nature of relations at the border of criticality, between size and the two performance variables, viz., the operating efficiency and the financial efficiency. The effect of breaching the critical size is examined on the stock price reactions. Consistent with the theory of SOC, it is hypothesized that the temporal response of a firm breaching the level of critical size should behave as a flicker noise (1/f) process. The flicker noise is characterized by correlations extended over a wide range of time scales, indicating some sort of cooperative effect among a firm's degrees of freedom. It is further hypothesized that a firm's size evolves to a spatial structure with scale-invariant, self-similar (fractal) properties. The system is said to be self-organized inasmuch as it naturally evolves to the state of criticality without any detailed specifications of the initial conditions. In this respect, the critical state is an attractor of the firm's dynamics. Another set of hypotheses examines the relations between the size and the

Self-Organization in 2D Traffic Flow Model with Jam-Avoiding Drive

Science.gov (United States)

Nagatani, Takashi

1995-04-01

A stochastic cellular automaton (CA) model is presented to investigate the traffic jam by self-organization in the two-dimensional (2D) traffic flow. The CA model is the extended version of the 2D asymmetric exclusion model to take into account jam-avoiding drive. Each site contains either a car moving to the up, a car moving to the right, or is empty. A up car can shift right with probability p ja if it is blocked ahead by other cars. It is shown that the three phases (the low-density phase, the intermediate-density phase and the high-density phase) appear in the traffic flow. The intermediate-density phase is characterized by the right moving of up cars. The jamming transition to the high-density jamming phase occurs with higher density of cars than that without jam-avoiding drive. The jamming transition point p 2c increases with the shifting probability p ja. In the deterministic limit of p ja=1, it is found that a new jamming transition occurs from the low-density synchronized-shifting phase to the high-density moving phase with increasing density of cars. In the synchronized-shifting phase, all up cars do not move to the up but shift to the right by synchronizing with the move of right cars. We show that the jam-avoiding drive has an important effect on the dynamical jamming transition.

Self-organized architectures from assorted DNA-framed nanoparticles

Science.gov (United States)

Liu, Wenyan; Halverson, Jonathan; Tian, Ye; Tkachenko, Alexei V.; Gang, Oleg

2016-09-01

The science of self-assembly has undergone a radical shift from asking questions about why individual components self-organize into ordered structures, to manipulating the resultant order. However, the quest for far-reaching nanomanufacturing requires addressing an even more challenging question: how to form nanoparticle (NP) structures with designed architectures without explicitly prescribing particle positions. Here we report an assembly concept in which building instructions are embedded into NPs via DNA frames. The integration of NPs and DNA origami frames enables the fabrication of NPs with designed anisotropic and selective interactions. Using a pre-defined set of different DNA-framed NPs, we show it is possible to design diverse planar architectures, which include periodic structures and shaped meso-objects that spontaneously emerge on mixing of the different topological types of NP. Even objects of non-trivial shapes, such as a nanoscale model of Leonardo da Vinci's Vitruvian Man, can be self-assembled successfully.

17 CFR 201.420 - Appeal of determinations by self-regulatory organizations.

Science.gov (United States)

2010-04-01

... self-regulatory organizations. 201.420 Section 201.420 Commodity and Securities Exchanges SECURITIES... Review § 201.420 Appeal of determinations by self-regulatory organizations. (a) Application for review... by a self-regulatory organization determination as to which a notice is required to be filed with the...

Organic Chemistry Self Instructional Package 2: Methane.

Science.gov (United States)

Zdravkovich, V.

This booklet, one of a series of 17 developed at Prince George's Community College, Largo, Maryland, provides an individualized, self-paced undergraduate organic chemistry instruction module designed to augment any course in organic chemistry but particularly those taught using the text "Organic Chemistry" by Morrison and Boyd. The…

Organic Chemistry Self Instructional Package 12: Alkynes.

Science.gov (United States)

Zdravkovich, V.

This booklet, one of a series of 17 developed at Prince George's Community College, Largo, Maryland, provides an individualized, self-paced undergraduate organic chemistry instruction module designed to augment any course in organic chemistry but particularly those taught using the text "Organic Chemistry" by Morrison and Boyd. The…

Total energy calculations from self-energy models

International Nuclear Information System (INIS)

Sanchez-Friera, P.

2001-06-01

Density-functional theory is a powerful method to calculate total energies of large systems of interacting electrons. The usefulness of this method, however, is limited by the fact that an approximation is required for the exchange-correlation energy. Currently used approximations (LDA and GGA) are not sufficiently accurate in many physical problems, as for instance the study of chemical reactions. It has been shown that exchange-correlation effects can be accurately described via the self-energy operator in the context of many-body perturbation theory. This is, however, a computationally very demanding approach. In this thesis a new scheme for calculating total energies is proposed, which combines elements from many-body perturbation theory and density-functional theory. The exchange-correlation energy functional is built from a simplified model of the self-energy, that nevertheless retains the main features of the exact operator. The model is built in such way that the computational effort is not significantly increased with respect to that required in a typical density-functional theory calculation. (author)

Self-modified quasi-stationary model for the radiation ablation

International Nuclear Information System (INIS)

Zhang Jun; Pei Wenbing; Gu Peijun; Sui Chengzhi; Chang Tieqiang

1996-01-01

The self-modified quasi-stationary model for radiation ablation has been established based on physical picture of numerical simulations. The objective of the model is to predict quantitatively the scaling laws of various ablation parameters driven by soft-X-ray, such as the dependence of ablation depth, pressure on radiation temperature, energy, pulse width, without resorting to complex computer simulations. The computational results are given for some interesting materials in ICF. Scaling laws obtained are simple and effective in target design and analysis of experimental results

Cascade and intermittency model for turbulent compressible self-gravitating matter and self-binding phase-space density fluctuations

International Nuclear Information System (INIS)

Biglari, H.; Diamond, P.H.

1988-01-01

A simple physical model which describes the dynamics of turbulence and the spectrum of density fluctuations in compressible, self-gravitating matter and self-binding, phase-space density fluctuations is presented. The two systems are analogous to each other in that each tends to self-organize into hierarchical structures via the mechanism of Jeans collapse. The model, the essential physical ingredient of which is a cascade constrained by the physical requirement of quasivirialization, is shown to exhibit interesting geometric properties such as intrinsic intermittency and anisotropy

The microscopic origin of self-organized nanostripe pattern formation on an electropolished aluminium surface

International Nuclear Information System (INIS)

Sarkar, Jaya; Basumallick, A; Khan, Gobinda Gopal

2009-01-01

By correlating the experimental evidence obtained from atomic force microscopy, conventional x-ray diffraction, and a surface sensitive modified x-ray diffraction technique with the results of density functional theory based computations, we demonstrate that self-organized nanostripe patterns formed on the electropolished surface of aluminium originate as a consequence of relaxation and reconstruction of the new surfaces exposed and textural changes at the surface caused by the dissolution during polishing.

Portraits of self-organization in fish schools interacting with robots

Science.gov (United States)

Aureli, M.; Fiorilli, F.; Porfiri, M.

2012-05-01

In this paper, we propose an enabling computational and theoretical framework for the analysis of experimental instances of collective behavior in response to external stimuli. In particular, this work addresses the characterization of aggregation and interaction phenomena in robot-animal groups through the exemplary analysis of fish schooling in the vicinity of a biomimetic robot. We adapt global observables from statistical mechanics to capture the main features of the shoal collective motion and its response to the robot from experimental observations. We investigate the shoal behavior by using a diffusion mapping analysis performed on these global observables that also informs the definition of relevant portraits of self-organization.

Computer Experiences, Self-Efficacy and Knowledge of Students Enrolled in Introductory University Agriculture Courses.

Science.gov (United States)

Johnson, Donald M.; Ferguson, James A.; Lester, Melissa L.

1999-01-01

Of 175 freshmen agriculture students, 74% had prior computer courses, 62% owned computers. The number of computer topics studied predicted both computer self-efficacy and computer knowledge. A substantial positive correlation was found between self-efficacy and computer knowledge. (SK)

Self-organization of muscle cell structure and function.

Directory of Open Access Journals (Sweden)

Anna Grosberg

2011-02-01

Full Text Available The organization of muscle is the product of functional adaptation over several length scales spanning from the sarcomere to the muscle bundle. One possible strategy for solving this multiscale coupling problem is to physically constrain the muscle cells in microenvironments that potentiate the organization of their intracellular space. We hypothesized that boundary conditions in the extracellular space potentiate the organization of cytoskeletal scaffolds for directed sarcomeregenesis. We developed a quantitative model of how the cytoskeleton of neonatal rat ventricular myocytes organizes with respect to geometric cues in the extracellular matrix. Numerical results and in vitro assays to control myocyte shape indicated that distinct cytoskeletal architectures arise from two temporally-ordered, organizational processes: the interaction between actin fibers, premyofibrils and focal adhesions, as well as cooperative alignment and parallel bundling of nascent myofibrils. Our results suggest that a hierarchy of mechanisms regulate the self-organization of the contractile cytoskeleton and that a positive feedback loop is responsible for initiating the break in symmetry, potentiated by extracellular boundary conditions, is required to polarize the contractile cytoskeleton.

Self-organization of muscle cell structure and function.

Science.gov (United States)

Grosberg, Anna; Kuo, Po-Ling; Guo, Chin-Lin; Geisse, Nicholas A; Bray, Mark-Anthony; Adams, William J; Sheehy, Sean P; Parker, Kevin Kit

2011-02-01

The organization of muscle is the product of functional adaptation over several length scales spanning from the sarcomere to the muscle bundle. One possible strategy for solving this multiscale coupling problem is to physically constrain the muscle cells in microenvironments that potentiate the organization of their intracellular space. We hypothesized that boundary conditions in the extracellular space potentiate the organization of cytoskeletal scaffolds for directed sarcomeregenesis. We developed a quantitative model of how the cytoskeleton of neonatal rat ventricular myocytes organizes with respect to geometric cues in the extracellular matrix. Numerical results and in vitro assays to control myocyte shape indicated that distinct cytoskeletal architectures arise from two temporally-ordered, organizational processes: the interaction between actin fibers, premyofibrils and focal adhesions, as well as cooperative alignment and parallel bundling of nascent myofibrils. Our results suggest that a hierarchy of mechanisms regulate the self-organization of the contractile cytoskeleton and that a positive feedback loop is responsible for initiating the break in symmetry, potentiated by extracellular boundary conditions, is required to polarize the contractile cytoskeleton.

