Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR.

PubMed

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms.

Usage Automata

NASA Astrophysics Data System (ADS)

Bartoletti, Massimo

Usage automata are an extension of finite stata automata, with some additional features (e.g. parameters and guards) that improve their expressivity. Usage automata are expressive enough to model security requirements of real-world applications; at the same time, they are simple enough to be statically amenable, e.g. they can be model-checked against abstractions of program usages. We study here some foundational aspects of usage automata. In particular, we discuss about their expressive power, and about their effective use in run-time mechanisms for enforcing usage policies.

Cellular automata and its applications in protein bioinformatics.

PubMed

Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen

2011-09-01

With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.

Automata-Based Verification of Temporal Properties on Running Programs

NASA Technical Reports Server (NTRS)

Giannakopoulou, Dimitra; Havelund, Klaus; Lan, Sonie (Technical Monitor)

2001-01-01

This paper presents an approach to checking a running program against its Linear Temporal Logic (LTL) specifications. LTL is a widely used logic for expressing properties of programs viewed as sets of executions. Our approach consists of translating LTL formulae to finite-state automata, which are used as observers of the program behavior. The translation algorithm we propose modifies standard LTL to Buchi automata conversion techniques to generate automata that check finite program traces. The algorithm has been implemented in a tool, which has been integrated with the generic JPaX framework for runtime analysis of Java programs.

Efficient Translation of LTL Formulae into Buchi Automata

NASA Technical Reports Server (NTRS)

Giannakopoulou, Dimitra; Lerda, Flavio

2001-01-01

Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.

QM Automata: A New Class of Restricted Quantum Membrane Automata.

PubMed

Giannakis, Konstantinos; Singh, Alexandros; Kastampolidou, Kalliopi; Papalitsas, Christos; Andronikos, Theodore

2017-01-01

The term "Unconventional Computing" describes the use of non-standard methods and models in computing. It is a recently established field, with many interesting and promising results. In this work we combine notions from quantum computing with aspects of membrane computing to define what we call QM automata. Specifically, we introduce a variant of quantum membrane automata that operate in accordance with the principles of quantum computing. We explore the functionality and capabilities of the QM automata through indicative examples. Finally we suggest future directions for research on QM automata.

Achieving microaggregation for secure statistical databases using fixed-structure partitioning-based learning automata.

PubMed

Fayyoumi, Ebaa; Oommen, B John

2009-10-01

We consider the microaggregation problem (MAP) that involves partitioning a set of individual records in a microdata file into a number of mutually exclusive and exhaustive groups. This problem, which seeks for the best partition of the microdata file, is known to be NP-hard and has been tackled using many heuristic solutions. In this paper, we present the first reported fixed-structure-stochastic-automata-based solution to this problem. The newly proposed method leads to a lower value of the information loss (IL), obtains a better tradeoff between the IL and the disclosure risk (DR) when compared with state-of-the-art methods, and leads to a superior value of the scoring index, which is a criterion involving a combination of the IL and the DR. The scheme has been implemented, tested, and evaluated for different real-life and simulated data sets. The results clearly demonstrate the applicability of learning automata to the MAP and its ability to yield a solution that obtains the best tradeoff between IL and DR when compared with the state of the art.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.

Fuzzy tree automata and syntactic pattern recognition.

PubMed

Lee, E T

1982-04-01

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

A Compositional Translation of Timed Automata with Deadlines to Uppaal Timed Automata

NASA Astrophysics Data System (ADS)

Gómez, Rodolfo

Timed Automata with Deadlines (TAD) are a form of timed automata that admit a more natural representation of urgent actions, with the additional advantage of avoiding the most common form of timelocks. We offer a compositional translation of a practically useful subset of TAD to timed safety automata (the well-known variant of timed automata where time progress conditions are expressed by invariants). More precisely, we translate networks of TAD to the modeling language of Uppaal, a state-of-the-art verification tool for timed automata. We also describe an implementation of this translation, which allows Uppaal to aid the design and analysis of TAD models.

Statistical learning and the challenge of syntax: Beyond finite state automata

NASA Astrophysics Data System (ADS)

Elman, Jeff

2003-10-01

Over the past decade, it has been clear that even very young infants are sensitive to the statistical structure of language input presented to them, and use the distributional regularities to induce simple grammars. But can such statistically-driven learning also explain the acquisition of more complex grammar, particularly when the grammar includes recursion? Recent claims (e.g., Hauser, Chomsky, and Fitch, 2002) have suggested that the answer is no, and that at least recursion must be an innate capacity of the human language acquisition device. In this talk evidence will be presented that indicates that, in fact, statistically-driven learning (embodied in recurrent neural networks) can indeed enable the learning of complex grammatical patterns, including those that involve recursion. When the results are generalized to idealized machines, it is found that the networks are at least equivalent to Push Down Automata. Perhaps more interestingly, with limited and finite resources (such as are presumed to exist in the human brain) these systems demonstrate patterns of performance that resemble those in humans.

A cellular automata approach for modeling surface water runoff

NASA Astrophysics Data System (ADS)

Jozefik, Zoltan; Nanu Frechen, Tobias; Hinz, Christoph; Schmidt, Heiko

2015-04-01

This abstract reports the development and application of a two-dimensional cellular automata based model, which couples the dynamics of overland flow, infiltration processes and surface evolution through sediment transport. The natural hill slopes are represented by their topographic elevation and spatially varying soil properties infiltration rates and surface roughness coefficients. This model allows modeling of Hortonian overland flow and infiltration during complex rainfall events. An advantage of the cellular automata approach over the kinematic wave equations is that wet/dry interfaces that often appear with rainfall overland flows can be accurately captured and are not a source of numerical instabilities. An adaptive explicit time stepping scheme allows for rainfall events to be adequately resolved in time, while large time steps are taken during dry periods to provide for simulation run time efficiency. The time step is constrained by the CFL condition and mass conservation considerations. The spatial discretization is shown to be first-order accurate. For validation purposes, hydrographs for non-infiltrating and infiltrating plates are compared to the kinematic wave analytic solutions and data taken from literature [1,2]. Results show that our cellular automata model quantitatively accurately reproduces hydrograph patterns. However, recent works have showed that even through the hydrograph is satisfyingly reproduced, the flow field within the plot might be inaccurate [3]. For a more stringent validation, we compare steady state velocity, water flux, and water depth fields to rainfall simulation experiments conducted in Thies, Senegal [3]. Comparisons show that our model is able to accurately capture these flow properties. Currently, a sediment transport and deposition module is being implemented and tested. [1] M. Rousseau, O. Cerdan, O. Delestre, F. Dupros, F. James, S. Cordier. Overland flow modeling with the Shallow Water Equation using a well balanced

Weighted Watson-Crick automata

NASA Astrophysics Data System (ADS)

Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

2014-07-01

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.

Mitochondrial fusion through membrane automata.

PubMed

Giannakis, Konstantinos; Andronikos, Theodore

2015-01-01

Studies have shown that malfunctions in mitochondrial processes can be blamed for diseases. However, the mechanism behind these operations is yet not sufficiently clear. In this work we present a novel approach to describe a biomolecular model for mitochondrial fusion using notions from the membrane computing. We use a case study defined in BioAmbient calculus and we show how to translate it in terms of a P automata variant. We combine brane calculi with (mem)brane automata to produce a new scheme capable of describing simple, realistic models. We propose the further use of similar methods and the test of other biomolecular models with the same behaviour.

Cellular-automata-based learning network for pattern recognition

NASA Astrophysics Data System (ADS)

Tzionas, Panagiotis G.; Tsalides, Phillippos G.; Thanailakis, Adonios

1991-11-01

Most classification techniques either adopt an approach based directly on the statistical characteristics of the pattern classes involved, or they transform the patterns in a feature space and try to separate the point clusters in this space. An alternative approach based on memory networks has been presented, its novelty being that it can be implemented in parallel and it utilizes direct features of the patterns rather than statistical characteristics. This study presents a new approach for pattern classification using pseudo 2-D binary cellular automata (CA). This approach resembles the memory network classifier in the sense that it is based on an adaptive knowledge based formed during a training phase, and also in the fact that both methods utilize pattern features that are directly available. The main advantage of this approach is that the sensitivity of the pattern classifier can be controlled. The proposed pattern classifier has been designed using 1.5 micrometers design rules for an N-well CMOS process. Layout has been achieved using SOLO 1400. Binary pseudo 2-D hybrid additive CA (HACA) is described in the second section of this paper. The third section describes the operation of the pattern classifier and the fourth section presents some possible applications. The VLSI implementation of the pattern classifier is presented in the fifth section and, finally, the sixth section draws conclusions from the results obtained.

Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study.

PubMed

Tîrnăucă, Cristina; Montaña, José L; Ontañón, Santiago; González, Avelino J; Pardo, Luis M

2016-06-24

Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent's actions and the environmental conditions during a certain period of time. The goal of Behavioral Cloning (BC) is more ambitious. In this last case, the learner must be able to build a model of the behavior of the agent. In both settings, the only assumption is that the learner has access to a training set that contains instances of observed behavioral traces for each available strategy. This paper studies a machine learning approach based on Probabilistic Finite Automata (PFAs), capable of achieving both the recognition and cloning tasks. We evaluate the performance of PFAs in the context of a simulated learning environment (in this case, a virtual Roomba vacuum cleaner robot), and compare it with a collection of other machine learning approaches.

Towards a voxel-based geographic automata for the simulation of geospatial processes

NASA Astrophysics Data System (ADS)

Jjumba, Anthony; Dragićević, Suzana

2016-07-01

Many geographic processes evolve in a three dimensional space and time continuum. However, when they are represented with the aid of geographic information systems (GIS) or geosimulation models they are modelled in a framework of two-dimensional space with an added temporal component. The objective of this study is to propose the design and implementation of voxel-based automata as a methodological approach for representing spatial processes evolving in the four-dimensional (4D) space-time domain. Similar to geographic automata models which are developed to capture and forecast geospatial processes that change in a two-dimensional spatial framework using cells (raster geospatial data), voxel automata rely on the automata theory and use three-dimensional volumetric units (voxels). Transition rules have been developed to represent various spatial processes which range from the movement of an object in 3D to the diffusion of airborne particles and landslide simulation. In addition, the proposed 4D models demonstrate that complex processes can be readily reproduced from simple transition functions without complex methodological approaches. The voxel-based automata approach provides a unique basis to model geospatial processes in 4D for the purpose of improving representation, analysis and understanding their spatiotemporal dynamics. This study contributes to the advancement of the concepts and framework of 4D GIS.

A Coral Reef Algorithm Based on Learning Automata for the Coverage Control Problem of Heterogeneous Directional Sensor Networks

PubMed Central

Li, Ming; Miao, Chunyan; Leung, Cyril

2015-01-01

Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches. PMID:26690162

A Coral Reef Algorithm Based on Learning Automata for the Coverage Control Problem of Heterogeneous Directional Sensor Networks.

PubMed

Li, Ming; Miao, Chunyan; Leung, Cyril

2015-12-04

Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches.

Automata learning algorithms and processes for providing more complete systems requirements specification by scenario generation, CSP-based syntax-oriented model construction, and R2D2C system requirements transformation

NASA Technical Reports Server (NTRS)

Margaria, Tiziana (Inventor); Hinchey, Michael G. (Inventor); Rouff, Christopher A. (Inventor); Rash, James L. (Inventor); Steffen, Bernard (Inventor)

2010-01-01

Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.

Probabilistic Cellular Automata

PubMed Central

Agapie, Alexandru; Giuclea, Marius

2014-01-01

Abstract Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case—connecting the probability of a configuration in the stationary distribution to its number of zero-one borders—the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557

Probabilistic cellular automata.

PubMed

Agapie, Alexandru; Andreica, Anca; Giuclea, Marius

2014-09-01

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

An Orthogonal Evolutionary Algorithm With Learning Automata for Multiobjective Optimization.