Organization of left–right coordination of neuronal activity in the mammalian spinal cord: Insights from computational modelling

Science.gov (United States)

Shevtsova, Natalia A; Talpalar, Adolfo E; Markin, Sergey N; Harris-Warrick, Ronald M; Kiehn, Ole; Rybak, Ilya A

2015-01-01

Different locomotor gaits in mammals, such as walking or galloping, are produced by coordinated activity in neuronal circuits in the spinal cord. Coordination of neuronal activity between left and right sides of the cord is provided by commissural interneurons (CINs), whose axons cross the midline. In this study, we construct and analyse two computational models of spinal locomotor circuits consisting of left and right rhythm generators interacting bilaterally via several neuronal pathways mediated by different CINs. The CIN populations incorporated in the models include the genetically identified inhibitory (V0D) and excitatory (V0V) subtypes of V0 CINs and excitatory V3 CINs. The model also includes the ipsilaterally projecting excitatory V2a interneurons mediating excitatory drive to the V0V CINs. The proposed network architectures and CIN connectivity allow the models to closely reproduce and suggest mechanistic explanations for several experimental observations. These phenomena include: different speed-dependent contributions of V0D and V0V CINs and V2a interneurons to left–right alternation of neural activity, switching gaits between the left–right alternating walking-like activity and the left–right synchronous hopping-like pattern in mutants lacking specific neuron classes, and speed-dependent asymmetric changes of flexor and extensor phase durations. The models provide insights into the architecture of spinal network and the organization of parallel inhibitory and excitatory CIN pathways and suggest explanations for how these pathways maintain alternating and synchronous gaits at different locomotor speeds. The models propose testable predictions about the neural organization and operation of mammalian locomotor circuits. Key points Coordination of neuronal activity between left and right sides of the mammalian spinal cord is provided by several sets of commissural interneurons (CINs) whose axons cross the midline. Genetically identified inhibitory V

Some Aspects of Nonlinearity and Self-Organization In Biosystems on Examples of Localized Excitations in the DNA Molecule and Generalized Fisher–KPP Model

Directory of Open Access Journals (Sweden)

A. V. Shapovalov

2018-02-01

Full Text Available This review deals with ideas and approaches to nonlinear phenomena, based on different branches of physics and related to biological systems, that focus on how small impacts can significantly change the state of the system at large spatial scales. This problem is very extensive, and it cannot be fully resolved in this paper. Instead, some selected physical effects are briefly reviewed. We consider sine-Gordon solitons and nonlinear Schrodinger solitons in some models of DNA as examples of self-organization at the molecular level, as well as examine features of their formation and dynamics under the influence of external influences. In addition, the formation of patterns in the generalized Fisher–KPP model is viewed as a simple example of self-organization in a system with nonlocal interaction at the cellular level. Symmetries of model equations are employed to analyze the considered nonlinear phenomena. In this context the possible relations between phenomena considered and released activity effect, which is assessed differently in the literature, are discussed.

Metal complexation and monolayer self-assembly of the bio-organic semiconductor Alizarin

Energy Technology Data Exchange (ETDEWEB)

Uppal, Neeti [Dept. Earth and Environmental Sciences, Ludwig-Maximilians-Universitaet Muenchen (LMU) and Center for NanoSciences (CeNS), Muenchen (Germany); Institut fuer Physik, Universitaet Augsburg (Germany); Gast, Norbert [Dept. Earth and Environmental Sciences, Ludwig-Maximilians-Universitaet Muenchen (LMU) and Center for NanoSciences (CeNS), Muenchen (Germany); Zentrum Neue Technologien, Deutsches Museum, Muenchen (Germany); Bueno, Martin [Fakultaet Feinwerk- und Mikrotechnik, Physikalische Technik, Hochschule Muenchen (Germany); Heckl, Wolfgang M. [Dept. of Physics, Technische Universitaet Muenchen (TUM), Garching (Germany); Zentrum Neue Technologien, Deutsches Museum, Muenchen (Germany); Trixler, Frank [Dept. Earth and Environmental Sciences, Ludwig-Maximilians-Universitaet Muenchen (LMU) and Center for NanoSciences (CeNS), Muenchen (Germany); Dept. of Physics, Technische Universitaet Muenchen (TUM), Garching (Germany); Zentrum Neue Technologien, Deutsches Museum, Muenchen (Germany)

2010-07-01

Organic Solid/Solid Wetting Deposition (OSWD) (Trixler et al.: Chem.Eur.J. 13 (2007), 7785) enables to deposit insoluble molecules such as organic pigments and semiconductors on substrate surfaces under ambient conditions. We explore the potential of OSWD to grow and manipulate monolayers of biomolecules and their chelates on graphite and use Alizarin as a model system - a natural organic compound which occurs mainly as an anthraquinone glycoside in plants. Our investigations via Scanning Tunneling Microscopy (STM), Tunneling Spectroscopy (TS) and Molecular Modelling reveal that OSWD works also with bio-organic molecules and chelate complexes and show that the advantages of OSWD (self-assembly under ambient conditions in a non-solvent environment, nanomanipulation via molecular extraction) can all be tapped.

Interpretation of fingerprint image quality features extracted by self-organizing maps

Science.gov (United States)

Danov, Ivan; Olsen, Martin A.; Busch, Christoph

2014-05-01

Accurate prediction of fingerprint quality is of significant importance to any fingerprint-based biometric system. Ensuring high quality samples for both probe and reference can substantially improve the system's performance by lowering false non-matches, thus allowing finer adjustment of the decision threshold of the biometric system. Furthermore, the increasing usage of biometrics in mobile contexts demands development of lightweight methods for operational environment. A novel two-tier computationally efficient approach was recently proposed based on modelling block-wise fingerprint image data using Self-Organizing Map (SOM) to extract specific ridge pattern features, which are then used as an input to a Random Forests (RF) classifier trained to predict the quality score of a propagated sample. This paper conducts an investigative comparative analysis on a publicly available dataset for the improvement of the two-tier approach by proposing additionally three feature interpretation methods, based respectively on SOM, Generative Topographic Mapping and RF. The analysis shows that two of the proposed methods produce promising results on the given dataset.

Computer-Based Self-Instructional Modules. Final Technical Report.

Science.gov (United States)

Weinstock, Harold

Reported is a project involving seven chemists, six mathematicians, and six physicists in the production of computer-based, self-study modules for use in introductory college courses in chemistry, physics, and mathematics. These modules were designed to be used by students and instructors with little or no computer backgrounds, in institutions…

Cyberinfrastructure to Support Collaborative and Reproducible Computational Hydrologic Modeling

Science.gov (United States)

Goodall, J. L.; Castronova, A. M.; Bandaragoda, C.; Morsy, M. M.; Sadler, J. M.; Essawy, B.; Tarboton, D. G.; Malik, T.; Nijssen, B.; Clark, M. P.; Liu, Y.; Wang, S. W.

2017-12-01

Creating cyberinfrastructure to support reproducibility of computational hydrologic models is an important research challenge. Addressing this challenge requires open and reusable code and data with machine and human readable metadata, organized in ways that allow others to replicate results and verify published findings. Specific digital objects that must be tracked for reproducible computational hydrologic modeling include (1) raw initial datasets, (2) data processing scripts used to clean and organize the data, (3) processed model inputs, (4) model results, and (5) the model code with an itemization of all software dependencies and computational requirements. HydroShare is a cyberinfrastructure under active development designed to help users store, share, and publish digital research products in order to improve reproducibility in computational hydrology, with an architecture supporting hydrologic-specific resource metadata. Researchers can upload data required for modeling, add hydrology-specific metadata to these resources, and use the data directly within HydroShare.org for collaborative modeling using tools like CyberGIS, Sciunit-CLI, and JupyterHub that have been integrated with HydroShare to run models using notebooks, Docker containers, and cloud resources. Current research aims to implement the Structure For Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model within HydroShare to support hypothesis-driven hydrologic modeling while also taking advantage of the HydroShare cyberinfrastructure. The goal of this integration is to create the cyberinfrastructure that supports hypothesis-driven model experimentation, education, and training efforts by lowering barriers to entry, reducing the time spent on informatics technology and software development, and supporting collaborative research within and across research groups.

A self-organized criticality model for ion temperature gradient mode driven turbulence in confined plasma

Science.gov (United States)

Isliker, H.; Pisokas, Th.; Strintzi, D.; Vlahos, L.

2010-08-01

A new self-organized criticality (SOC) model is introduced in the form of a cellular automaton (CA) for ion temperature gradient (ITG) mode driven turbulence in fusion plasmas. Main characteristics of the model are that it is constructed in terms of the actual physical variable, the ion temperature, and that the temporal evolution of the CA, which necessarily is in the form of rules, mimics actual physical processes as they are considered to be active in the system, i.e., a heating process and a local diffusive process that sets on if a threshold in the normalized ITG R /LT is exceeded. The model reaches the SOC state and yields ion temperature profiles of exponential shape, which exhibit very high stiffness, in that they basically are independent of the loading pattern applied. This implies that there is anomalous heat transport present in the system, despite the fact that diffusion at the local level is imposed to be of a normal kind. The distributions of the heat fluxes in the system and of the heat out-fluxes are of power-law shape. The basic properties of the model are in good qualitative agreement with experimental results.

A self-organized criticality model for ion temperature gradient mode driven turbulence in confined plasma

International Nuclear Information System (INIS)

Isliker, H.; Pisokas, Th.; Vlahos, L.; Strintzi, D.

2010-01-01

A new self-organized criticality (SOC) model is introduced in the form of a cellular automaton (CA) for ion temperature gradient (ITG) mode driven turbulence in fusion plasmas. Main characteristics of the model are that it is constructed in terms of the actual physical variable, the ion temperature, and that the temporal evolution of the CA, which necessarily is in the form of rules, mimics actual physical processes as they are considered to be active in the system, i.e., a heating process and a local diffusive process that sets on if a threshold in the normalized ITG R/L T is exceeded. The model reaches the SOC state and yields ion temperature profiles of exponential shape, which exhibit very high stiffness, in that they basically are independent of the loading pattern applied. This implies that there is anomalous heat transport present in the system, despite the fact that diffusion at the local level is imposed to be of a normal kind. The distributions of the heat fluxes in the system and of the heat out-fluxes are of power-law shape. The basic properties of the model are in good qualitative agreement with experimental results.

FPGA implementation of self organizing map with digital phase locked loops.

Science.gov (United States)

Hikawa, Hiroomi

2005-01-01

The self-organizing map (SOM) has found applicability in a wide range of application areas. Recently new SOM hardware with phase modulated pulse signal and digital phase-locked loops (DPLLs) has been proposed (Hikawa, 2005). The system uses the DPLL as a computing element since the operation of the DPLL is very similar to that of SOM's computation. The system also uses square waveform phase to hold the value of the each input vector element. This paper discuss the hardware implementation of the DPLL SOM architecture. For effective hardware implementation, some components are redesigned to reduce the circuit size. The proposed SOM architecture is described in VHDL and implemented on field programmable gate array (FPGA). Its feasibility is verified by experiments. Results show that the proposed SOM implemented on the FPGA has a good quantization capability, and its circuit size very small.

Distributed Fast Self-Organized Maps for Massive Spectrophotometric Data Analysis †

Directory of Open Access Journals (Sweden)

Carlos Dafonte

2018-05-01

Full Text Available Analyzing huge amounts of data becomes essential in the era of Big Data, where databases are populated with hundreds of Gigabytes that must be processed to extract knowledge. Hence, classical algorithms must be adapted towards distributed computing methodologies that leverage the underlying computational power of these platforms. Here, a parallel, scalable, and optimized design for self-organized maps (SOM is proposed in order to analyze massive data gathered by the spectrophotometric sensor of the European Space Agency (ESA Gaia spacecraft, although it could be extrapolated to other domains. The performance comparison between the sequential implementation and the distributed ones based on Apache Hadoop and Apache Spark is an important part of the work, as well as the detailed analysis of the proposed optimizations. Finally, a domain-specific visualization tool to explore astronomical SOMs is presented.

The Four Sources of Influence on Computer Self-Efficacy.

Science.gov (United States)

Smith, Sheila M.

2001-01-01

Using Bandura's four sources of influence on self-efficacy, 210 students rated their computer self-efficacy. Mastery experiences were most influential for white males; vicarious learning had the most influence for females and nonwhite students. (Contains 29 references.) (SK)

TEACHERS’ COMPUTER SELF-EFFICACY AND THEIR USE OF EDUCATIONAL TECHNOLOGY

Directory of Open Access Journals (Sweden)

Vehbi TUREL

2014-10-01

Full Text Available This study examined the use of educational technology by primary and subject teachers (i.e. secondary and high school teachers in a small town in the eastern part of Turkey in the spring of 2012. The study examined the primary, secondary and high school teachers’ Ø personal and computer related (demographic characteristics, Ø their computer self-efficacy perceptions, Ø their computer-using level in certain software, Ø their frequency of computer use for teaching, administrative and communication objectives, and Ø their use of educational technology preferences for preparation and teaching purposes. In this study, all primary, secondary and high school teachers in the small town were given the questionnaires to complete. 158 teachers (n=158 completed and returned them. The study was mostly quantitative and partly qualitative. The quantitative results were analysed with SPSS (i.e. mean, Std. Deviation, frequency, percentage, ANOVA. The qualitative data were analysed with examining the participants’ responses gathered from the open-ended questions and focussing on the shared themes among the responses. The results reveal that the teachers think that they have good computer self-efficacy perceptions, their level in certain programs is good, and they often use computers for a wide range of purposes. There are also statistical differences between; Ø their computer self-efficacy perceptions, Ø frequency of computer use for certain purposes, and Ø computer level in certain programs in terms of different independent variables.

Self-interaction and charge transfer in organic semiconductors

Energy Technology Data Exchange (ETDEWEB)

Koerzdoerfer, Thomas

2009-12-18

This work concentrates on the problem of self-interaction, which is one of the most serious problems of commonly used approximative density functionals. As a major result of this work, it is demonstrated that self-interaction plays a decisive role for the performance of different approximative functionals in predicting accurate electronic properties of organic molecular semiconductors. In search for a solution to the self-interaction problem, a new concept for correcting commonly used density functionals for self-interaction is introduced and applied to a variety of systems, spanning small molecules, extended molecular chains, and organic molecular semiconductors. It is further shown that the performance of functionals that are not free from self-interaction can vary strongly for different systems and observables of interest, thus entailing the danger of misinterpretation of the results obtained from those functionals. The underlying reasons for the varying performance of commonly used density functionals are discussed thoroughly in this work. Finally, this thesis provides strategies that allow to analyze the reliability of commonly used approximations to the exchange-correlation functional for particular systems of interest. This cumulative dissertation is divided into three parts. Part I gives a short introduction into DFT and its time-dependent extension (TDDFT). Part II provides further insights into the self-interaction problem, presents a newly developed concept for the correction of self-interaction, gives an introduction into the publications, and discusses their basic results. Finally, the four publications on self-interaction and charge-transfer in extended molecular systems and organic molecular semiconductors are collected in Part III. (orig.)

Subwavelength Microstructures Fabrication by Self-Organization Processes in Photopolymerizable Nanocomposite

Directory of Open Access Journals (Sweden)

I. Yu. Denisyuk

2012-01-01

Full Text Available This paper describes our research results on nanometers sizes subwavelength nanostructure fabrication by UV curing of special nanocomposite material with self-organization and light self-focusing effects. For this purpose, special UV curable nanocomposite material with a set of effects was developing: light self-focusing in the photopolymer with positive refractive index change, self-organization based on photo-induced nanoparticles transportation, and oxygen-based polymerization threshold. Both holographic and projection lithography writing methods application for microstructure making shows geometrical optical laws perturbation as result of nanocomposite self-organization effects with formation of nanometers-sized high-aspect-ratio structures. Obtained results will be useful for diffraction limit overcoming in projection lithography as well as for deep lithography technique.

Thought analysis on self-organization theories of MHD plasma

International Nuclear Information System (INIS)

Kondoh, Yoshiomi; Sato, Tetsuya.

1992-08-01

A thought analysis on the self-organization theories of dissipative MHD plasma is presented to lead to three groups of theories that lead to the same relaxed state of ∇ x B = λB, in order to find an essential physical picture embedded in the self-organization phenomena due to nonlinear and dissipative processes. The self-organized relaxed state due to the dissipation by the Ohm loss is shown to be formulated generally as the state such that yields the minimum dissipation rate of global auto-and/or cross-correlations between two quantities in j, B, and A for their own instantaneous values of the global correlations. (author)

Self-organized criticality in fragmenting

DEFF Research Database (Denmark)

Oddershede, L.; Dimon, P.; Bohr, J.

1993-01-01

The measured mass distributions of fragments from 26 fractured objects of gypsum, soap, stearic paraffin, and potato show evidence of obeying scaling laws; this suggests the possibility of self-organized criticality in fragmenting. The probability of finding a fragment scales inversely to a power...

Atomic switch networks-nanoarchitectonic design of a complex system for natural computing.

Science.gov (United States)

Demis, E C; Aguilera, R; Sillin, H O; Scharnhorst, K; Sandouk, E J; Aono, M; Stieg, A Z; Gimzewski, J K

2015-05-22

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing-a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

Discerning Thermodynamic Basis of Self-Organization in Critical Zone Structure and Function

Science.gov (United States)

Richardson, M.; Kumar, P.

2017-12-01

Self-organization characterizes the spontaneous emergence of order. Self-organization in the Critical Zone, the region of Earth's skin from below the groundwater table to the top of the vegetation canopy, involves the interaction of biotic and abiotic processes occurring through a hierarchy of temporal and spatial scales. The self-organization is sustained through input of energy and material in an open system framework, and the resulting formations are called dissipative structures. Why do these local states of organization form and how are they thermodynamically favorable? We hypothesize that structure formation is linked to energy conversion and matter throughput rates across driving gradients. Furthermore, we predict that structures in the Critical Zone evolve based on local availability of nutrients, water, and energy. By considering ecosystems as open thermodynamic systems, we model and study the throughput signatures on short times scales to determine origins and characteristics of ecosystem structure. This diagnostic approach allows us to use fluxes of matter and energy to understand the thermodynamic drivers of the system. By classifying the fluxes and dynamics in a system, we can identify patterns to determine the thermodynamic drivers for organized states. Additionally, studying the partitioning of nutrients, water, and energy throughout ecosystems through dissipative structures will help identify reasons for structure shapes and how these shapes impact major Critical Zone functions.

Sugar-Based Polyamides: Self-Organization in Strong Polar Organic Solvents.

Science.gov (United States)

Rosu, Cornelia; Russo, Paul S; Daly, William H; Cueto, Rafael; Pople, John A; Laine, Roger A; Negulescu, Ioan I

2015-09-14

Periodic patterns resembling spirals were observed to form spontaneously upon unassisted cooling of d-glucaric acid- and d-galactaric acid-based polyamide solutions in N-methyl-N-morpholine oxide (NMMO) monohydrate. Similar observations were made in d-galactaric acid-based polyamide/ionic liquid (IL) solutions. The morphologies were investigated by optical, polarized light and confocal microscopy assays to reveal pattern details. Differential scanning calorimetry was used to monitor solution thermal behavior. Small- and wide-angle X-ray scattering data reflected the complex and heterogeneous nature of the self-organized patterns. Factors such as concentration and temperature were found to influence spiral dimensions and geometry. The distance between rings followed a first-order exponential decay as a function of polymer concentration. Fourier-Transform Infrared Microspectroscopy analysis of spirals pointed to H-bonding between the solvent and the pendant hydroxyl groups of the glucose units from the polymer backbone. Tests on self-organization into spirals of ketal-protected d-galactaric acid polyamides in NMMO monohydrate confirmed the importance of the monosaccharide's pendant free hydroxyl groups on the formation of these patterns. Rheology performed on d-galactaric-based polyamides at high concentration in NMMO monohydrate solution revealed the optimum conditions necessary to process these materials as fibers by spinning. The self-organization of these sugar-based polyamides mimics certain biological materials.