PubMed

Dai, Cai; Wang, Yuping; Ye, Miao; Xue, Xingsi; Liu, Hailin

2016-12-01

Research on multiobjective optimization problems becomes one of the hottest topics of intelligent computation. In order to improve the search efficiency of an evolutionary algorithm and maintain the diversity of solutions, in this paper, the learning automata (LA) is first used for quantization orthogonal crossover (QOX), and a new fitness function based on decomposition is proposed to achieve these two purposes. Based on these, an orthogonal evolutionary algorithm with LA for complex multiobjective optimization problems with continuous variables is proposed. The experimental results show that in continuous states, the proposed algorithm is able to achieve accurate Pareto-optimal sets and wide Pareto-optimal fronts efficiently. Moreover, the comparison with the several existing well-known algorithms: nondominated sorting genetic algorithm II, decomposition-based multiobjective evolutionary algorithm, decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes, multiobjective optimization by LA, and multiobjective immune algorithm with nondominated neighbor-based selection, on 15 multiobjective benchmark problems, shows that the proposed algorithm is able to find more accurate and evenly distributed Pareto-optimal fronts than the compared ones.

Configurable Cellular Automata for Pseudorandom Number Generation

NASA Astrophysics Data System (ADS)

Quieta, Marie Therese; Guan, Sheng-Uei

This paper proposes a generalized structure of cellular automata (CA) — the configurable cellular automata (CoCA). With selected properties from programmable CA (PCA) and controllable CA (CCA), a new approach to cellular automata is developed. In CoCA, the cells are dynamically reconfigured at run-time via a control CA. Reconfiguration of a cell simply means varying the properties of that cell with time. Some examples of properties to be reconfigured are rule selection, boundary condition, and radius. While the objective of this paper is to propose CoCA as a new CA method, the main focus is to design a CoCA that can function as a good pseudorandom number generator (PRNG). As a PRNG, CoCA can be a suitable candidate as it can pass 17 out of 18 Diehard tests with 31 cells. CoCA PRNG's performance based on Diehard test is considered superior over other CA PRNG works. Moreover, CoCA opens new rooms for research not only in the field of random number generation, but in modeling complex systems as well.

Generic framework for mining cellular automata models on protein-folding simulations.

PubMed

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

A stochastic cellular automata model of tautomer equilibria

NASA Astrophysics Data System (ADS)

Bowers, Gregory A.; Seybold, Paul G.

2018-03-01

Many chemical substances, including drugs and biomolecules, exist in solution not as a single species, but as a collection of tautomers and related species. Importantly, each of these species is an independent compoundwith its own specific biochemical and physicochemical properties. The species interconvert in a dynamic and often complicated manner, making modelling the overall species composition difficult. Agent-based cellular automata models are uniquely suited to meet this challenge, allowing the equilibria to be simulated using simple rulesand at the same time capturing the inherent stochasticity of the natural phenomenon. In the present example a stochastic cellular automata model is employed to simulate the tautomer equilibria of 9-anthrone and 9-anthrol in the presence of their common anion. The observed KE of the 9-anthrone ⇌ 9-anthrol tautomerisation along with the measured tautomer pKa values were used to model the equilibria at pH values 4, 7 and 10. At pH 4 and 7, the anthrone comprises >99% of the total species population, while at pH 10the anthrone and the anion each represent just under half of the total population. The advantages of the cellular automata approach over the customary coupled differential equation approach are discussed.

Modeling a student-classroom interaction in a tutorial-like system using learning automata.

PubMed

Oommen, B John; Hashem, M Khaled

2010-02-01

Almost all of the learning paradigms used in machine learning, learning automata (LA), and learning theory, in general, use the philosophy of a Student (learning mechanism) attempting to learn from a teacher. This paradigm has been generalized in a myriad of ways, including the scenario when there are multiple teachers or a hierarchy of mechanisms that collectively achieve the learning. In this paper, we consider a departure from this paradigm by allowing the Student to be a member of a classroom of Students, where, for the most part, we permit each member of the classroom not only to learn from the teacher(s) but also to "extract" information from any of his fellow Students. This paper deals with issues concerning the modeling, decision-making process, and testing of such a scenario within the LA context. The main result that we show is that a weak learner can actually benefit from this capability of utilizing the information that he gets from a superior colleague-if this information transfer is done appropriately. As far as we know, the whole concept of Students learning from both a teacher and from a classroom of Students is novel and unreported in the literature. The proposed Student-classroom interaction has been tested for numerous strategies and for different environments, including the established benchmarks, and the results show that Students can improve their learning by interacting with each other. For example, for some interaction strategies, a weak Student can improve his learning by up to 73% when interacting with a classroom of Students, which includes Students of various capabilities. In these interactions, the Student does not have a priori knowledge of the identity or characteristics of the Students who offer their assistance.

Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach.

PubMed

Kumar, Anand; Ligatti, Jay; Tu, Yi-Cheng

2015-11-01

Privacy and usage restriction issues are important when valuable data are exchanged or acquired by different organizations. Standard access control mechanisms either restrict or completely grant access to valuable data. On the other hand, data obfuscation limits the overall usability and may result in loss of total value. There are no standard policy enforcement mechanisms for data acquired through mutual and copyright agreements. In practice, many different types of policies can be enforced in protecting data privacy. Hence there is the need for an unified framework that encapsulates multiple suites of policies to protect the data. We present our vision of an architecture named security automata model (SAM) to enforce privacy-preserving policies and usage restrictions. SAM analyzes the input queries and their outputs to enforce various policies, liberating data owners from the burden of monitoring data access. SAM allows administrators to specify various policies and enforces them to monitor queries and control the data access. Our goal is to address the problems of data usage control and protection through privacy policies that can be defined, enforced, and integrated with the existing access control mechanisms using SAM. In this paper, we lay out the theoretical foundation of SAM, which is based on an automata named Mandatory Result Automata. We also discuss the major challenges of implementing SAM in a real-world database environment as well as ideas to meet such challenges.

A cognitive approach to classifying perceived behaviors

NASA Astrophysics Data System (ADS)

Benjamin, Dale Paul; Lyons, Damian

2010-04-01

This paper describes our work on integrating distributed, concurrent control in a cognitive architecture, and using it to classify perceived behaviors. We are implementing the Robot Schemas (RS) language in Soar. RS is a CSP-type programming language for robotics that controls a hierarchy of concurrently executing schemas. The behavior of every RS schema is defined using port automata. This provides precision to the semantics and also a constructive means of reasoning about the behavior and meaning of schemas. Our implementation uses Soar operators to build, instantiate and connect port automata as needed. Our approach is to use comprehension through generation (similar to NLSoar) to search for ways to construct port automata that model perceived behaviors. The generality of RS permits us to model dynamic, concurrent behaviors. A virtual world (Ogre) is used to test the accuracy of these automata. Soar's chunking mechanism is used to generalize and save these automata. In this way, the robot learns to recognize new behaviors.

Evaluating a Novel Cellular Automata-Based Distributed Power Management Approach for Mobile Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali

According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach

PubMed Central

2014-01-01

Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the

Stimulus-Response Theory of Finite Automata, Technical Report No. 133.

ERIC Educational Resources Information Center

Suppes, Patrick

The central aim of this paper and its projected successors is to prove in detail that stimulus-response theory, or at least a mathematically precise version, can give an account of the learning of many phrase-structure grammars. Section 2 is concerned with standard notions of finite and probabilistic automata. An automaton is defined as a device…

Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach

PubMed Central

Kumar, Anand; Ligatti, Jay; Tu, Yi-Cheng

2015-01-01

Privacy and usage restriction issues are important when valuable data are exchanged or acquired by different organizations. Standard access control mechanisms either restrict or completely grant access to valuable data. On the other hand, data obfuscation limits the overall usability and may result in loss of total value. There are no standard policy enforcement mechanisms for data acquired through mutual and copyright agreements. In practice, many different types of policies can be enforced in protecting data privacy. Hence there is the need for an unified framework that encapsulates multiple suites of policies to protect the data. We present our vision of an architecture named security automata model (SAM) to enforce privacy-preserving policies and usage restrictions. SAM analyzes the input queries and their outputs to enforce various policies, liberating data owners from the burden of monitoring data access. SAM allows administrators to specify various policies and enforces them to monitor queries and control the data access. Our goal is to address the problems of data usage control and protection through privacy policies that can be defined, enforced, and integrated with the existing access control mechanisms using SAM. In this paper, we lay out the theoretical foundation of SAM, which is based on an automata named Mandatory Result Automata. We also discuss the major challenges of implementing SAM in a real-world database environment as well as ideas to meet such challenges. PMID:26997936

Iterons, fractals and computations of automata

NASA Astrophysics Data System (ADS)

Siwak, Paweł

1999-03-01

Processing of strings by some automata, when viewed on space-time (ST) diagrams, reveals characteristic soliton-like coherent periodic objects. They are inherently associated with iterations of automata mappings thus we call them the iterons. In the paper we present two classes of one-dimensional iterons: particles and filtrons. The particles are typical for parallel (cellular) processing, while filtrons, introduced in (32) are specific for serial processing of strings. In general, the images of iterated automata mappings exhibit not only coherent entities but also the fractals, and quasi-periodic and chaotic dynamics. We show typical images of such computations: fractals, multiplication by a number, and addition of binary numbers defined by a Turing machine. Then, the particles are presented as iterons generated by cellular automata in three computations: B/U code conversion (13, 29), majority classification (9), and in discrete version of the FPU (Fermi-Pasta-Ulam) dynamics (7, 23). We disclose particles by a technique of combinational recoding of ST diagrams (as opposed to sequential recoding). Subsequently, we recall the recursive filters based on FCA (filter cellular automata) window operators, and considered by Park (26), Ablowitz (1), Fokas (11), Fuchssteiner (12), Bruschi (5) and Jiang (20). We present the automata equivalents to these filters (33). Some of them belong to the class of filter automata introduced in (30). We also define and illustrate some properties of filtrons. Contrary to particles, the filtrons interact nonlocally in the sense that distant symbols may influence one another. Thus their interactions are very unusual. Some examples have been given in (32). Here we show new examples of filtron phenomena: multifiltron solitonic collisions, attracting and repelling filtrons, trapped bouncing filtrons (which behave like a resonance cavity) and quasi filtrons.

Algebraic Systems and Pushdown Automata

NASA Astrophysics Data System (ADS)

Petre, Ion; Salomaa, Arto

We concentrate in this chapter on the core aspects of algebraic series, pushdown automata, and their relation to formal languages. We choose to follow here a presentation of their theory based on the concept of properness. We introduce in Sect. 2 some auxiliary notions and results needed throughout the chapter, in particular the notions of discrete convergence in semirings and C-cycle free infinite matrices. In Sect. 3 we introduce the algebraic power series in terms of algebraic systems of equations. We focus on interconnections with context-free grammars and on normal forms. We then conclude the section with a presentation of the theorems of Shamir and Chomsky-Schützenberger. We discuss in Sect. 4 the algebraic and the regulated rational transductions, as well as some representation results related to them. Section 5 is dedicated to pushdown automata and focuses on the interconnections with classical (non-weighted) pushdown automata and on the interconnections with algebraic systems. We then conclude the chapter with a brief discussion of some of the other topics related to algebraic systems and pushdown automata.

Inferring the Limit Behavior of Some Elementary Cellular Automata

NASA Astrophysics Data System (ADS)

Ruivo, Eurico L. P.; de Oliveira, Pedro P. B.

Cellular automata locally define dynamical systems, discrete in space, time and in the state variables, capable of displaying arbitrarily complex global emergent behavior. One core question in the study of cellular automata refers to their limit behavior, that is, to the global dynamical features in an infinite time evolution. Previous works have shown that for finite time evolutions, the dynamics of one-dimensional cellular automata can be described by regular languages and, therefore, by finite automata. Such studies have shown the existence of growth patterns in the evolution of such finite automata for some elementary cellular automata rules and also inferred the limit behavior of such rules based upon the growth patterns; however, the results on the limit behavior were obtained manually, by direct inspection of the structures that arise during the time evolution. Here we present the formalization of an automatic method to compute such structures. Based on this, the rules of the elementary cellular automata space were classified according to the existence of a growth pattern in their finite automata. Also, we present a method to infer the limit graph of some elementary cellular automata rules, derived from the analysis of the regular expressions that describe their behavior in finite time. Finally, we analyze some attractors of two rules for which we could not compute the whole limit set.

Data Automata in Scala

NASA Technical Reports Server (NTRS)

Havelund, Klaus

2014-01-01

The field of runtime verification has during the last decade seen a multitude of systems for monitoring event sequences (traces) emitted by a running system. The objective is to ensure correctness of a system by checking its execution traces against formal specifications representing requirements. A special challenge is data parameterized events, where monitors have to keep track of the combination of control states as well as data constraints, relating events and the data they carry across time points. This poses a challenge wrt. efficiency of monitors, as well as expressiveness of logics. Data automata is a form of automata where states are parameterized with data, supporting monitoring of data parameterized events. We describe the full details of a very simple API in the Scala programming language, an internal DSL (Domain-Specific Language), implementing data automata. The small implementation suggests a design pattern. Data automata allow transition conditions to refer to other states than the source state, and allow target states of transitions to be inlined, offering a temporal logic flavored notation. An embedding of a logic in a high-level language like Scala in addition allows monitors to be programmed using all of Scala's language constructs, offering the full flexibility of a programming language. The framework is demonstrated on an XML processing scenario previously addressed in related work.

Evolution of cellular automata with memory: The Density Classification Task.

PubMed

Stone, Christopher; Bull, Larry

2009-08-01

The Density Classification Task is a well known test problem for two-state discrete dynamical systems. For many years researchers have used a variety of evolutionary computation approaches to evolve solutions to this problem. In this paper, we investigate the evolvability of solutions when the underlying Cellular Automaton is augmented with a type of memory based on the Least Mean Square algorithm. To obtain high performance solutions using a simple non-hybrid genetic algorithm, we design a novel representation based on the ternary representation used for Learning Classifier Systems. The new representation is found able to produce superior performance to the bit string traditionally used for representing Cellular automata. Moreover, memory is shown to improve evolvability of solutions and appropriate memory settings are able to be evolved as a component part of these solutions.

Nonsynchronous updating in the multiverse of cellular automata

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Kinouchi, Osame

2015-04-01

In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.

Nonsynchronous updating in the multiverse of cellular automata.

PubMed

Reia, Sandro M; Kinouchi, Osame

2015-04-01

In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.

Predictability in Cellular Automata

PubMed Central

Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius

2014-01-01

Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case. PMID:25271778

Predictability in cellular automata.

PubMed

Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius

2014-01-01

Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case.

Modeling biological pathway dynamics with timed automata.

PubMed

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Consequences of Landscape Fragmentation on Lyme Disease Risk: A Cellular Automata Approach

PubMed Central

Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O.

2012-01-01

The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial

Cellular Automata Generalized To An Inferential System

NASA Astrophysics Data System (ADS)

Blower, David J.

2007-11-01

Stephen Wolfram popularized elementary one-dimensional cellular automata in his book, A New Kind of Science. Among many remarkable things, he proved that one of these cellular automata was a Universal Turing Machine. Such cellular automata can be interpreted in a different way by viewing them within the context of the formal manipulation rules from probability theory. Bayes's Theorem is the most famous of such formal rules. As a prelude, we recapitulate Jaynes's presentation of how probability theory generalizes classical logic using modus ponens as the canonical example. We emphasize the important conceptual standing of Boolean Algebra for the formal rules of probability manipulation and give an alternative demonstration augmenting and complementing Jaynes's derivation. We show the complementary roles played in arguments of this kind by Bayes's Theorem and joint probability tables. A good explanation for all of this is afforded by the expansion of any particular logic function via the disjunctive normal form (DNF). The DNF expansion is a useful heuristic emphasized in this exposition because such expansions point out where relevant 0s should be placed in the joint probability tables for logic functions involving any number of variables. It then becomes a straightforward exercise to rely on Boolean Algebra, Bayes's Theorem, and joint probability tables in extrapolating to Wolfram's cellular automata. Cellular automata are seen as purely deductive systems, just like classical logic, which probability theory is then able to generalize. Thus, any uncertainties which we might like to introduce into the discussion about cellular automata are handled with ease via the familiar inferential path. Most importantly, the difficult problem of predicting what cellular automata will do in the far future is treated like any inferential prediction problem.

Observability of Automata Networks: Fixed and Switching Cases.

PubMed

Li, Rui; Hong, Yiguang; Wang, Xingyuan

2018-04-01

Automata networks are a class of fully discrete dynamical systems, which have received considerable interest in various different areas. This brief addresses the observability of automata networks and switched automata networks in a unified framework, and proposes simple necessary and sufficient conditions for observability. The results are achieved by employing methods from symbolic computation, and are suited for implementation using computer algebra systems. Several examples are presented to demonstrate the application of the results.

Astrobiological complexity with probabilistic cellular automata.

PubMed

Vukotić, Branislav; Ćirković, Milan M

2012-08-01

The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.

Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios

NASA Astrophysics Data System (ADS)

Avolio, MV; Di Gregorio, Salvatore; Mantovani, Franco; Pasuto, Alessandro; Rongo, Rocco; Silvano, Sandro; Spataro, William

Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.

Maximizing the Adjacent Possible in Automata Chemistries.

PubMed

Hickinbotham, Simon; Clark, Edward; Nellis, Adam; Stepney, Susan; Clarke, Tim; Young, Peter

2016-01-01

Automata chemistries are good vehicles for experimentation in open-ended evolution, but they are by necessity complex systems whose low-level properties require careful design. To aid the process of designing automata chemistries, we develop an abstract model that classifies the features of a chemistry from a physical (bottom up) perspective and from a biological (top down) perspective. There are two levels: things that can evolve, and things that cannot. We equate the evolving level with biology and the non-evolving level with physics. We design our initial organisms in the biology, so they can evolve. We design the physics to facilitate evolvable biologies. This architecture leads to a set of design principles that should be observed when creating an instantiation of the architecture. These principles are Everything Evolves, Everything's Soft, and Everything Dies. To evaluate these ideas, we present experiments in the recently developed Stringmol automata chemistry. We examine the properties of Stringmol with respect to the principles, and so demonstrate the usefulness of the principles in designing automata chemistries.

Scalable asynchronous execution of cellular automata

NASA Astrophysics Data System (ADS)

Folino, Gianluigi; Giordano, Andrea; Mastroianni, Carlo

2016-10-01

The performance and scalability of cellular automata, when executed on parallel/distributed machines, are limited by the necessity of synchronizing all the nodes at each time step, i.e., a node can execute only after the execution of the previous step at all the other nodes. However, these synchronization requirements can be relaxed: a node can execute one step after synchronizing only with the adjacent nodes. In this fashion, different nodes can execute different time steps. This can be a notable advantageous in many novel and increasingly popular applications of cellular automata, such as smart city applications, simulation of natural phenomena, etc., in which the execution times can be different and variable, due to the heterogeneity of machines and/or data and/or executed functions. Indeed, a longer execution time at a node does not slow down the execution at all the other nodes but only at the neighboring nodes. This is particularly advantageous when the nodes that act as bottlenecks vary during the application execution. The goal of the paper is to analyze the benefits that can be achieved with the described asynchronous implementation of cellular automata, when compared to the classical all-to-all synchronization pattern. The performance and scalability have been evaluated through a Petri net model, as this model is very useful to represent the synchronization barrier among nodes. We examined the usual case in which the territory is partitioned into a number of regions, and the computation associated with a region is assigned to a computing node. We considered both the cases of mono-dimensional and two-dimensional partitioning. The results show that the advantage obtained through the asynchronous execution, when compared to the all-to-all synchronous approach is notable, and it can be as large as 90% in terms of speedup.

Random early detection for congestion avoidance in wired networks: a discretized pursuit learning-automata-like solution.

PubMed

Misra, Sudip; Oommen, B John; Yanamandra, Sreekeerthy; Obaidat, Mohammad S

2010-02-01

In this paper, we present a learning-automata-like The reason why the mechanism is not a pure LA, but rather why it yet mimics one, will be clarified in the body of this paper. (LAL) mechanism for congestion avoidance in wired networks. Our algorithm, named as LAL Random Early Detection (LALRED), is founded on the principles of the operations of existing RED congestion-avoidance mechanisms, augmented with a LAL philosophy. The primary objective of LALRED is to optimize the value of the average size of the queue used for congestion avoidance and to consequently reduce the total loss of packets at the queue. We attempt to achieve this by stationing a LAL algorithm at the gateways and by discretizing the probabilities of the corresponding actions of the congestion-avoidance algorithm. At every time instant, the LAL scheme, in turn, chooses the action that possesses the maximal ratio between the number of times the chosen action is rewarded and the number of times that it has been chosen. In LALRED, we simultaneously increase the likelihood of the scheme converging to the action, which minimizes the number of packet drops at the gateway. Our approach helps to improve the performance of congestion avoidance by adaptively minimizing the queue-loss rate and the average queue size. Simulation results obtained using NS2 establish the improved performance of LALRED over the traditional RED methods which were chosen as the benchmarks for performance comparison purposes.

Failover in Cellular Automata

NASA Astrophysics Data System (ADS)

Kumar, Shailesh; Rao, Shrisha

This paper studies a phenomenon called failover, and shows that this phenomenon (in particular, stateless failover) can be modeled by Game of Life cellular automata. This is the first time that this sophisticated real-life system behavior has been modeled in abstract terms. A cellular automata (CA) configuration is constructed that exhibits emergent failover. The configuration is based on standard Game of Life rules. Gliders and glider-guns form the core messaging structure in the configuration. The blinker is represented as the basic computational unit, and it is shown how it can be recreated in case of a failure. Stateless failover using the primary-backup mechanism is demonstrated. The details of the CA components used in the configuration and its working are described, and a simulation of the complete configuration is also presented.

Phase transitions in coupled map lattices and in associated probabilistic cellular automata.

PubMed

Just, Wolfram

2006-10-01

Analytical tools are applied to investigate piecewise linear coupled map lattices in terms of probabilistic cellular automata. The so-called disorder condition of probabilistic cellular automata is closely related with attracting sets in coupled map lattices. The importance of this condition for the suppression of phase transitions is illustrated by spatially one-dimensional systems. Invariant densities and temporal correlations are calculated explicitly. Ising type phase transitions are found for one-dimensional coupled map lattices acting on repelling sets and for a spatially two-dimensional Miller-Huse-like system with stable long time dynamics. Critical exponents are calculated within a finite size scaling approach. The relevance of detailed balance of the resulting probabilistic cellular automaton for the critical behavior is pointed out.

Asynchronous adaptive time step in quantitative cellular automata modeling

PubMed Central

Zhu, Hao; Pang, Peter YH; Sun, Yan; Dhar, Pawan

2004-01-01

Background The behaviors of cells in metazoans are context dependent, thus large-scale multi-cellular modeling is often necessary, for which cellular automata are natural candidates. Two related issues are involved in cellular automata based multi-cellular modeling: how to introduce differential equation based quantitative computing to precisely describe cellular activity, and upon it, how to solve the heavy time consumption issue in simulation. Results Based on a modified, language based cellular automata system we extended that allows ordinary differential equations in models, we introduce a method implementing asynchronous adaptive time step in simulation that can considerably improve efficiency yet without a significant sacrifice of accuracy. An average speedup rate of 4–5 is achieved in the given example. Conclusions Strategies for reducing time consumption in simulation are indispensable for large-scale, quantitative multi-cellular models, because even a small 100 × 100 × 100 tissue slab contains one million cells. Distributed and adaptive time step is a practical solution in cellular automata environment. PMID:15222901

Canalization and Control in Automata Networks: Body Segmentation in Drosophila melanogaster

PubMed Central

Marques-Pita, Manuel; Rocha, Luis M.