Time series modeling, computation, and inference

CERN Document Server

Prado, Raquel

2010-01-01

The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit

Enabling Self-Organization in Embedded Systems with Reconfigurable Hardware

Directory of Open Access Journals (Sweden)

Christophe Bobda

2009-01-01

Full Text Available We present a methodology based on self-organization to manage resources in networked embedded systems based on reconfigurable hardware. Two points are detailed in this paper, the monitoring system used to analyse the system and the Local Marketplaces Global Symbiosis (LMGS concept defined for self-organization of dynamically reconfigurable nodes.

Use of the self-organizing feature map to diagnose abnormal engineering change

Science.gov (United States)

Lu, Ruei-Shan; Wu, Zhi-Ting; Peng, Kuo-Wei; Yu, Tai-Yi

2015-07-01

This study established identification manners with self-organizing feature map (SOM) to achieve the goal of monitoring Engineering Change (EC) based on historical data of a company that specializes in computers and peripherals. The product life cycle of this company is 3-6 months. The historical data were divided into three parts, each covering four months. The first part, comprising 2,343 records from January to April (the training period), comprise the Control Group. The second and third parts comprise Experimental Groups (EG) 1 and 2, respectively. For EG 1 and 2, the successful rate of recognizing information on abnormal ECs was approximately 96% and 95%, respectively. This paper shows the importance and screening procedures of abnormal engineering change for a particular company specializing in computers and peripherals.

Computer system organization the B5700/B6700 series

CERN Document Server

Organick, Elliott I

1973-01-01

Computer System Organization: The B5700/B6700 Series focuses on the organization of the B5700/B6700 Series developed by Burroughs Corp. More specifically, it examines how computer systems can (or should) be organized to support, and hence make more efficient, the running of computer programs that evolve with characteristically similar information structures.Comprised of nine chapters, this book begins with a background on the development of the B5700/B6700 operating systems, paying particular attention to their hardware/software architecture. The discussion then turns to the block-structured p

Stage-structured matrix models for organisms with non-geometric development times

Science.gov (United States)

Andrew Birt; Richard M. Feldman; David M. Cairns; Robert N. Coulson; Maria Tchakerian; Weimin Xi; James M. Guldin

2009-01-01

Matrix models have been used to model population growth of organisms for many decades. They are popular because of both their conceptual simplicity and their computational efficiency. For some types of organisms they are relatively accurate in predicting population growth; however, for others the matrix approach does not adequately model...

Teaching Computer Organization and Architecture Using Simulation and FPGA Applications

OpenAIRE

D. K.M. Al-Aubidy

2007-01-01

This paper presents the design concepts and realization of incorporating micro-operation simulation and FPGA implementation into a teaching tool for computer organization and architecture. This teaching tool helps computer engineering and computer science students to be familiarized practically with computer organization and architecture through the development of their own instruction set, computer programming and interfacing experiments. A two-pass assembler has been designed and implemente...

The Self-Organized Archive: SPASE, PDS and Archive Cooperatives

Science.gov (United States)

King, T. A.; Hughes, J. S.; Roberts, D. A.; Walker, R. J.; Joy, S. P.

2005-05-01

Information systems with high quality metadata enable uses and services which often go beyond the original purpose. There are two types of metadata: annotations which are items that comment on or describe the content of a resource and identification attributes which describe the external properties of the resource itself. For example, annotations may indicate which columns are present in a table of data, whereas an identification attribute would indicate source of the table, such as the observatory, instrument, organization, and data type. When the identification attributes are collected and used as the basis of a search engine, a user can constrain on an attribute, the archive can then self-organize around the constraint, presenting the user with a particular view of the archive. In an archive cooperative where each participating data system or archive may have its own metadata standards, providing a multi-system search engine requires that individual archive metadata be mapped to a broad based standard. To explore how cooperative archives can form a larger self-organized archive we will show how the Space Physics Archive Search and Extract (SPASE) data model will allow different systems to create a cooperative and will use Planetary Data System (PDS) plus existing space physics activities as a demonstration.

Self-Organization in Aggregating Robot Swarms: A DW-KNN Topological Approach

KAUST Repository

Khaldi, Belkacem

2018-02-02

In certain swarm applications, where the inter-agent distance is not the only factor in the collective behaviours of the swarm, additional properties such as density could have a crucial effect. In this paper, we propose applying a Distance-Weighted K-Nearest Neighbouring (DW-KNN) topology to the behaviour of robot swarms performing self-organized aggregation, in combination with a virtual physics approach to keep the robots together. A distance-weighted function based on a Smoothed Particle Hydrodynamic (SPH) interpolation approach, which is used to evaluate the robot density in the swarm, is applied as the key factor for identifying the K-nearest neighbours taken into account when aggregating the robots. The intra virtual physical connectivity among these neighbours is achieved using a virtual viscoelastic-based proximity model. With the ARGoS based-simulator, we model and evaluate the proposed approach, showing various self-organized aggregations performed by a swarm of N foot-bot robots. Also, we compared the aggregation quality of DW-KNN aggregation approach to that of the conventional KNN approach and found better performance.

Identification and ranking of the risk factors of cloud computing in State-Owned organizations

Directory of Open Access Journals (Sweden)

Noor Mohammad Yaghoubi

2015-05-01

Full Text Available Rapid development of processing and storage technologies and the success of the Internet have made computing resources cheaper, more powerful and more available than before. This technological trend has enabled the realization of a new computing model called cloud computing. Recently, the State-Owned organizations have begun to utilize cloud computing architectures, platforms, and applications to deliver services and meet constituents’ needs. Despite all of the advantages and opportunities of cloud computing technology, there are so many risks that State-Owned organizations need to know about before their migration to cloud environment. The purpose of this study is to identify and rank the risks factors of cloud computing in State-Owned organizations by making use of IT experts’ opinion. Firstly, by reviewing key articles, a comprehensive list of risks factors were extracted and classified into two categories: tangible and intangible. Then, six experts were interviewed about these risks and their classifications, and 10 risks were identified. After that, process of ranking the risks was done by seeking help from 52 experts and by fuzzy analytic hierarchy process. The results show that experts have identified intangible risks as the most important risks in cloud computing usage by State-Owned organizations. As the results indicate, "data confidentiality" risk has the highest place among the other risks.

Self-organized criticality as a paradigm for transport in magnetically confined plasmas

International Nuclear Information System (INIS)

Carreras, B.A.; Newman, D.; Lynch, V.E.; Diamond, P.H.

1996-01-01

Many models of natural phenomena manifest the basic hypothesis of self-organized criticality (SOC) [P. Bak, C. Tang, and K. Weisenfeld, Phys. Rev. Lett., 1987, vol. 59, p. 381]. The SOC concept brings together the self-similarity on space and time scales that are common to many of these phenomena. The application of the SOC modeling concept to the plasma dynamics near marginal stability opens new possibilities of understanding issues such as Bohm scaling, profile consistency, broad-band fluctuation spectra with universal characteristics, and fast time scales. In this paper, we review the SOC concept and its possible applications to the study of transport in magnetically confined plasmas

17 CFR 201.421 - Commission consideration of determinations by self-regulatory organizations.

Science.gov (United States)

2010-04-01

... determinations by self-regulatory organizations. 201.421 Section 201.421 Commodity and Securities Exchanges... Commission Review § 201.421 Commission consideration of determinations by self-regulatory organizations. (a..., order review of any determination by a self-regulatory organization that could be subject to an...

Self-Organized Fission Control for Flocking System

Directory of Open Access Journals (Sweden)

Mingyong Liu

2015-01-01

Full Text Available This paper studies the self-organized fission control problem for flocking system. Motivated by the fission behavior of biological flocks, information coupling degree (ICD is firstly designed to represent the interaction intensity between individuals. Then, from the information transfer perspective, a “maximum-ICD” based pairwise interaction rule is proposed to realize the directional information propagation within the flock. Together with the “separation/alignment/cohesion” rules, a self-organized fission control algorithm is established that achieves the spontaneous splitting of flocking system under conflict external stimuli. Finally, numerical simulations are provided to demonstrate the effectiveness of the proposed algorithm.

Internal structures of self-organized relaxed states and self-similar decay phase

International Nuclear Information System (INIS)

Kondoh, Yoshiomi

1992-03-01

A thought analysis on relaxation due to nonlinear processes is presented to lead to a set of general thoughts applicable to general nonlinear dynamical systems for finding out internal structures of the self-organized relaxed state without using 'invariant'. Three applications of the set of general thoughts to energy relaxations in resistive MHD plasmas, incompressible viscous fluids, and incompressible viscous MHD fluids are shown to lead to the internal structures of the self-organized relaxed states. It is shown that all of the relaxed states in these three dynamical systems are followed by self-similar decay phase without significant change of the spatial structure. The well known relaxed state of ∇ x B = ±λ B is shown to be derived generally in the low β plasma limit. (author)

Principle of Minimum Energy in Magnetic Reconnection in a Self-organized Critical Model for Solar Flares

Science.gov (United States)

Farhang, Nastaran; Safari, Hossein; Wheatland, Michael S.

2018-05-01

Solar flares are an abrupt release of magnetic energy in the Sun’s atmosphere due to reconnection of the coronal magnetic field. This occurs in response to turbulent flows at the photosphere that twist the coronal field. Similar to earthquakes, solar flares represent the behavior of a complex system, and expectedly their energy distribution follows a power law. We present a statistical model based on the principle of minimum energy in a coronal loop undergoing magnetic reconnection, which is described as an avalanche process. We show that the distribution of peaks for the flaring events in this self-organized critical system is scale-free. The obtained power-law index of 1.84 ± 0.02 for the peaks is in good agreement with satellite observations of soft X-ray flares. The principle of minimum energy can be applied for general avalanche models to describe many other phenomena.

Lamination of organic solar cells and organic light emitting devices: Models and experiments

International Nuclear Information System (INIS)

Oyewole, O. K.; Yu, D.; Du, J.; Asare, J.; Fashina, A.; Anye, V. C.; Zebaze Kana, M. G.; Soboyejo, W. O.