2013-01-01

We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics – a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity – with the ultimate goal of explaining how do cells and tissues ‘compute’. PMID:23520449

Canalization and control in automata networks: body segmentation in Drosophila melanogaster.

PubMed

Marques-Pita, Manuel; Rocha, Luis M

2013-01-01

We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics--a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity--with the ultimate goal of explaining how do cells and tissues 'compute'.

Cellular Automata Simulation for Wealth Distribution

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching

2009-08-01

Wealth distribution of a country is a complicate system. A model, which is based on the Epstein & Axtell's "Sugars cape" model, is presented in Netlogo. The model considers the income, age, working opportunity and salary as control variables. There are still other variables should be considered while an artificial society is established. In this study, a more complicate cellular automata model for wealth distribution model is proposed. The effects of social welfare, tax, economical investment and inheritance are considered and simulated. According to the cellular automata simulation for wealth distribution, we will have a deep insight of financial policy of the government.

Free Quantum Field Theory from Quantum Cellular Automata

NASA Astrophysics Data System (ADS)

Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro

2015-10-01

After leading to a new axiomatic derivation of quantum theory (see D'Ariano et al. in Found Phys, 2015), the new informational paradigm is entering the domain of quantum field theory, suggesting a quantum automata framework that can be regarded as an extension of quantum field theory to including an hypothetical Planck scale, and with the usual quantum field theory recovered in the relativistic limit of small wave-vectors. Being derived from simple principles (linearity, unitarity, locality, homogeneity, isotropy, and minimality of dimension), the automata theory is quantum ab-initio, and does not assume Lorentz covariance and mechanical notions. Being discrete it can describe localized states and measurements (unmanageable by quantum field theory), solving all the issues plaguing field theory originated from the continuum. These features make the theory an ideal framework for quantum gravity, with relativistic covariance and space-time emergent solely from the interactions, and not assumed a priori. The paper presents a synthetic derivation of the automata theory, showing how the principles lead to a description in terms of a quantum automaton over a Cayley graph of a group. Restricting to Abelian groups we show how the automata recover the Weyl, Dirac and Maxwell dynamics in the relativistic limit. We conclude with some new routes about the more general scenario of non-Abelian Cayley graphs. The phenomenology arising from the automata theory in the ultra-relativistic domain and the analysis of corresponding distorted Lorentz covariance is reviewed in Bisio et al. (Found Phys 2015, in this same issue).

Viewing hybrid systems as products of control systems and automata

NASA Technical Reports Server (NTRS)

Grossman, R. L.; Larson, R. G.

1992-01-01

The purpose of this note is to show how hybrid systems may be modeled as products of nonlinear control systems and finite state automata. By a hybrid system, we mean a network of consisting of continuous, nonlinear control system connected to discrete, finite state automata. Our point of view is that the automata switches between the control systems, and that this switching is a function of the discrete input symbols or letters that it receives. We show how a nonlinear control system may be viewed as a pair consisting of a bialgebra of operators coding the dynamics, and an algebra of observations coding the state space. We also show that a finite automata has a similar representation. A hybrid system is then modeled by taking suitable products of the bialgebras coding the dynamics and the observation algebras coding the state spaces.

Using Mobile TLA as a Logic for Dynamic I/O Automata

NASA Astrophysics Data System (ADS)

Kapus, Tatjana

Input/Output (I/O) automata and the Temporal Logic of Actions (TLA) are two well-known techniques for the specification and verification of concurrent systems. Over the past few years, they have been extended to the so-called dynamic I/O automata and, respectively, Mobile TLA (MTLA) in order to be more appropriate for mobile agent systems. Dynamic I/O automata is just a mathematical model, whereas MTLA is a logic with a formally defined language. In this paper, therefore, we investigate how MTLA could be used as a formal language for the specification of dynamic I/O automata. We do this by writing an MTLA specification of a travel agent system which has been specified semi-formally in the literature on that model. In this specification, we deal with always existing agents as well as with an initially unknown number of dynamically created agents, with mobile and non-mobile agents, with I/O-automata-style communication, and with the changing communication capabilities of mobile agents. We have previously written a TLA specification of this system. This paper shows that an MTLA specification of such a system can be more elegant and faithful to the dynamic I/O automata definition because the agent existence and location can be expressed directly by using agent and location names instead of special variables as in TLA. It also shows how the reuse of names for dynamically created and destroyed agents within the dynamic I/O automata framework can be specified in MTLA.

A full computation-relevant topological dynamics classification of elementary cellular automata.

PubMed

Schüle, Martin; Stoop, Ruedi

2012-12-01

Cellular automata are both computational and dynamical systems. We give a complete classification of the dynamic behaviour of elementary cellular automata (ECA) in terms of fundamental dynamic system notions such as sensitivity and chaoticity. The "complex" ECA emerge to be sensitive, but not chaotic and not eventually weakly periodic. Based on this classification, we conjecture that elementary cellular automata capable of carrying out complex computations, such as needed for Turing-universality, are at the "edge of chaos."

Lempel-Ziv complexity analysis of one dimensional cellular automata.

PubMed

Estevez-Rams, E; Lora-Serrano, R; Nunes, C A J; Aragón-Fernández, B

2015-12-01

Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.

Lempel-Ziv complexity analysis of one dimensional cellular automata

NASA Astrophysics Data System (ADS)

Estevez-Rams, E.; Lora-Serrano, R.; Nunes, C. A. J.; Aragón-Fernández, B.

2015-12-01

Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.

Cellular automata approach for the dynamics of HIV infection under antiretroviral therapies: The role of the virus diffusion

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; de Figueirêdo, Pedro Hugo; Coutinho, Sérgio

2013-10-01

We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell-cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.

Cellular Automata with Anticipation: Examples and Presumable Applications

NASA Astrophysics Data System (ADS)

Krushinsky, Dmitry; Makarenko, Alexander

2010-11-01

One of the most prospective new methodologies for modelling is the so-called cellular automata (CA) approach. According to this paradigm, the models are built from simple elements connected into regular structures with local interaction between neighbours. The patterns of connections usually have a simple geometry (lattices). As one of the classical examples of CA we mention the game `Life' by J. Conway. This paper presents two examples of CA with anticipation property. These examples include a modification of the game `Life' and a cellular model of crowd movement.

Probabilistic arithmetic automata and their applications.

PubMed

Marschall, Tobias; Herms, Inke; Kaltenbach, Hans-Michael; Rahmann, Sven

2012-01-01

We present a comprehensive review on probabilistic arithmetic automata (PAAs), a general model to describe chains of operations whose operands depend on chance, along with two algorithms to numerically compute the distribution of the results of such probabilistic calculations. PAAs provide a unifying framework to approach many problems arising in computational biology and elsewhere. We present five different applications, namely 1) pattern matching statistics on random texts, including the computation of the distribution of occurrence counts, waiting times, and clump sizes under hidden Markov background models; 2) exact analysis of window-based pattern matching algorithms; 3) sensitivity of filtration seeds used to detect candidate sequence alignments; 4) length and mass statistics of peptide fragments resulting from enzymatic cleavage reactions; and 5) read length statistics of 454 and IonTorrent sequencing reads. The diversity of these applications indicates the flexibility and unifying character of the presented framework. While the construction of a PAA depends on the particular application, we single out a frequently applicable construction method: We introduce deterministic arithmetic automata (DAAs) to model deterministic calculations on sequences, and demonstrate how to construct a PAA from a given DAA and a finite-memory random text model. This procedure is used for all five discussed applications and greatly simplifies the construction of PAAs. Implementations are available as part of the MoSDi package. Its application programming interface facilitates the rapid development of new applications based on the PAA framework.

Minimal entropy approximation for cellular automata

NASA Astrophysics Data System (ADS)

Fukś, Henryk

2014-02-01

We present a method for the construction of approximate orbits of measures under the action of cellular automata which is complementary to the local structure theory. The local structure theory is based on the idea of Bayesian extension, that is, construction of a probability measure consistent with given block probabilities and maximizing entropy. If instead of maximizing entropy one minimizes it, one can develop another method for the construction of approximate orbits, at the heart of which is the iteration of finite-dimensional maps, called minimal entropy maps. We present numerical evidence that the minimal entropy approximation sometimes outperforms the local structure theory in characterizing the properties of cellular automata. The density response curve for elementary CA rule 26 is used to illustrate this claim.

A cryptographic hash function based on chaotic network automata

NASA Astrophysics Data System (ADS)

Machicao, Jeaneth; Bruno, Odemir M.

2017-12-01

Chaos theory has been used to develop several cryptographic methods relying on the pseudo-random properties extracted from simple nonlinear systems such as cellular automata (CA). Cryptographic hash functions (CHF) are commonly used to check data integrity. CHF “compress” arbitrary long messages (input) into much smaller representations called hash values or message digest (output), designed to prevent the ability to reverse the hash values into the original message. This paper proposes a chaos-based CHF inspired on an encryption method based on chaotic CA rule B1357-S2468. Here, we propose an hybrid model that combines CA and networks, called network automata (CNA), whose chaotic spatio-temporal outputs are used to compute a hash value. Following the Merkle and Damgård model of construction, a portion of the message is entered as the initial condition of the network automata, so that the rest parts of messages are iteratively entered to perturb the system. The chaotic network automata shuffles the message using flexible control parameters, so that the generated hash value is highly sensitive to the message. As demonstrated in our experiments, the proposed model has excellent pseudo-randomness and sensitivity properties with acceptable performance when compared to conventional hash functions.

Quantum cellular automata and free quantum field theory

NASA Astrophysics Data System (ADS)

D'Ariano, Giacomo Mauro; Perinotti, Paolo

2017-02-01

In a series of recent papers [1-4] it has been shown how free quantum field theory can be derived without using mechanical primitives (including space-time, special relativity, quantization rules, etc.), but only considering the easiest quantum algorithm encompassing a countable set of quantum systems whose network of interactions satisfies the simple principles of unitarity, homogeneity, locality, and isotropy. This has opened the route to extending the axiomatic information-theoretic derivation of the quantum theory of abstract systems [5, 6] to include quantum field theory. The inherent discrete nature of the informational axiomatization leads to an extension of quantum field theory to a quantum cellular automata theory, where the usual field theory is recovered in a regime where the discrete structure of the automata cannot be probed. A simple heuristic argument sets the scale of discreteness to the Planck scale, and the customary physical regime where discreteness is not visible is the relativistic one of small wavevectors. In this paper we provide a thorough derivation from principles that in the most general case the graph of the quantum cellular automaton is the Cayley graph of a finitely presented group, and showing how for the case corresponding to Euclidean emergent space (where the group resorts to an Abelian one) the automata leads to Weyl, Dirac and Maxwell field dynamics in the relativistic limit. We conclude with some perspectives towards the more general scenario of non-linear automata for interacting quantum field theory.

A Decomposition Theorem for Finite Automata.

ERIC Educational Resources Information Center

Santa Coloma, Teresa L.; Tucci, Ralph P.

1990-01-01

Described is automata theory which is a branch of theoretical computer science. A decomposition theorem is presented that is easier than the Krohn-Rhodes theorem. Included are the definitions, the theorem, and a proof. (KR)

Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment

PubMed Central

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Context Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. Objective This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. Method The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. Results The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. Conclusion The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns. PMID:25243670

Design pattern mining using distributed learning automata and DNA sequence alignment.

PubMed

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

The 3-dimensional cellular automata for HIV infection

NASA Astrophysics Data System (ADS)

Mo, Youbin; Ren, Bin; Yang, Wencao; Shuai, Jianwei

2014-04-01

The HIV infection dynamics is discussed in detail with a 3-dimensional cellular automata model in this paper. The model can reproduce the three-phase development, i.e., the acute period, the asymptotic period and the AIDS period, observed in the HIV-infected patients in a clinic. We show that the 3D HIV model performs a better robustness on the model parameters than the 2D cellular automata. Furthermore, we reveal that the occurrence of a perpetual source to successively generate infectious waves to spread to the whole system drives the model from the asymptotic state to the AIDS state.

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

USGS Publications Warehouse

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

Cellular Automata and the Humanities.

ERIC Educational Resources Information Center

Gallo, Ernest

1994-01-01

The use of cellular automata to analyze several pre-Socratic hypotheses about the evolution of the physical world is discussed. These hypotheses combine characteristics of both rigorous and metaphoric language. Since the computer demands explicit instructions for each step in the evolution of the automaton, such models can reveal conceptual…

Multilane Traffic Flow Modeling Using Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Chechina, Antonina; Churbanova, Natalia; Trapeznikova, Marina

2018-02-01

The paper deals with the mathematical modeling of traffic flows on urban road networks using microscopic approach. The model is based on the cellular automata theory and presents a generalization of the Nagel-Schreckenberg model to a multilane case. The created program package allows to simulate traffic on various types of road fragments (T or X type intersection, strait road elements, etc.) and on road networks that consist of these elements. Besides that, it allows to predict the consequences of various decisions regarding road infrastructure changes, such as: number of lanes increasing/decreasing, putting new traffic lights into operation, building new roads, entrances/exits, road junctions.

Unary probabilistic and quantum automata on promise problems

NASA Astrophysics Data System (ADS)

Gainutdinova, Aida; Yakaryılmaz, Abuzer

2018-02-01

We continue the systematic investigation of probabilistic and quantum finite automata (PFAs and QFAs) on promise problems by focusing on unary languages. We show that bounded-error unary QFAs are more powerful than bounded-error unary PFAs, and, contrary to the binary language case, the computational power of Las-Vegas QFAs and bounded-error PFAs is equivalent to the computational power of deterministic finite automata (DFAs). Then, we present a new family of unary promise problems defined with two parameters such that when fixing one parameter QFAs can be exponentially more succinct than PFAs and when fixing the other parameter PFAs can be exponentially more succinct than DFAs.

Towards Time Automata and Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Hutzler, G.; Klaudel, H.; Wang, D. Y.

2004-01-01

The design of reactive systems must comply with logical correctness (the system does what it is supposed to do) and timeliness (the system has to satisfy a set of temporal constraints) criteria. In this paper, we propose a global approach for the design of adaptive reactive systems, i.e., systems that dynamically adapt their architecture depending on the context. We use the timed automata formalism for the design of the agents' behavior. This allows evaluating beforehand the properties of the system (regarding logical correctness and timeliness), thanks to model-checking and simulation techniques. This model is enhanced with tools that we developed for the automatic generation of code, allowing to produce very quickly a running multi-agent prototype satisfying the properties of the model.

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

PubMed Central

Liu, Aiming; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-01-01

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems. PMID:29117100

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata.

PubMed

Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-11-08

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.

Cellular automata model for human articular chondrocytes migration, proliferation and cell death: An in vitro validation.

PubMed

Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A

2017-01-01

Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.

Molecular Magnetic Quantum Cellular Automata

DTIC Science & Technology

2004-06-01

Folting K, Gatteschi D, Christou G, Hendrickson D N 1993a, High-Spin Molecules - [Mn12O12(O2CR)16(H2O)4], J. Am. Chem. Soc. 115 1804 Sessoli R... Gatteschi D, Caneschi A and Novak M A 1993b, Magnetic bistability in a metal-ion cluster, Nature 365 141 Twamely J 2003, Quantum-cellular-automata

A novel image encryption algorithm using chaos and reversible cellular automata

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Luan, Dapeng

2013-11-01

In this paper, a novel image encryption scheme is proposed based on reversible cellular automata (RCA) combining chaos. In this algorithm, an intertwining logistic map with complex behavior and periodic boundary reversible cellular automata are used. We split each pixel of image into units of 4 bits, then adopt pseudorandom key stream generated by the intertwining logistic map to permute these units in confusion stage. And in diffusion stage, two-dimensional reversible cellular automata which are discrete dynamical systems are applied to iterate many rounds to achieve diffusion on bit-level, in which we only consider the higher 4 bits in a pixel because the higher 4 bits carry almost the information of an image. Theoretical analysis and experimental results demonstrate the proposed algorithm achieves a high security level and processes good performance against common attacks like differential attack and statistical attack. This algorithm belongs to the class of symmetric systems.

Computing aggregate properties of preimages for 2D cellular automata.

PubMed

Beer, Randall D

2017-11-01

Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm-incremental aggregation-that can compute aggregate properties of the set of precursors exponentially faster than naïve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach.

Computing aggregate properties of preimages for 2D cellular automata

NASA Astrophysics Data System (ADS)

Beer, Randall D.

2017-11-01

Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm—incremental aggregation—that can compute aggregate properties of the set of precursors exponentially faster than naïve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Fuzzy cellular automata models in immunology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahmed, E.

1996-10-01

The self-nonself character of antigens is considered to be fuzzy. The Chowdhury et al. cellular automata model is generalized accordingly. New steady states are found. The first corresponds to a below-normal help and suppression and is proposed to be related to autoimmune diseases. The second corresponds to a below-normal B-cell level.

Discovery learning with SAVI approach in geometry learning

NASA Astrophysics Data System (ADS)

Sahara, R.; Mardiyana; Saputro, D. R. S.

2018-05-01

Geometry is one branch of mathematics that an important role in learning mathematics in the schools. This research aims to find out about Discovery Learning with SAVI approach to achievement of learning geometry. This research was conducted at Junior High School in Surakarta city. Research data were obtained through test and questionnaire. Furthermore, the data was analyzed by using two-way Anova. The results showed that Discovery Learning with SAVI approach gives a positive influence on mathematics learning achievement. Discovery Learning with SAVI approach provides better mathematics learning outcomes than direct learning. In addition, students with high self-efficacy categories have better mathematics learning achievement than those with moderate and low self-efficacy categories, while student with moderate self-efficacy categories are better mathematics learning achievers than students with low self-efficacy categories. There is an interaction between Discovery Learning with SAVI approach and self-efficacy toward student's mathematics learning achievement. Therefore, Discovery Learning with SAVI approach can improve mathematics learning achievement.

Color image encryption based on hybrid hyper-chaotic system and cellular automata

NASA Astrophysics Data System (ADS)

Yaghouti Niyat, Abolfazl; Moattar, Mohammad Hossein; Niazi Torshiz, Masood

2017-03-01

This paper proposes an image encryption scheme based on Cellular Automata (CA). CA is a self-organizing structure with a set of cells in which each cell is updated by certain rules that are dependent on a limited number of neighboring cells. The major disadvantages of cellular automata in cryptography include limited number of reversal rules and inability to produce long sequences of states by these rules. In this paper, a non-uniform cellular automata framework is proposed to solve this problem. This proposed scheme consists of confusion and diffusion steps. In confusion step, the positions of the original image pixels are replaced by chaos mapping. Key image is created using non-uniform cellular automata and then the hyper-chaotic mapping is used to select random numbers from the image key for encryption. The main contribution of the paper is the application of hyper chaotic functions and non-uniform CA for robust key image generation. Security analysis and experimental results show that the proposed method has a very large key space and is resistive against noise and attacks. The correlation between adjacent pixels in the encrypted image is reduced and the amount of entropy is equal to 7.9991 which is very close to 8 which is ideal.

Design of Efficient Mirror Adder in Quantum- Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Mishra, Prashant Kumar; Chattopadhyay, Manju K.

2018-03-01

Lower power consumption is an essential demand for portable multimedia system using digital signal processing algorithms and architectures. Quantum dot cellular automata (QCA) is a rising nano technology for the development of high performance ultra-dense low power digital circuits. QCA based several efficient binary and decimal arithmetic circuits are implemented, however important improvements are still possible. This paper demonstrate Mirror Adder circuit design in QCA. We present comparative study of mirror adder cells designed using conventional CMOS technique and mirror adder cells designed using quantum-dot cellular automata. QCA based mirror adders are better in terms of area by order of three.

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.

Quantum-dot cellular automata: Review and recent experiments (invited)

NASA Astrophysics Data System (ADS)

Snider, G. L.; Orlov, A. O.; Amlani, I.; Zuo, X.; Bernstein, G. H.; Lent, C. S.; Merz, J. L.; Porod, W.

1999-04-01

An introduction to the operation of quantum-dot cellular automata is presented, along with recent experimental results. Quantum-dot cellular automata (QCA) is a transistorless computation paradigm that addresses the issues of device density and interconnection. The basic building blocks of the QCA architecture, such as AND, OR, and NOT are presented. The experimental device is a four-dot QCA cell with two electrometers. The dots are metal islands, which are coupled by capacitors and tunnel junctions. An improved design of the cell is presented in which all four dots of the cell are coupled by tunnel junctions. The operation of this basic cell is confirmed by the externally controlled polarization change of the cell.

Emergent dynamic structures and statistical law in spherical lattice gas automata

NASA Astrophysics Data System (ADS)

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Emergent dynamic structures and statistical law in spherical lattice gas automata.

PubMed

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Jahn-Teller effect in molecular electronics: quantum cellular automata

NASA Astrophysics Data System (ADS)

Tsukerblat, B.; Palii, A.; Clemente-Juan, J. M.; Coronado, E.

2017-05-01

The article summarizes the main results of application of the theory of the Jahn-Teller (JT) and pseudo JT effects to the description of molecular quantum dot cellular automata (QCA), a new paradigm of quantum computing. The following issues are discussed: 1) QCA as a new paradigm of quantum computing, principles and advantages; 2) molecular implementation of QCA; 3) role of the JT effect in charge trapping, encoding of binary information in the quantum cell and non-linear cell-cell response; 4) spin-switching in molecular QCA based on mixed-valence cell; 5) intervalence optical absorption in tetrameric molecular mixed-valence cell through the symmetry assisted approach to the multimode/multilevel JT and pseudo JT problems.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

A verification strategy for web services composition using enhanced stacked automata model.

PubMed

Nagamouttou, Danapaquiame; Egambaram, Ilavarasan; Krishnan, Muthumanickam; Narasingam, Poonkuzhali

2015-01-01

Currently, Service-Oriented Architecture (SOA) is becoming the most popular software architecture of contemporary enterprise applications, and one crucial technique of its implementation is web services. Individual service offered by some service providers may symbolize limited business functionality; however, by composing individual services from different service providers, a composite service describing the intact business process of an enterprise can be made. Many new standards have been defined to decipher web service composition problem namely Business Process Execution Language (BPEL). BPEL provides an initial work for forming an Extended Markup Language (XML) specification language for defining and implementing business practice workflows for web services. The problems with most realistic approaches to service composition are the verification of composed web services. It has to depend on formal verification method to ensure the correctness of composed services. A few research works has been carried out in the literature survey for verification of web services for deterministic system. Moreover the existing models did not address the verification properties like dead transition, deadlock, reachability and safetyness. In this paper, a new model to verify the composed web services using Enhanced Stacked Automata Model (ESAM) has been proposed. The correctness properties of the non-deterministic system have been evaluated based on the properties like dead transition, deadlock, safetyness, liveness and reachability. Initially web services are composed using Business Process Execution Language for Web Service (BPEL4WS) and it is converted into ESAM (combination of Muller Automata (MA) and Push Down Automata (PDA)) and it is transformed into Promela language, an input language for Simple ProMeLa Interpreter (SPIN) tool. The model is verified using SPIN tool and the results revealed better recital in terms of finding dead transition and deadlock in contrast to the

Discovering Motifs in Biological Sequences Using the Micron Automata Processor.