2015-01-01

In this paper, a combined experimental, computational, and analytical approach is used to provide new insights into the lamination of organic solar cells and light emitting devices at macro- and micro-scales. First, the effects of applied lamination force (on contact between the laminated layers) are studied. The crack driving forces associated with the interfacial cracks (at the bi-material interfaces) are estimated along with the critical interfacial crack driving forces associated with the separation of thin films, after layer transfer. The conditions for successful lamination are predicted using a combination of experiments and computational models. Guidelines are developed for the lamination of low-cost organic electronic structures

Self-organizing bioinspired oligothiophene–oligopeptide hybrids

Directory of Open Access Journals (Sweden)

Alexey K. Shaytan

2011-09-01

Full Text Available In this minireview, we survey recent advances in the synthesis, characterization, and modeling of new oligothiophene–oligopeptide hybrids capable of forming nanostructured fibrillar aggregates in solution and on solid substrates. Compounds of this class are promising for applications because their self-assembly and stimuli-responsive properties, provided by the peptide moieties combined with the semiconducting properties of the thiophene blocks, can result in novel opportunities for the design of advanced smart materials. These bio-inspired molecular hybrids are experimentally shown to form stable fibrils as visualized by AFM and TEM. While the experimental evidence alone is not sufficient to reveal the exact molecular organization of the fibrils, theoretical approaches based on quantum chemistry calculations and large-scale atomistic molecular dynamics simulations are attempted in an effort to reveal the structure of the fibrils at the nanoscale. Based on the combined theoretical and experimental analysis, the most likely models of fibril formation and aggregation are suggested.

Eco-evolutionary feedbacks in self-organized ecosystems

NARCIS (Netherlands)

de Jager, M.

2015-01-01

Spatial patterns in natural systems may appear amazingly complex. Yet, they can often be explained by a few simple rules. In self-organized ecosystems, complex spatial patterns at the ecosystem scale arise as the consequence of actions of and interactions between organisms at a local scale.

Self-Structured Organizing Single-Input CMAC Control for Robot Manipulator

Directory of Open Access Journals (Sweden)

ThanhQuyen Ngo

2011-09-01

Full Text Available This paper represents a self-structured organizing single-input control system based on differentiable cerebellar model articulation controller (CMAC for an n-link robot manipulator to achieve the high-precision position tracking. In the proposed scheme, the single-input CMAC controller is solely used to control the plant, so the input space dimension of CMAC can be simplified and no conventional controller is needed. The structure of single-input CMAC will also be self-organized; that is, the layers of single-input CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The online tuning laws of single-input CMAC parameters are derived in gradient-descent learning method and the discrete-type Lyapunov function is applied to determine the learning rates of proposed control system so that the stability of the system can be guaranteed. The simulation results of robot manipulator are provided to verify the effectiveness of the proposed control methodology.

Comparison between genetic algorithm and self organizing map to detect botnet network traffic

Science.gov (United States)

Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

2017-11-01

In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

Self-organization through decoupling

Directory of Open Access Journals (Sweden)

Romar Correa

2000-01-01

Full Text Available In one line of research, the transition from Fordism to flexible specialisation is explained by the infeasibility of a mode of regulation that relied on central controls. According to another explanation, which we favour, the disintegration of vertically integrated production is unpredictable. The concept of self-organization is often recommended to model the transition from hierarchical organizational forms to flatter structures. Formally, a conditionally stable nonlinear system of differential equations is examined. In the first thesis, the characteristic roots with positive real parts play the role of ‘order’ parameters which can become unstable modes. The rest of the variables refer to stable modes. The strategy is to show that the stable modes can be expressed in terms of the unstable modes so that the former can be eliminated from the system. On the other hand, we provide a theorem showing that a coupled set of differential equations can become uncoupled and vice versa as an argument in favour of the second thesis. The path of evolution can turn both ways.

Self-organization principles result in robust control of flexible manufacturing systems

DEFF Research Database (Denmark)

Nature shows us in our daily life how robust, flexible and optimal self-organized modular constructions work in complex physical, chemical and biological systems, which successfully adapt to new and unexpected situations. A promising strategy is therefore to use such self-organization and pattern...... problems with several autonomous robots and several targets are considered as model of flexible manufacturing systems. Each manufacturing target has to be served in a given time interval by one and only one robot and the total working costs have to be minimized (or total winnings maximized). A specifically...... constructed dynamical system approach (coupled selection equations) is used which is based on pattern formation principles and results in fault resistant and robust behaviour. An important feature is that this type of control also guarantees feasiblitiy of the assignment solutions. In previous work...

Predicting Cloud Computing Technology Adoption by Organizations: An Empirical Integration of Technology Acceptance Model and Theory of Planned Behavior

Science.gov (United States)

Ekufu, ThankGod K.

2012-01-01

Organizations are finding it difficult in today's economy to implement the vast information technology infrastructure required to effectively conduct their business operations. Despite the fact that some of these organizations are leveraging on the computational powers and the cost-saving benefits of computing on the Internet cloud, others…

Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network.

Science.gov (United States)

Del Papa, Bruno; Priesemann, Viola; Triesch, Jochen

2017-01-01

Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions - matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model's performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN's spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences.

From self-organization to emergence: Aesthetic implications of shifting ideas of organization

Science.gov (United States)

Hayles, N. Katherine

1996-06-01

From 1945-95, a shift took place within cybernetics from a paradigm emphasizing self-organization to one emphasizing emergence. Central in bringing about this shift was the spread of the microcomputer. With its greatly enhanced processing speed and memory capabilities, the microcomputer made simulations possible that could not have been done before. The microcomputer has also been instrumental in effecting a similar change within literary texts. To exemplify the aesthetic implications of the shift from self-organization to emergence, the chapter discusses Vladmir Nabokov's Pale Fire and Milorad Pavić's Dictionary of the Khazars: A Lexicon Novel in 100,000 Words.

Revisit to self-organization of solitons for dissipative Korteweg-de Vries equation

International Nuclear Information System (INIS)

Kondoh, Y.; Van Dam, J.W.

1995-03-01

The process by which self-organization occurs for solitons described by the Korteweg-de Vries (KdV) equation with a viscous dissipation term is reinvestigated theoretically, with the use of numerical simulations in a periodic system. It is shown that, during nonlinear interactions, two basic processes for the self-organization of solitons are energy transfer and selective dissipation among the eigenmodes of the dissipative operator. It is also clarified that an important process during nonlinear self-organization is an interchange between the dominant operators, which has hitherto been overlooked in conventional self-organization theories and which leads to a final self-similar coherent structure determined uniquely by the dissipative operator

Modeling Physical Processes at the Nanoscale—Insight into Self-Organization of Small Systems (abstract)

Science.gov (United States)

Proykova, Ana

2009-04-01

Essential contributions have been made in the field of finite-size systems of ingredients interacting with potentials of various ranges. Theoretical simulations have revealed peculiar size effects on stability, ground state structure, phases, and phase transformation of systems confined in space and time. Models developed in the field of pure physics (atomic and molecular clusters) have been extended and successfully transferred to finite-size systems that seem very different—small-scale financial markets, autoimmune reactions, and social group reactions to advertisements. The models show that small-scale markets diverge unexpectedly fast as a result of small fluctuations; autoimmune reactions are sequences of two discontinuous phase transitions; and social groups possess critical behavior (social percolation) under the influence of an external field (advertisement). Some predicted size-dependent properties have been experimentally observed. These findings lead to the hypothesis that restrictions on an object's size determine the object's total internal (configuration) and external (environmental) interactions. Since phases are emergent phenomena produced by self-organization of a large number of particles, the occurrence of a phase in a system containing a small number of ingredients is remarkable.

The Use of Hebbian Cell Assemblies for Nonlinear Computation

DEFF Research Database (Denmark)

Tetzlaff, Christian; Dasgupta, Sakyasingha; Kulvicius, Tomas

2015-01-01

When learning a complex task our nervous system self-organizes large groups of neurons into coherent dynamic activity patterns. During this, a network with multiple, simultaneously active, and computationally powerful cell assemblies is created. How such ordered structures are formed while preser...... computing complex non-linear transforms and - for execution - must cooperate with each other without interference. This mechanism, thus, permits the self-organization of computationally powerful sub-structures in dynamic networks for behavior control....

Phase transitions and self-organized criticality in networks of stochastic spiking neurons.

Science.gov (United States)

Brochini, Ludmila; de Andrade Costa, Ariadne; Abadi, Miguel; Roque, Antônio C; Stolfi, Jorge; Kinouchi, Osame

2016-11-07

Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains - a form of short-term plasticity probably located at the axon initial segment (AIS) - instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing.

Self-tolerance in a minimal model of the idiotypic network.

Science.gov (United States)

Schulz, Robert; Werner, Benjamin; Behn, Ulrich

2014-01-01

We consider the problem of self-tolerance in the frame of a minimalistic model of the idiotypic network. A node of this network represents a population of B-lymphocytes of the same idiotype, which is encoded by a bit string. The links of the network connect nodes with (nearly) complementary strings. The population of a node survives if the number of occupied neighbors is not too small and not too large. There is an influx of lymphocytes with random idiotype from the bone marrow. Previous investigations have shown that this system evolves toward highly organized architectures, where the nodes can be classified into groups according to their statistical properties. The building principles of these architectures can be analytically described and the statistical results of simulations agree very well with results of a modular mean-field theory. In this paper, we present simulation results for the case that one or several nodes, playing the role of self, are permanently occupied. These self nodes influence their linked neighbors, the autoreactive clones, but are themselves not affected by idiotypic interactions. We observe that the group structure of the architecture is very similar to the case without self antigen, but organized such that the neighbors of the self are only weakly occupied, thus providing self-tolerance. We also treat this situation in mean-field theory, which give results in good agreement with data from simulation. The model supports the view that autoreactive clones, which naturally occur also in healthy organisms are controlled by anti-idiotypic interactions, and could be helpful to understand network aspects of autoimmune disorders.

Autonomous Data Collection Using a Self-Organizing Map.

Science.gov (United States)

Faigl, Jan; Hollinger, Geoffrey A

2018-05-01

The self-organizing map (SOM) is an unsupervised learning technique providing a transformation of a high-dimensional input space into a lower dimensional output space. In this paper, we utilize the SOM for the traveling salesman problem (TSP) to develop a solution to autonomous data collection. Autonomous data collection requires gathering data from predeployed sensors by moving within a limited communication radius. We propose a new growing SOM that adapts the number of neurons during learning, which also allows our approach to apply in cases where some sensors can be ignored due to a lower priority. Based on a comparison with available combinatorial heuristic algorithms for relevant variants of the TSP, the proposed approach demonstrates improved results, while also being less computationally demanding. Moreover, the proposed learning procedure can be extended to cases where particular sensors have varying communication radii, and it can also be extended to multivehicle planning.

Fields of Tension in a Boundary-Crossing World: Towards a Democratic Organization of the Self.

Science.gov (United States)

Hermans, Hubert J M; Konopka, Agnieszka; Oosterwegel, Annerieke; Zomer, Peter

2017-12-01

In their study of the relationship between self and society, scientists have proposed taking society as a metaphor for understanding the dynamics of the self, such as the analogy between the self and the functioning of a totalitarian state or the analogy between the self and the functioning of a bureaucratic organization. In addition to these models, the present article proposes a democratic society as a metaphor for understanding the workings of a dialogical self in a globalizing, boundary-crossing world. The article follows four steps. In the first step the self is depicted as extended to the social and societal environment and made up of fields of tension in which a multiplicity of self-positions are involved in processes of positioning and counter-positioning and in relationships of social power. In the second step, the fertility of the democratic metaphor is demonstrated by referring to theory and research from three identity perspectives: multicultural, multiracial, and transgender. In the fields of tension emerging between the multiplicity of self-positions, new, hybrid, and mixed identities have a chance to emerge as adaptive responses to the limitations of existing societal structures. In the third step, we place the democratic self in a broader societal context by linking three levels of inclusiveness, proposed by Self-Categorization Theory (personal, social, and human) to recent conceptions of a cosmopolitan democracy. In the fourth and final step, a model is presented which allows the formulation of a series of specific research questions for future studies of a democratically organized self.

Extending Particle Swarm Optimisers with Self-Organized Criticality

DEFF Research Database (Denmark)

Løvbjerg, Morten; Krink, Thiemo

2002-01-01

Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster convergence and better solutions.......Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster convergence and better solutions....

CPU SIM: A Computer Simulator for Use in an Introductory Computer Organization-Architecture Class.

Science.gov (United States)

Skrein, Dale

1994-01-01

CPU SIM, an interactive low-level computer simulation package that runs on the Macintosh computer, is described. The program is designed for instructional use in the first or second year of undergraduate computer science, to teach various features of typical computer organization through hands-on exercises. (MSE)

Justifications and self-organization as determinants of recycling behavior. The case of used batteries

Energy Technology Data Exchange (ETDEWEB)

Hansmann, Ralf; Bernasconi, Petra; Smieszek, Timo; Loukopoulos, Peter; Scholz, Roland W [Chair of Environmental Sciences: Natural and Social Science Interface, Swiss Federal Institute of Technology, Zurich (ETH Zuerich), Universitaetsstrasse 22, ETH Zentrum CHN J76.3, CH-8092 Zurich (Switzerland)

2006-06-15

Much previous research on recycling behavior has drawn heavily on models of personal and perceived social norms, as well as of personal attitudes, to explain recycling behavior. Although such models have received empirical support, the issue concerning discrepancies between norms, personal attitudes and an individual's behavior is yet to be resolved. Using battery recycling in Switzerland as a case in point, the present questionnaire-based research examines via regression analyses the relationship between self-reported recycling behavior and socio-demographic variables, attitudes towards ecologically positive waste disposal, trust in waste disposal authorities, specific knowledge concerning recycling, justifications for not participating in the recycling scheme, self-organization of recycling behavior, and level of battery consumption. It was found that recycling knowledge, self-organization of recycling, and disagreement with justifications for non-recycling were positively related to recycling behavior, while attitudes towards ecological waste disposal and trust in waste disposal authorities were not directly related to respondents' self-reported battery recycling behavior. On the basis of these results, with reference to Sykes and Matza's Neutralization theory [Sykes GM, Matza D. Techniques of neutralization: a theory of delinquency. Am Sociol Rev 1957:22(6):664-70] a contextualized model of recycling behavior is proposed. This model is able to account for inconsistencies between personal attitudes and perceived social norms, and has practical implications for the design of public intervention strategies for enhancing participation in the recycling. (author)

Towards Self-Managed Executable Petri Nets

DEFF Research Database (Denmark)

Hansen, Klaus Marius; Zhang, Weishan; Ingstrup, Mads

2008-01-01

An issue in self-managed systems is that different abstractions and programming models are used on different architectural layers, leading to systems that are harder to build and understand. To alleviate this, we introduce a self-management approach which combines high-level Petri nets...... with the capability of distributed communication among nets. Organized in a three-layer goal management, change management, and component control architecture this allows for self-management in distributed systems. We validate the approach through the Flamenco/CPN middleware that allows for self-management of service......-oriented pervasive computing systems through the runtime interpretation of colored Petri nets. The current work focuses on the change management and component control layers....

Self-organizing groups : conditions and constraints in a sociotechnical perspective

NARCIS (Netherlands)

van der Zwaan, A.H.; Molleman, E.

1998-01-01

An increased level of self-organization, particularly in autonomous work teams, is widely believed to be a necessary part of a successful firm and a factor in many modern restructuring initiatives. This article investigates the limitations of self-organized groups and surveys these limitations from

Self-organization observed in either fusion or strongly coupled plasmas

International Nuclear Information System (INIS)

Himura, Haruhiko; Sanpei, Akio

2011-01-01

If self-organization happens in the fusion plasma, the plasma alters its shape by weakening the confining magnetic field. The self-organized plasma is stable and robust, so its configuration is conserved even during transport in asymmetric magnetic fields. The self-organization of the plasma is driven by an electrostatic potential. Examples of the plasma that has such strong potential are non-neutral plasmas of pure ions or electrons and dusty plasmas. In the present paper, characteristic phenomena of strongly coupled plasmas such as particle aggregation and formation of the ordered structure are discussed. (T.I.)

A stochastic large deformation model for computational anatomy

DEFF Research Database (Denmark)

Arnaudon, Alexis; Holm, Darryl D.; Pai, Akshay Sadananda Uppinakudru

2017-01-01

In the study of shapes of human organs using computational anatomy, variations are found to arise from inter-subject anatomical differences, disease-specific effects, and measurement noise. This paper introduces a stochastic model for incorporating random variations into the Large Deformation...

Life system modeling and intelligent computing. Pt. I. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Li, Kang; Irwin, George W. (eds.) [Belfast Queen' s Univ. (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Fei, Minrui; Jia, Li [Shanghai Univ. (China). School of Mechatronical Engineering and Automation

2010-07-01

This book is part I of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 55 papers in this volume are organized in topical sections on intelligent modeling, monitoring, and control of complex nonlinear systems; autonomy-oriented computing and intelligent agents; advanced theory and methodology in fuzzy systems and soft computing; computational intelligence in utilization of clean and renewable energy resources; intelligent modeling, control and supervision for energy saving and pollution reduction; intelligent methods in developing vehicles, engines and equipments; computational methods and intelligence in modeling genetic and biochemical networks and regulation. (orig.)

Effects of cement organic additives on the adsorption of uranyl ions on calcium silicate hydrate phases: experimental determination and computational molecular modelling

International Nuclear Information System (INIS)

Androniuk, Iuliia

2017-01-01

Cementitious materials are extensively used in the design and construction of radioactive waste repositories. One of the ways to enhance their performance is to introduce organic admixtures into the cement structure. However, the presence of organics in the pore water may affect the radionuclide mobility: organic molecules can form water-soluble complexes and compete for sorption sites. This work was designed to get detailed understanding of the mechanisms of such interactions on the molecular level. The model system has three components. First, pure C-S-H phases with different Ca/Si ratios were chosen as a cement model. Secondly, gluconate (a simple well-described molecule) is selected as a good starting organic additive model to probe the interaction mechanisms on the molecular scale. A more complex system involving poly-carboxylate super-plasticizer (PCE) was also tested. The third, U(VI), is a representative of the actinide radionuclide series. The development of description of the effects of organics for radioactive waste disposal applications was the primary objective of this work. The study of binary systems provides reference data for the investigation of more complex ternary (C-S-H/organic/U(VI)). The interactions are studied by means of both experimental and computational molecular modelling techniques. Data on sorption and desorption kinetics and isotherms for additives and for U(VI) on C-S-H are acquired in this work. In parallel, atomistic models are developed for the interfaces of interest. Structural, energetic, and dynamic aspects of the sorption processes on surface of cement are quantitatively modeled by molecular dynamics technique. (author)

Self-organization, Networks, Future

Directory of Open Access Journals (Sweden)

T. S. Akhromeyeva

2013-01-01

Full Text Available This paper presents an analytical review of a conference on the great scientist, a brilliant professor, an outstanding educator Sergei Kapitsa, held in November 2012. In the focus of this forum were problems of self-organization and a paradigm of network structures. The use of networks in the context of national defense, economics, management of mass consciousness was discussed. The analysis of neural networks in technical systems, the structure of the brain, as well as in the space of knowledge, information, and behavioral strategies plays an important role. One of the conference purposes was to an online organize community in Russia and to identify the most promising directions in this field. Some of them are presented in this paper.

Pseudo-self-organized topological phases in glassy selenides for IR photonics

Energy Technology Data Exchange (ETDEWEB)

Shpotyuk, O. [Lviv Institute of Materials of Scientific Research Company ' ' Carat' ' 202, Stryjska str., 79031 Lviv (Ukraine); Institute of Physics of Jan Dlugosz University 13/15, al. Armii Krajowej, 42201 Czestochowa (Poland); Golovchak, R. [Lviv Institute of Materials of Scientific Research Company ' ' Carat' ' 202, Stryjska str., 79031 Lviv (Ukraine)

2011-09-15

Network-forming cluster approach is applied to As-Se and Ge-Se glasses to justify their tendency to self-organization. It is shown that reversibility windows determined by temperature-modulated differential scanning calorimetry using short-term aged or as-prepared samples do not necessary coincide with self-organized phase in these materials. The obtained results testify also pseudo-self-organization phenomenon in Ge-Se glasses: over-constrained outrigger raft structural units built of two edge- and four corner-shared tetrahedra are interconnected via optimally-constrained {identical_to}Ge-Se-Se-Ge{identical_to} bridges within the range of compositions identified previously as self-organized phase by temperature modulated differential scanning calorimetry technique. (copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Methodology of modeling and measuring computer architectures for plasma simulations

Science.gov (United States)

Wang, L. P. T.