PubMed

Roy, Indranil; Aluru, Srinivas

2016-01-01

Finding approximately conserved sequences, called motifs, across multiple DNA or protein sequences is an important problem in computational biology. In this paper, we consider the (l, d) motif search problem of identifying one or more motifs of length l present in at least q of the n given sequences, with each occurrence differing from the motif in at most d substitutions. The problem is known to be NP-complete, and the largest solved instance reported to date is (26,11). We propose a novel algorithm for the (l,d) motif search problem using streaming execution over a large set of non-deterministic finite automata (NFA). This solution is designed to take advantage of the micron automata processor, a new technology close to deployment that can simultaneously execute multiple NFA in parallel. We demonstrate the capability for solving much larger instances of the (l, d) motif search problem using the resources available within a single automata processor board, by estimating run-times for problem instances (39,18) and (40,17). The paper serves as a useful guide to solving problems using this new accelerator technology.

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information.

PubMed

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft's algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms.

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information

PubMed Central

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft’s algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms. PMID:27806102

Simulation of interdiffusion and voids growth based on cellular automata

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhang, Boyan; Zhang, Nan; Du, Haishun; Zhang, Xinhong

2017-02-01

In the interdiffusion of two solid-state materials, if the diffusion coefficients of the two materials are not the same, the interface of the two materials will shift to the material with the lower diffusion coefficient. This effect is known as the Kirkendall effect. The Kirkendall effect leads to Kirkendall porosity. The pores act as sinks for vacancies and become voids. In this paper, the movement of the Kirkendall plane at interdiffusion is simulated based on cellular automata. The number of vacancies, the critical radius of voids nucleation and the nucleation rate are analysed. The vacancies diffusion, vacancies aggregation and voids growth are also simulated based on cellular automata.

An Automaton Analysis of the Learning of a Miniature System of Japanese. Psychology Series.

ERIC Educational Resources Information Center

Wexler, Kenneth Norman

The purpose of the study reported here was to do an automata-theoretical and experimental investigation of the learning of the syntax and semantics of a second natural language. The main thrust of the work was to ask what kind of automaton a person can become. Various kinds of automata were considered, predictions were made from them, and these…

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes

A comparative analysis of electronic and molecular quantum dot cellular automata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Umamahesvari, H., E-mail: umamaheswarihema@gmail.com, E-mail: ajithavijay1@gmail.com; Ajitha, D., E-mail: umamaheswarihema@gmail.com, E-mail: ajithavijay1@gmail.com

This paper presents a comparative analysis of electronic quantum-dot cellular automata (EQCA) and Magnetic quantum dot Cellular Automata (MQCA). QCA is a computing paradigm that encodes and processes information by the position of individual electrons. To enhance the high dense and ultra-low power devices, various researches have been actively carried out to find an alternative way to continue and follow Moore’s law, so called “beyond CMOS technology”. There have been several proposals for physically implementing QCA, EQCA and MQCA are the two important QCAs reported so far. This paper provides a comparative study on these two QCAs.

Distribution functions of probabilistic automata

NASA Technical Reports Server (NTRS)

Vatan, F.

2001-01-01

Each probabilistic automaton M over an alphabet A defines a probability measure Prob sub(M) on the set of all finite and infinite words over A. We can identify a k letter alphabet A with the set {0, 1,..., k-1}, and, hence, we can consider every finite or infinite word w over A as a radix k expansion of a real number X(w) in the interval [0, 1]. This makes X(w) a random variable and the distribution function of M is defined as usual: F(x) := Prob sub(M) { w: X(w) < x }. Utilizing the fixed-point semantics (denotational semantics), extended to probabilistic computations, we investigate the distribution functions of probabilistic automata in detail. Automata with continuous distribution functions are characterized. By a new, and much more easier method, it is shown that the distribution function F(x) is an analytic function if it is a polynomial. Finally, answering a question posed by D. Knuth and A. Yao, we show that a polynomial distribution function F(x) on [0, 1] can be generated by a prob abilistic automaton iff all the roots of F'(x) = 0 in this interval, if any, are rational numbers. For this, we define two dynamical systems on the set of polynomial distributions and study attracting fixed points of random composition of these two systems.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.

PubMed

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-22

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

PubMed Central

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-01-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

NASA Astrophysics Data System (ADS)

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

A 3-D model of tumor progression based on complex automata driven by particle dynamics.

PubMed

Wcisło, Rafał; Dzwinel, Witold; Yuen, David A; Dudek, Arkadiusz Z

2009-12-01

The dynamics of a growing tumor involving mechanical remodeling of healthy tissue and vasculature is neglected in most of the existing tumor models. This is due to the lack of efficient computational framework allowing for simulation of mechanical interactions. Meanwhile, just these interactions trigger critical changes in tumor growth dynamics and are responsible for its volumetric and directional progression. We describe here a novel 3-D model of tumor growth, which combines particle dynamics with cellular automata concept. The particles represent both tissue cells and fragments of the vascular network. They interact with their closest neighbors via semi-harmonic central forces simulating mechanical resistance of the cell walls. The particle dynamics is governed by both the Newtonian laws of motion and the cellular automata rules. These rules can represent cell life-cycle and other biological interactions involving smaller spatio-temporal scales. We show that our complex automata, particle based model can reproduce realistic 3-D dynamics of the entire system consisting of the tumor, normal tissue cells, blood vessels and blood flow. It can explain phenomena such as the inward cell motion in avascular tumor, stabilization of tumor growth by the external pressure, tumor vascularization due to the process of angiogenesis, trapping of healthy cells by invading tumor, and influence of external (boundary) conditions on the direction of tumor progression. We conclude that the particle model can serve as a general framework for designing advanced multiscale models of tumor dynamics and it is very competitive to the modeling approaches presented before.

Boolean linear differential operators on elementary cellular automata

NASA Astrophysics Data System (ADS)

Martín Del Rey, Ángel

2014-12-01

In this paper, the notion of boolean linear differential operator (BLDO) on elementary cellular automata (ECA) is introduced and some of their more important properties are studied. Special attention is paid to those differential operators whose coefficients are the ECA with rule numbers 90 and 150.

Potential field cellular automata model for pedestrian flow

NASA Astrophysics Data System (ADS)

Zhang, Peng; Jian, Xiao-Xia; Wong, S. C.; Choi, Keechoo

2012-02-01

This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.

Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

PubMed

de Bruin, Jeroen S; Steltzer, Heinz; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

2017-01-01

Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationships between measured or observed data and linguistic terms are expressed as degrees of compatibility that model the unsharpness of the boundaries of linguistic terms. Propositional uncertainty due to incomplete knowledge of relationships between clinical linguistic concepts is modeled with fuzzy logic. Fuzzy Arden Syntax also supports the construction of fuzzy state monitors. The latter are defined as monitors that employ fuzzy automata to observe gradual transitions between different stages of disease. As a use case, we re-implemented FuzzyARDS, a previously published clinical monitoring system for patients suffering from acute respiratory distress syndrome (ARDS). Using the re-implementation as an example, we show how key concepts of fuzzy automata, i.e., fuzzy states and parallel fuzzy state transitions, can be implemented in Fuzzy Arden Syntax. The results showed that fuzzy state monitors can be implemented in a straightforward manner.

A Cellular Automata-based Model for Simulating Restitution Property in a Single Heart Cell.

PubMed

Sabzpoushan, Seyed Hojjat; Pourhasanzade, Fateme

2011-01-01

Ventricular fibrillation is the cause of the most sudden mortalities. Restitution is one of the specific properties of ventricular cell. The recent findings have clearly proved the correlation between the slope of restitution curve with ventricular fibrillation. This; therefore, mandates the modeling of cellular restitution to gain high importance. A cellular automaton is a powerful tool for simulating complex phenomena in a simple language. A cellular automaton is a lattice of cells where the behavior of each cell is determined by the behavior of its neighboring cells as well as the automata rule. In this paper, a simple model is depicted for the simulation of the property of restitution in a single cardiac cell using cellular automata. At first, two state variables; action potential and recovery are introduced in the automata model. In second, automata rule is determined and then recovery variable is defined in such a way so that the restitution is developed. In order to evaluate the proposed model, the generated restitution curve in our study is compared with the restitution curves from the experimental findings of valid sources. Our findings indicate that the presented model is not only capable of simulating restitution in cardiac cell, but also possesses the capability of regulating the restitution curve.

Cellular automata in photonic cavity arrays.

PubMed

Li, Jing; Liew, T C H

2016-10-31

We propose theoretically a photonic Turing machine based on cellular automata in arrays of nonlinear cavities coupled with artificial gauge fields. The state of the system is recorded making use of the bistability of driven cavities, in which losses are fully compensated by an external continuous drive. The sequential update of the automaton layers is achieved automatically, by the local switching of bistable states, without requiring any additional synchronization or temporal control.

Parallel Implementation of Triangular Cellular Automata for Computing Two-Dimensional Elastodynamic Response on Arbitrary Domains

NASA Astrophysics Data System (ADS)

Leamy, Michael J.; Springer, Adam C.

In this research we report parallel implementation of a Cellular Automata-based simulation tool for computing elastodynamic response on complex, two-dimensional domains. Elastodynamic simulation using Cellular Automata (CA) has recently been presented as an alternative, inherently object-oriented technique for accurately and efficiently computing linear and nonlinear wave propagation in arbitrarily-shaped geometries. The local, autonomous nature of the method should lead to straight-forward and efficient parallelization. We address this notion on symmetric multiprocessor (SMP) hardware using a Java-based object-oriented CA code implementing triangular state machines (i.e., automata) and the MPI bindings written in Java (MPJ Express). We use MPJ Express to reconfigure our existing CA code to distribute a domain's automata to cores present on a dual quad-core shared-memory system (eight total processors). We note that this message passing parallelization strategy is directly applicable to computer clustered computing, which will be the focus of follow-on research. Results on the shared memory platform indicate nearly-ideal, linear speed-up. We conclude that the CA-based elastodynamic simulator is easily configured to run in parallel, and yields excellent speed-up on SMP hardware.

Dynamics of HIV infection on 2D cellular automata

NASA Astrophysics Data System (ADS)

Benyoussef, A.; HafidAllah, N. El; ElKenz, A.; Ez-Zahraouy, H.; Loulidi, M.

2003-05-01

We use a cellular automata approach to describe the interactions of the immune system with the human immunodeficiency virus (HIV). We study the evolution of HIV infection, particularly in the clinical latency period. The results we have obtained show the existence of four different behaviours in the plane of death rate of virus-death rate of infected T cell. These regions meet at a critical point, where the virus density and the infected T cell density remain invariant during the evolution of disease. We have introduced two kinds of treatments, the protease inhibitors and the RT inhibitors, in order to study their effects on the evolution of HIV infection. These treatments are powerful in decreasing the density of the virus in the blood and the delay of the AIDS onset.

Approaches to Machine Learning.

DTIC Science & Technology

1984-02-16

The field of machine learning strives to develop methods and techniques to automatic the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition. We illustrate each of the basic approaches with paradigmatic examples. (Author)

Learning automata-based solutions to the nonlinear fractional knapsack problem with applications to optimal resource allocation.

PubMed

Granmo, Ole-Christoffer; Oommen, B John; Myrer, Svein Arild; Olsen, Morten Goodwin

2007-02-01

This paper considers the nonlinear fractional knapsack problem and demonstrates how its solution can be effectively applied to two resource allocation problems dealing with the World Wide Web. The novel solution involves a "team" of deterministic learning automata (LA). The first real-life problem relates to resource allocation in web monitoring so as to "optimize" information discovery when the polling capacity is constrained. The disadvantages of the currently reported solutions are explained in this paper. The second problem concerns allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. This is the scenario encountered when the user has to evaluate multiple web sites by accessing a limited number of web pages, and the proportions of interest are the fraction of each web site that is successfully validated by an HTML validator. Using the general LA paradigm to tackle both of the real-life problems, the proposed scheme improves a current solution in an online manner through a series of informed guesses that move toward the optimal solution. At the heart of the scheme, a team of deterministic LA performs a controlled random walk on a discretized solution space. Comprehensive experimental results demonstrate that the discretization resolution determines the precision of the scheme, and that for a given precision, the current solution (to both problems) is consistently improved until a nearly optimal solution is found--even for switching environments. Thus, the scheme, while being novel to the entire field of LA, also efficiently handles a class of resource allocation problems previously not addressed in the literature.

Universal map for cellular automata

NASA Astrophysics Data System (ADS)

García-Morales, V.

2012-08-01

A universal map is derived for all deterministic 1D cellular automata (CAs) containing no freely adjustable parameters and valid for any alphabet size and any neighborhood range (including non-symmetrical neighborhoods). The map can be extended to an arbitrary number of dimensions and topologies and to arbitrary order in time. Specific CA maps for the famous Conway's Game of Life and Wolfram's 256 elementary CAs are given. An induction method for CAs, based in the universal map, allows mathematical expressions for the orbits of a wide variety of elementary CAs to be systematically derived.

Computational Modeling of Proteins based on Cellular Automata: A Method of HP Folding Approximation.

PubMed

Madain, Alia; Abu Dalhoum, Abdel Latif; Sleit, Azzam

2018-06-01

The design of a protein folding approximation algorithm is not straightforward even when a simplified model is used. The folding problem is a combinatorial problem, where approximation and heuristic algorithms are usually used to find near optimal folds of proteins primary structures. Approximation algorithms provide guarantees on the distance to the optimal solution. The folding approximation approach proposed here depends on two-dimensional cellular automata to fold proteins presented in a well-studied simplified model called the hydrophobic-hydrophilic model. Cellular automata are discrete computational models that rely on local rules to produce some overall global behavior. One-third and one-fourth approximation algorithms choose a subset of the hydrophobic amino acids to form H-H contacts. Those algorithms start with finding a point to fold the protein sequence into two sides where one side ignores H's at even positions and the other side ignores H's at odd positions. In addition, blocks or groups of amino acids fold the same way according to a predefined normal form. We intend to improve approximation algorithms by considering all hydrophobic amino acids and folding based on the local neighborhood instead of using normal forms. The CA does not assume a fixed folding point. The proposed approach guarantees one half approximation minus the H-H endpoints. This lower bound guaranteed applies to short sequences only. This is proved as the core and the folds of the protein will have two identical sides for all short sequences.

Cellular Automata Ideas in Digital Circuits and Switching Theory.

ERIC Educational Resources Information Center

Siwak, Pawel P.

1985-01-01

Presents two examples which illustrate the usefulness of ideas from cellular automata. First, Lee's algorithm is recalled and its cellular nature shown. Then a problem from digraphs, which has arisen from analyzing predecessing configurations in the famous Conway's "game of life," is considered. (Author/JN)

Quantifying a cellular automata simulation of electric vehicles

NASA Astrophysics Data System (ADS)

Hill, Graeme; Bell, Margaret; Blythe, Phil

2014-12-01

Within this work the Nagel-Schreckenberg (NS) cellular automata is used to simulate a basic cyclic road network. Results from SwitchEV, a real world Electric Vehicle trial which has collected more than two years of detailed electric vehicle data, are used to quantify the results of the NS automata, demonstrating similar power consumption behavior to that observed in the experimental results. In particular the efficiency of the electric vehicles reduces as the vehicle density increases, due in part to the reduced efficiency of EVs at low speeds, but also due to the energy consumption inherent in changing speeds. Further work shows the results from introducing spatially restricted speed restriction. In general it can be seen that induced congestion from spatially transient events propagates back through the road network and alters the energy and efficiency profile of the simulated vehicles, both before and after the speed restriction. Vehicles upstream from the restriction show a reduced energy usage and an increased efficiency, and vehicles downstream show an initial large increase in energy usage as they accelerate away from the speed restriction.

Experimental Studies of Quasi-Adiabatic Quantum-dot Cellular Automata

NASA Astrophysics Data System (ADS)

Orlov, Alexei; Amlani, Islamshah; Kummamuru, Ravi; Toth, Geza; Bernstein, Gary; Lent, Craig; Snider, Gregory

2000-03-01

The computational approach known as Quantum-dot Cellular Automata (QCA) uses interacting quantum dots to encode and process binary information. The first realization of a functioning QCA cell has already been reported. Recently, quasi-adiabatic switching of QCA in a metal dot system near the instantaneous ground state was proposed [1]. The advantage if this approach is that it allows both logic and addressable memory to be implemented within the QCA framework. We report on the fabrication and measurement of such a device in the Al-AlOx tunnel junction system. This basic building block consists of three metal islands connected in series by tunnel junctions, where an electron can be moved between islands by means of electrostatic perturbation on either control electrodes or adjacent cells. The cell can have three operational modes, i.e. active, locked and null, which provide a solution for ground state computing that is not susceptible to metastable states. [1] G. Toth and C. S. Lent, J. appl. Phys. 85 5, 2977-2984, 1999.

A stochastic automata network for earthquake simulation and hazard estimation

NASA Astrophysics Data System (ADS)

Belubekian, Maya Ernest

1998-11-01

This research develops a model for simulation of earthquakes on seismic faults with available earthquake catalog data. The model allows estimation of the seismic hazard at a site of interest and assessment of the potential damage and loss in a region. There are two approaches for studying the earthquakes: mechanistic and stochastic. In the mechanistic approach, seismic processes, such as changes in stress or slip on faults, are studied in detail. In the stochastic approach, earthquake occurrences are simulated as realizations of a certain stochastic process. In this dissertation, a stochastic earthquake occurrence model is developed that uses the results from dislocation theory for the estimation of slip released in earthquakes. The slip accumulation and release laws and the event scheduling mechanism adopted in the model result in a memoryless Poisson process for the small and moderate events and in a time- and space-dependent process for large events. The minimum and maximum of the hazard are estimated by the model when the initial conditions along the faults correspond to a situation right after a largest event and after a long seismic gap, respectively. These estimates are compared with the ones obtained from a Poisson model. The Poisson model overestimates the hazard after the maximum event and underestimates it in the period of a long seismic quiescence. The earthquake occurrence model is formulated as a stochastic automata network. Each fault is divided into cells, or automata, that interact by means of information exchange. The model uses a statistical method called bootstrap for the evaluation of the confidence bounds on its results. The parameters of the model are adjusted to the target magnitude patterns obtained from the catalog. A case study is presented for the city of Palo Alto, where the hazard is controlled by the San Andreas, Hayward and Calaveras faults. The results of the model are used to evaluate the damage and loss distribution in Palo Alto

Construction of living cellular automata using the Physarum plasmodium

NASA Astrophysics Data System (ADS)

Shirakawa, Tomohiro; Sato, Hiroshi; Ishiguro, Shinji

2015-04-01

The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that has an amorphous cell body. To clearly observe how the plasmodium makes decisions in its motile and exploratory behaviours, we developed a new experimental system to pseudo-discretize the motility of the organism. In our experimental space that has agar surfaces arranged in a two-dimensional lattice, the continuous and omnidirectional movement of the plasmodium was limited to the stepwise one, and the direction of the locomotion was also limited to four neighbours. In such an experimental system, a cellular automata-like system was constructed using the living cell. We further analysed the exploratory behaviours of the plasmodium by duplicating the experimental results in the simulation models of cellular automata. As a result, it was revealed that the behaviours of the plasmodium are not reproduced by only local state transition rules; and for the reproduction, a kind of historical rule setting is needed.

Synchronization, TIGoRS, and Information Flow in Complex Systems: Dispositional Cellular Automata.

PubMed

Sulis, William H

2016-04-01

Synchronization has a long history in physics where it refers to the phase matching of two identical oscillators. This notion has been extensively studied in physics as well as in biology, where it has been applied to such widely varying phenomena as the flashing of fireflies and firing of neurons in the brain. Human behavior, however, may be recurrent but it is not oscillatory even though many physiological systems do exhibit oscillatory tendencies. Moreover, much of human behaviour is collaborative and cooperative, where the individual behaviours may be distinct yet contemporaneous (if not simultaneous) and taken collectively express some functionality. In the context of behaviour, the important aspect is the repeated co-occurrence in time of behaviours that facilitate the propagation of information or of functionality, regardless of whether or not these behaviours are similar or identical. An example of this weaker notion of synchronization is transient induced global response synchronization (TIGoRS). Previous work has shown that TIGoRS is a ubiquitous phenomenon among complex systems, enabling them to stably parse environmental transients into salient units to which they stably respond. This leads to the notion of Sulis machines, which emergently generate a primitive linguistic structure through their dynamics. This article reviews the notion of TIGoRS and its expression in several complex systems models including tempered neural networks, driven cellular automata and cocktail party automata. The emergent linguistics of Sulis machines are discussed. A new class of complex systems model, the dispositional cellular automaton is introduced. A new metric for TIGoRS, the excess synchronization, is introduced and applied to the study of TIGoRS in dispositional cellular automata. It is shown that these automata exhibit a nonlinear synchronization response to certain perturbing transients.

A Programmable Cellular-Automata Polarized Dirac Vacuum

NASA Astrophysics Data System (ADS)

Osoroma, Drahcir S.

2013-09-01

We explore properties of a `Least Cosmological Unit' (LCU) as an inherent spacetime raster tiling or tessellating the unique backcloth of Holographic Anthropic Multiverse (HAM) cosmology as an array of programmable cellular automata. The HAM vacuum is a scale-invariant HD extension of a covariant polarized Dirac vacuum with `bumps' and `holes' typically described by extended electromagnetic theory corresponding to an Einstein energy-dependent spacetime metric admitting a periodic photon mass. The new cosmology incorporates a unique form of M-Theoretic Calabi-Yau-Poincaré Dodecadedral-AdS5-DS5space (PDS) with mirror symmetry best described by an HD extension of Cramer's Transactional Interpretation when integrated also with an HD extension of the de Broglie-Bohm-Vigier causal interpretation of quantum theory. We incorporate a unique form of large-scale additional dimensionality (LSXD) bearing some similarity to that conceived by Randall and Sundrum; and extend the fundamental basis of our model to the Unified Field, UF. A Sagnac Effect rf-pulsed incursive resonance hierarchy is utilized to manipulate and ballistically program the geometric-topological properties of this putative LSXD space-spacetime network. The model is empirically testable; and it is proposed that a variety of new technologies will arise from ballistic programming of tessellated LCU vacuum cellular automata.

Simulations of Forest Fires by the Cellular Automata Model "ABBAMPAU"

NASA Astrophysics Data System (ADS)

di Gregorio, S.; Bendicenti, E.

2003-04-01

Forest fires represent a serious environmental problem, whose negative impact is becoming day by day more worrisome. Forest fires are very complex phenomena; that need an interdisciplinary approach. The adopted method to modelling involves the definition of local rules, from which the global behaviour of the system can emerge. The paradigm of Cellular Automata was applied and the model ABBAMPAU was projected to simulate the evolution of forest fires. Cellular Automata features (parallelism and a-centrism) seem to match the system "forest fire"; the parameters, describing globally a forest fire, i.e. propagation rate, flame length and direction, fireline intensity, fire duration time et c. are mainly depending on some local characteristics i.e. vegetation type (live and dead fuel), relative humidity, fuel moisture, heat, territory morphology (altitude, slope), et c.. The only global characteristic is given by wind velocity and direction, but wind velocity and direction is locally altered according to the morphology; therefore wind has also to be considered at local level. ABBAMPAU accounts for the following aspects of the phenomenon: effects of combustion in surface and crown fire inside the cell, crown fire triggering off; surface and crown fire spread, determination of the local wind rate and direction. A validation of ABBAMPAU was tested on a real case of forest fire, in the territory of Villaputzu, Sardinia island, August 22nd, 1998. First simulations account for the main characteristics of the phenomenon and agree with the observations. The results show that the model could be applied for the forest fire preventions, the productions of risk scenarios and the evaluation of the forest fire environmental impact.