1977-01-01

A brief introduction to plasma simulation using computers and the difficulties on currently available computers is given. Through the use of an analyzing and measuring methodology - SARA, the control flow and data flow of a particle simulation model REM2-1/2D are exemplified. After recursive refinements the total execution time may be greatly shortened and a fully parallel data flow can be obtained. From this data flow, a matched computer architecture or organization could be configured to achieve the computation bound of an application problem. A sequential type simulation model, an array/pipeline type simulation model, and a fully parallel simulation model of a code REM2-1/2D are proposed and analyzed. This methodology can be applied to other application problems which have implicitly parallel nature.

Computer Intervention: Illness Self-Management/Quality of Life of Rural Women.

Science.gov (United States)

Weinert, Clarann; Cudney, Shirley; Comstock, Bryan; Bansal, Aasthaa

2014-03-01

The Women To Women project, a computer-based support and educational research intervention, was designed to help rural women better understand and manage their chronic illnesses. Its impact on psychosocial adaptation has been reported elsewhere. This article reports on the effect of a computer intervention on chronic illness self-management skills and quality of life. Using a parallel 2-group study design, the researchers randomized 309 middle-aged rural women with chronic conditions to either a computer-based intervention or a control group. They collected data on self-management of chronic illness and quality of life indicators at baseline and at the end of the intervention. Women in the intervention group reported significantly more self-efficacy in managing their chronic disease than those in the control group and the observed effect was of moderate size. Women in the intervention group also reported statistically significant gains in quality of life; effect sizes were small but consistent. Select chronic illness self-management skills and quality of life can be positively influenced by a well-designed computer intervention. Copyright© by Ingram School of Nursing, McGill University.

A unified internal model theory to resolve the paradox of active versus passive self-motion sensation.

Science.gov (United States)

Laurens, Jean; Angelaki, Dora E

2017-10-18

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated ('passive') movements. However, these neurons show reduced responses during self-generated ('active') movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements.

An application of the Self Organizing Map Algorithm to computer aided classification of ASTER multispectral data

Directory of Open Access Journals (Sweden)

Ferdinando Giacco

2008-01-01

Full Text Available In this paper we employ the Kohonen’s Self Organizing Map (SOM as a strategy for an unsupervised analysis of ASTER multispectral (MS images. In order to obtain an accurate clusterization we introduce as input for the network, in addition to spectral data, some texture measures extracted from IKONOS images, which gives a contribution to the classification of manmade structures. After clustering of SOM outcomes, we associated each cluster with a major land cover and compared them with prior knowledge of the scene analyzed.

Analysis of mass incident diffusion in Weibo based on self-organization theory

Science.gov (United States)

Pan, Jun; Shen, Huizhang

2018-02-01

This study introduces some theories and methods of self-organization system to the research of the diffusion mechanism of mass incidents in Weibo (Chinese Twitter). Based on the analysis on massive Weibo data from Songjiang battery factory incident happened in 2013 and Jiiangsu Qidong OJI PAPER incident happened in 2012, we find out that diffusion system of mass incident in Weibo satisfies Power Law, Zipf's Law, 1/f noise and Self-similarity. It means this system is the self-organization criticality system and dissemination bursts can be understood as one kind of Self-organization behavior. As the consequence, self-organized criticality (SOC) theory can be used to explain the evolution of mass incident diffusion and people may come up with the right strategy to control such kind of diffusion if they can handle the key ingredients of Self-organization well. Such a study is of practical importance which can offer opportunities for policy makers to have good management on these events.

Self-Organization in Coupled Map Scale-Free Networks

International Nuclear Information System (INIS)

Xiao-Ming, Liang; Zong-Hua, Liu; Hua-Ping, Lü

2008-01-01

We study the self-organization of phase synchronization in coupled map scale-free networks with chaotic logistic map at each node and find that a variety of ordered spatiotemporal patterns emerge spontaneously in a regime of coupling strength. These ordered behaviours will change with the increase of the average links and are robust to both the system size and parameter mismatch. A heuristic theory is given to explain the mechanism of self-organization and to figure out the regime of coupling for the ordered spatiotemporal patterns

Computational disease modeling – fact or fiction?

Directory of Open Access Journals (Sweden)

Stephan Klaas

2009-06-01

Full Text Available Abstract Background Biomedical research is changing due to the rapid accumulation of experimental data at an unprecedented scale, revealing increasing degrees of complexity of biological processes. Life Sciences are facing a transition from a descriptive to a mechanistic approach that reveals principles of cells, cellular networks, organs, and their interactions across several spatial and temporal scales. There are two conceptual traditions in biological computational-modeling. The bottom-up approach emphasizes complex intracellular molecular models and is well represented within the systems biology community. On the other hand, the physics-inspired top-down modeling strategy identifies and selects features of (presumably essential relevance to the phenomena of interest and combines available data in models of modest complexity. Results The workshop, "ESF Exploratory Workshop on Computational disease Modeling", examined the challenges that computational modeling faces in contributing to the understanding and treatment of complex multi-factorial diseases. Participants at the meeting agreed on two general conclusions. First, we identified the critical importance of developing analytical tools for dealing with model and parameter uncertainty. Second, the development of predictive hierarchical models spanning several scales beyond intracellular molecular networks was identified as a major objective. This contrasts with the current focus within the systems biology community on complex molecular modeling. Conclusion During the workshop it became obvious that diverse scientific modeling cultures (from computational neuroscience, theory, data-driven machine-learning approaches, agent-based modeling, network modeling and stochastic-molecular simulations would benefit from intense cross-talk on shared theoretical issues in order to make progress on clinically relevant problems.

Computational neurogenetic modeling

CERN Document Server

Benuskova, Lubica

2010-01-01

Computational Neurogenetic Modeling is a student text, introducing the scope and problems of a new scientific discipline - Computational Neurogenetic Modeling (CNGM). CNGM is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. These include neural network models and their integration with gene network models. This new area brings together knowledge from various scientific disciplines, such as computer and information science, neuroscience and cognitive science, genetics and molecular biol

Self-Organized Criticality and Scaling in Lifetime of Traffic Jams

Science.gov (United States)

Nagatani, Takashi

1995-01-01

The deterministic cellular automaton 184 (the one-dimensional asymmetric simple-exclusion model with parallel dynamics) is extended to take into account injection or extraction of particles. The model presents the traffic flow on a highway with inflow or outflow of cars.Introducing injection or extraction of particles into the asymmetric simple-exclusion model drives the system asymptotically into a steady state exhibiting a self-organized criticality. The typical lifetime of traffic jams scales as \\cong Lν with ν=0.65±0.04. It is shown that the cumulative distribution Nm (L) of lifetimes satisfies the finite-size scaling form Nm (L) \\cong L-1 f(m/Lν).

Self-organization and forcing templates in coastal barrier response to storms

Science.gov (United States)

Lazarus, E.

2015-12-01

When a storm event pushes water up and over a coastal barrier, cross-shore flow transports sediment from the barrier face to the back-barrier environment. This natural physical process is called "overwash", and "washover" is the sedimentary deposit it forms. Overwash and washover support critical coastal habitats, and enable barriers to maintain their height and width relative to rising sea level. On developed barrier coasts, overwash constitutes a natural hazard, which sea-level rise will exacerbate. Overwash is also a prerequisite for barrier breaching and coastal flooding. Predicting occurrence and characteristics of overwash and washover has significant societal value. Hazard models typically assume that pre-storm barrier morphology determines how the barrier changes during a storm. However, classic work has documented the absence of a relationship between pre/post-storm topography in some cases, and has also identified rhythmic patterns in washover alongshore. Previous explanations for these spatial patterns have looked to forcing templates, forms that get imprinted in the barrier shape. An alternative explanation is that washover patterns self-organize, emerging from feedbacks between water flow and sediment transport. Self-organization and forcing templates are often framed as mutually exclusive, but patterns likely form across a continuum of conditions. Here, I use data from a new physical experiment to suggest that spatial patterns in washover can self-organize within the limit of a forcing template of some critical "strength", beyond which pre/post-storm morphologies are highly correlated. Quantifying spatial patterns in washover deposits opens exciting questions regarding coastal morphodynamic response to storms. Measurement of relative template strength over extended spatial (and temporal) scales has the potential to improve hazard assessment and prediction, particularly where template strength is low and self-organization dominates barrier change.

Dynamical model of computation of the rhodium self-powered neutron detector current

International Nuclear Information System (INIS)

Erben, O.; Slovacek, M.; Zerola, L.

1992-01-01

A model is presented for the calculation of the rhodium self-powered neutron detector current in dependence on the neutron flux density during reactor core transients. The total signal consists of a beta emission, prompt, and gamma component and a background signal. The model has been verified by means of experimental data obtained during measurements on the LVR-15 research reactor and at the Dukovany nuclear power plant. (author) 9 figs., 21 refs

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

Energy Technology Data Exchange (ETDEWEB)

Shumilov, V. N., E-mail: vnshumilov@rambler.ru; Syryamkin, V. I., E-mail: maximus70sir@gmail.com; Syryamkin, M. V., E-mail: maximus70sir@gmail.com [National Research Tomsk State University, 634050, Tomsk, Lenin Avenue, 36 (Russian Federation)

2015-11-17

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervous systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

International Nuclear Information System (INIS)

Shumilov, V. N.; Syryamkin, V. I.; Syryamkin, M. V.

2015-01-01

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervous systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of

A Secure, Scalable and Elastic Autonomic Computing Systems Paradigm: Supporting Dynamic Adaptation of Self-* Services from an Autonomic Cloud

Directory of Open Access Journals (Sweden)

Abdul Jaleel

2018-05-01

Full Text Available Autonomic computing embeds self-management features in software systems using external feedback control loops, i.e., autonomic managers. In existing models of autonomic computing, adaptive behaviors are defined at the design time, autonomic managers are statically configured, and the running system has a fixed set of self-* capabilities. An autonomic computing design should accommodate autonomic capability growth by allowing the dynamic configuration of self-* services, but this causes security and integrity issues. A secure, scalable and elastic autonomic computing system (SSE-ACS paradigm is proposed to address the runtime inclusion of autonomic managers, ensuring secure communication between autonomic managers and managed resources. Applying the SSE-ACS concept, a layered approach for the dynamic adaptation of self-* services is presented with an online ‘Autonomic_Cloud’ working as the middleware between Autonomic Managers (offering the self-* services and Autonomic Computing System (requiring the self-* services. A stock trading and forecasting system is used for simulation purposes. The security impact of the SSE-ACS paradigm is verified by testing possible attack cases over the autonomic computing system with single and multiple autonomic managers running on the same and different machines. The common vulnerability scoring system (CVSS metric shows a decrease in the vulnerability severity score from high (8.8 for existing ACS to low (3.9 for SSE-ACS. Autonomic managers are introduced into the system at runtime from the Autonomic_Cloud to test the scalability and elasticity. With elastic AMs, the system optimizes the Central Processing Unit (CPU share resulting in an improved execution time for business logic. For computing systems requiring the continuous support of self-management services, the proposed system achieves a significant improvement in security, scalability, elasticity, autonomic efficiency, and issue resolving time

Self-organization of the critical state in Josephson lattices and granulated superconductors

International Nuclear Information System (INIS)

Ginzburg, S.L.

1994-01-01

A number of models of a Josephson medium and granulated superconductors are studied. It is shown that an important parameter is the quantity V∼j c a 3 /Φ 0 , where j c is the Josephson-current density, a is the granule size, and Φ 0 is the quantum of flux. In the limit V>>1 the continuum approximation is inapplicable. In this case the Josephson medium is transformed into a system in which pinning is realized on elementary loops that incorporate Josephson junctions. Here, nonlinear properties of these junctions obtain. The equations obtained for the currents of the Josephson lattice are identical to the standard formulation in the problem of self-organized criticality, while in granulated superconductors a problem of self-organized criticality with a different symmetry arises-a problem not of sites, but of loop. From the point of view of the critical state in granulated superconductors the concept of self-organized criticality radically changes the entire customary picture. The usual equations of the critical state describe only the average values of the magnetic field in the hydrodynamic approximation. However, it follows from the concept of self-organized criticality that the critical state has an extremely complicated structure, much more complicated than that which follows from the equation of the critical state. In particular, the fluctuations of various quantities in the critical state are much stronger than the ordinary statistical fluctuations, since there are large-scale fluctuations of the currents and fields, with a power-law (scaling) behavior that extends up to scales of the order of the size of the system, as in a turbulent medium. On the other hand, the basic equations in it reflect all the features of pinning - hysteresis and threshold behavior. Therefore, the self-organization of the critical state of a superconductor is a natural realization of this extremely general problem. 15 refs., 4 figs

Large Scale Computing for the Modelling of Whole Brain Connectivity

DEFF Research Database (Denmark)

Albers, Kristoffer Jon

organization of the brain in continuously increasing resolution. From these images, networks of structural and functional connectivity can be constructed. Bayesian stochastic block modelling provides a prominent data-driven approach for uncovering the latent organization, by clustering the networks into groups...... of neurons. Relying on Markov Chain Monte Carlo (MCMC) simulations as the workhorse in Bayesian inference however poses significant computational challenges, especially when modelling networks at the scale and complexity supported by high-resolution whole-brain MRI. In this thesis, we present how to overcome...... these computational limitations and apply Bayesian stochastic block models for un-supervised data-driven clustering of whole-brain connectivity in full image resolution. We implement high-performance software that allows us to efficiently apply stochastic blockmodelling with MCMC sampling on large complex networks...

Comparison of entropy production rates in two different types of self-organized flows: Benard convection and zonal flow

International Nuclear Information System (INIS)

Kawazura, Y.; Yoshida, Z.

2012-01-01

Two different types of self-organizing and sustaining ordered motion in fluids or plasmas--one is a Benard convection (or streamer) and the other is a zonal flow--have been compared by introducing a thermodynamic phenomenological model and evaluating the corresponding entropy production rates (EP). These two systems have different topologies in their equivalent circuits: the Benard convection is modeled by parallel connection of linear and nonlinear conductances, while the zonal flow is modeled by series connection. The ''power supply'' that drives the systems is also a determinant of operating modes. When the energy flux is a control parameter (as in usual plasma experiments), the driver is modeled by a constant-current power supply, and when the temperature difference between two separate boundaries is controlled (as in usual computational studies), the driver is modeled by a constant-voltage power supply. The parallel (series)-connection system tends to minimize (maximize) the total EP when a constant-current power supply drives the system. This minimum/maximum relation flips when a constant-voltage power supply is connected.

A Computer Program for Modeling the Conversion of Organic Waste to Energy

Directory of Open Access Journals (Sweden)

Pragasen Pillay

2011-11-01

Full Text Available This paper presents a tool for the analysis of conversion of organic waste into energy. The tool is a program that uses waste characterization parameters and mass flow rates at each stage of the waste treatment process to predict the given products. The specific waste treatment process analysed in this paper is anaerobic digestion. The different waste treatment stages of the anaerobic digestion process are: conditioning of input waste, secondary treatment, drying of sludge, conditioning of digestate, treatment of digestate, storage of liquid and solid effluent, disposal of liquid and solid effluents, purification, utilization and storage of combustible gas. The program uses mass balance equations to compute the amount of CH4, NH3, CO2 and H2S produced from anaerobic digestion of organic waste, and hence the energy available. Case studies are also presented.

Self-organization phenomena and decaying self-similar state in two-dimensional incompressible viscous fluids

International Nuclear Information System (INIS)

Kondoh, Yoshiomi; Serizawa, Shunsuke; Nakano, Akihiro; Takahashi, Toshiki; Van Dam, James W.

2004-01-01

The final self-similar state of decaying two-dimensional (2D) turbulence in 2D incompressible viscous flow is analytically and numerically investigated for the case with periodic boundaries. It is proved by theoretical analysis and simulations that the sinh-Poisson state cω=-sinh(βψ) is not realized in the dynamical system of interest. It is shown by an eigenfunction spectrum analysis that a sufficient explanation for the self-organization to the decaying self-similar state is the faster energy decay of higher eigenmodes and the energy accumulation to the lowest eigenmode for given boundary conditions due to simultaneous normal and inverse cascading by nonlinear mode couplings. The theoretical prediction is demonstrated to be correct by simulations leading to the lowest eigenmode of {(1,0)+(0,1)} of the dissipative operator for the periodic boundaries. It is also clarified that an important process during nonlinear self-organization is an interchange between the dominant operators, which leads to the final decaying self-similar state

Model for the computation of self-motion in biological systems

Science.gov (United States)

Perrone, John A.

1992-01-01

A technique is presented by which direction- and speed-tuned cells, such as those commonly found in the middle temporal region of the primate brain, can be utilized to analyze the patterns of retinal image motion that are generated during observer movement through the environment. The developed model determines heading by finding the peak response in a population of detectors or neurons each tuned to a particular heading direction. It is suggested that a complex interaction of multiple cell networks is required for the solution of the self-motion problem in the primate brain.

Self-organization of single filaments and diffusive plasmas during a single pulse in dielectric-barrier discharges

International Nuclear Information System (INIS)

Babaeva, Natalia Yu; Kushner, Mark J

2014-01-01

Self-organization of filaments in dielectric-barrier discharges (DBDs) probably has many origins. However, the dominant cause is proposed to be the accumulation of charge on the surfaces of the bounding dielectrics that reinforces successive discharge pulses to occur at the same locations. A secondary cause is the electrostatic repulsion of individual plasma filaments. Self-organization typically develops over many discharge pulses. In this paper, we discuss the results of a computational investigation of plasma filaments in overvoltage DBDs that, under select conditions, display self-organized patterns (SOPs) of plasma density during a single discharge pulse. (Overvoltage refers to the rapid application of a voltage in excess of the quasi-dc breakdown voltage.) The origin of the SOPs is a synergistic relationship between the speed of the surface-ionization waves that propagate along each dielectric and the rate at which avalanche occurs across the gap. For our test conditions, SOPs were not observed at lower voltages and gradually formed at higher voltages. The same conditions that result in SOPs, i.e. the application of an overvoltage, also produce more diffuse discharges. A transition from a single narrow filament to a more diffuse structure was observed as overvoltage was approached. The sensitivity of SOPs to the orientation and permittivity of the bounding dielectrics is discussed. (paper)

Functional self-organization in complex systems

Energy Technology Data Exchange (ETDEWEB)

Fontana, W. (Los Alamos National Lab., NM (USA) Santa Fe Inst., NM (USA))

1990-01-01

A novel approach to functional self-organization is presented. It consists of a universe generated by a formal language that defines objects (=programs), their meaning (=functions), and their interactions (=composition). Results obtained so far are briefly discussed. 17 refs., 5 figs.

SOUNET: Self-Organized Underwater Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Hee-won Kim

2017-02-01

Full Text Available In this paper, we propose an underwater wireless sensor network (UWSN named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR, and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

SOUNET: Self-Organized Underwater Wireless Sensor Network.

Science.gov (United States)

Kim, Hee-Won; Cho, Ho-Shin

2017-02-02

In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

Minimal Self-Models and the Free Energy Principle

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Jakub eLimanowski

2013-09-01

Full Text Available The term "minimal phenomenal selfhood" describes the basic, pre-reflective experience of being a self (Blanke & Metzinger, 2009. Theoretical accounts of the minimal self have long recognized the importance and the ambivalence of the body as both part of the physical world, and the enabling condition for being in this world (Gallagher, 2005; Grafton, 2009. A recent account of minimal phenomenal selfhood (MPS, Metzinger, 2004a centers on the consideration that minimal selfhood emerges as the result of basic self-modeling mechanisms, thereby being founded on pre-reflective bodily processes. The free energy principle (FEP, Friston, 2010 is a novel unified theory of cortical function that builds upon the imperative that self-organizing systems entail hierarchical generative models of the causes of their sensory input, which are optimized by minimizing free energy as an approximation of the log-likelihood of the model. The implementation of the FEP via predictive coding mechanisms and in particular the active inference principle emphasizes the role of embodiment for predictive self-modeling, which has been appreciated in recent publications. In this review, we provide an overview of these conceptions and illustrate thereby the potential power of the FEP in explaining the mechanisms underlying minimal selfhood and its key constituents, multisensory integration, interoception, agency, perspective, and the experience of mineness. We conclude that the conceptualization of MPS can be well mapped onto a hierarchical generative model furnished by the free energy principle and may constitute the basis for higher-level, cognitive forms of self-referral, as well as the understanding of other minds.

Self-organizing expert communities in educational projects

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Gennadiy P. Vinogradov

2018-01-01