Investigation of phase diagrams for cylindrical Ising nanotube using cellular automata

NASA Astrophysics Data System (ADS)

Astaraki, M.; Ghaemi, M.; Afzali, K.

2018-05-01

Recent developments in the field of applied nanoscience and nanotechnology have heightened the need for categorizing various characteristics of nanostructures. In this regard, this paper establishes a novel method to investigate magnetic properties (phase diagram and spontaneous magnetization) of a cylindrical Ising nanotube. Using a two-layer Ising model and the core-shell concept, the interactions within nanotube has been modelled. In the model, both ferromagnetic and antiferromagnetic cases have been considered. Furthermore, the effect of nanotube's length on the critical temperature is investigated. The model has been simulated using cellular automata approach and phase diagrams were constructed for different values of inter- and intra-layer couplings. For the antiferromagnetic case, the possibility of existence of compensation point is observed.

Design of Improved Arithmetic Logic Unit in Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Heikalabad, Saeed Rasouli; Gadim, Mahya Rahimpour

2018-06-01

The quantum-dot cellular automata (QCA) can be replaced to overcome the limitation of CMOS technology. An arithmetic logic unit (ALU) is a basic structure of any computer devices. In this paper, design of improved single-bit arithmetic logic unit in quantum dot cellular automata is presented. The proposed structure for ALU has AND, OR, XOR and ADD operations. A unique 2:1 multiplexer, an ultra-efficient two-input XOR and a low complexity full adder are used in the proposed structure. Also, an extended design of this structure is provided for two-bit ALU in this paper. The proposed structure of ALU is simulated by QCADesigner and simulation result is evaluated. Evaluation results show that the proposed design has best performance in terms of area, complexity and delay compared to the previous designs.

Design of Improved Arithmetic Logic Unit in Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Heikalabad, Saeed Rasouli; Gadim, Mahya Rahimpour

2018-03-01

The quantum-dot cellular automata (QCA) can be replaced to overcome the limitation of CMOS technology. An arithmetic logic unit (ALU) is a basic structure of any computer devices. In this paper, design of improved single-bit arithmetic logic unit in quantum dot cellular automata is presented. The proposed structure for ALU has AND, OR, XOR and ADD operations. A unique 2:1 multiplexer, an ultra-efficient two-input XOR and a low complexity full adder are used in the proposed structure. Also, an extended design of this structure is provided for two-bit ALU in this paper. The proposed structure of ALU is simulated by QCADesigner and simulation result is evaluated. Evaluation results show that the proposed design has best performance in terms of area, complexity and delay compared to the previous designs.

Regulation Effects by Programmed Molecules for Transcription-Based Diagnostic Automata towards Therapeutic Use

NASA Astrophysics Data System (ADS)

Hirabayashi, Miki; Ohashi, Hirotada; Kubo, Tai

We have presented experimental analysis on the controllability of our transcription-based diagnostic biomolecular automata by programmed molecules. Focusing on the noninvasive transcriptome diagnosis by salivary mRNAs, we already proposed the novel concept of diagnostic device using DNA computation. This system consists of the main computational element which has a stem shaped promoter region and a pseudo-loop shaped read-only memory region for transcription regulation through the conformation change caused by the recognition of disease-related biomarkers. We utilize the transcription of malachite green aptamer sequence triggered by the target recognition for observation of detection. This algorithm makes it possible to release RNA-aptamer drugs multiply, different from the digestion-based systems by the restriction enzyme which was proposed previously, for the in-vivo use, however, the controllability of aptamer release is not enough at the previous stage. In this paper, we verified the regulation effect on aptamer transcription by programmed molecules in basic conditions towards the developm! ent of therapeutic automata. These results would bring us one step closer to the realization of new intelligent diagnostic and therapeutic automata based on molecular circuits.

Simulation of root forms using cellular automata model

NASA Astrophysics Data System (ADS)

Winarno, Nanang; Prima, Eka Cahya; Afifah, Ratih Mega Ayu

2016-02-01

This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled "A New Kind of Science" discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram's investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.

Simulation of root forms using cellular automata model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winarno, Nanang, E-mail: nanang-winarno@upi.edu; Prima, Eka Cahya; Afifah, Ratih Mega Ayu

This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled “A New Kind of Science” discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram’s investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation usedmore » four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.« less

On the derivation of approximations to cellular automata models and the assumption of independence.

PubMed

Davies, K J; Green, J E F; Bean, N G; Binder, B J; Ross, J V

2014-07-01

Cellular automata are discrete agent-based models, generally used in cell-based applications. There is much interest in obtaining continuum models that describe the mean behaviour of the agents in these models. Previously, continuum models have been derived for agents undergoing motility and proliferation processes, however, these models only hold under restricted conditions. In order to narrow down the reason for these restrictions, we explore three possible sources of error in deriving the model. These sources are the choice of limiting arguments, the use of a discrete-time model as opposed to a continuous-time model and the assumption of independence between the state of sites. We present a rigorous analysis in order to gain a greater understanding of the significance of these three issues. By finding a limiting regime that accurately approximates the conservation equation for the cellular automata, we are able to conclude that the inaccuracy between our approximation and the cellular automata is completely based on the assumption of independence. Copyright © 2014 Elsevier Inc. All rights reserved.

Stochastic computing with biomolecular automata

PubMed Central

Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud

2004-01-01

Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure. PMID:15215499

A learning approach to the bandwidth multicolouring problem

NASA Astrophysics Data System (ADS)

Akbari Torkestani, Javad

2016-05-01

In this article, a generalisation of the vertex colouring problem known as bandwidth multicolouring problem (BMCP), in which a set of colours is assigned to each vertex such that the difference between the colours, assigned to each vertex and its neighbours, is by no means less than a predefined threshold, is considered. It is shown that the proposed method can be applied to solve the bandwidth colouring problem (BCP) as well. BMCP is known to be NP-hard in graph theory, and so a large number of approximation solutions, as well as exact algorithms, have been proposed to solve it. In this article, two learning automata-based approximation algorithms are proposed for estimating a near-optimal solution to the BMCP. We show, for the first proposed algorithm, that by choosing a proper learning rate, the algorithm finds the optimal solution with a probability close enough to unity. Moreover, we compute the worst-case time complexity of the first algorithm for finding a 1/(1-ɛ) optimal solution to the given problem. The main advantage of this method is that a trade-off between the running time of algorithm and the colour set size (colouring optimality) can be made, by a proper choice of the learning rate also. Finally, it is shown that the running time of the proposed algorithm is independent of the graph size, and so it is a scalable algorithm for large graphs. The second proposed algorithm is compared with some well-known colouring algorithms and the results show the efficiency of the proposed algorithm in terms of the colour set size and running time of algorithm.

Generalized hydrodynamic transport in lattice-gas automata

NASA Technical Reports Server (NTRS)

Luo, Li-Shi; Chen, Hudong; Chen, Shiyi; Doolen, Gary D.; Lee, Yee-Chun

1991-01-01

The generalized hydrodynamics of two-dimensional lattice-gas automata is solved analytically in the linearized Boltzmann approximation. The dependence of the transport coefficients (kinematic viscosity, bulk viscosity, and sound speed) upon wave number k is obtained analytically. Anisotropy of these coefficients due to the lattice symmetry is studied for the entire range of wave number, k. Boundary effects due to a finite mean free path (Knudsen layer) are analyzed, and accurate comparisons are made with lattice-gas simulations.

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

PubMed

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.

Cellular automata rule characterization and classification using texture descriptors

NASA Astrophysics Data System (ADS)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

Does the acceptance of hybrid learning affect learning approaches in France?

PubMed

Marco, Lionel Di; Venot, Alain; Gillois, Pierre

2017-01-01

Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (P< 0.001), which is consistent with their declared learning strategies (personal reorganization of information; search and use of examples). There was no correlation between poor acceptance of the learning model and inadequate learning approaches. The strategy of using deep learning techniques was moderately correlated with acceptance of the learning model (r s = 0.42, P= 0.03). Learning approaches were not affected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

Does the acceptance of hybrid learning affect learning approaches in France?

PubMed Central

2017-01-01

Purpose Acceptance of a learning technology affects students’ intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students’ way of learning. Methods We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Results Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (P< 0.001), which is consistent with their declared learning strategies (personal reorganization of information; search and use of examples). There was no correlation between poor acceptance of the learning model and inadequate learning approaches. The strategy of using deep learning techniques was moderately correlated with acceptance of the learning model (rs= 0.42, P= 0.03). Conclusion Learning approaches were not affected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students’ time utilization, which explains their neutral intention to use the system. PMID:29051406

Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; Coutinho, Sérgio; Zorzenon dos Santos, Rita Maria; de Figueirêdo, Pedro Hugo

2013-10-01

The dynamics of human immunodeficiency virus infection under antiretroviral therapy is investigated using a cellular automata model where the effectiveness of each drug is self-adjusted by the concentration of CD4+ T infected cells present at each time step. The effectiveness of the drugs and the infected cell concentration at the beginning of treatment are the control parameters of the cell population’s dynamics during therapy. The model allows describing processes of mono and combined therapies. The dynamics that emerges from this model when considering combined antiretroviral therapies reproduces with fair qualitative agreement the phases and different time scales of the process. As observed in clinical data, the results reproduce the significant decrease in the population of infected cells and a concomitant increase of the population of healthy cells in a short timescale (weeks) after the initiation of treatment. Over long time scales, early treatment with potent drugs may lead to undetectable levels of infection. For late treatment or treatments starting with a low density of CD4+ T healthy cells it was observed that the treatment may lead to a steady state in which the T cell counts are above the threshold associated with the onset of AIDS. The results obtained are validated through comparison to available clinical trial data.

Social interactions of eating behaviour among high school students: a cellular automata approach

PubMed Central

2012-01-01

Background Overweight and obesity in children and adolescents is a global epidemic posing problems for both developed and developing nations. The prevalence is particularly alarming in developed nations, such as the United States, where approximately one in three school-aged adolescents (ages 12-19) are overweight or obese. Evidence suggests that weight gain in school-aged adolescents is related to energy imbalance exacerbated by the negative aspects of the school food environment, such as presence of unhealthy food choices. While a well-established connection exists between the food environment, presently there is a lack of studies investigating the impact of the social environment and associated interactions of school-age adolescents. This paper uses a mathematical modelling approach to explore how social interactions among high school adolescents can affect their eating behaviour and food choice. Methods In this paper we use a Cellular Automata (CA) modelling approach to explore how social interactions among school-age adolescents can affect eating behaviour, and food choice. Our CA model integrates social influences and transition rules to simulate the way individuals would interact in a social community (e.g., school cafeteria). To replicate these social interactions, we chose the Moore neighbourhood which allows all neighbours (eights cells in a two-dimensional square lattice) to influence the central cell. Our assumption is that individuals belong to any of four states; Bring Healthy, Bring Unhealthy, Purchase Healthy, and Purchase Unhealthy, and will influence each other according to parameter settings and transition rules. Simulations were run to explore how the different states interact under varying parameter settings. Results This study, through simulations, illustrates that students will change their eating behaviour from unhealthy to healthy as a result of positive social and environmental influences. In general, there is one common characteristic of

Modelling of Microstructure Changes in Hot Deformed Materials Using Cellular Automata

NASA Astrophysics Data System (ADS)

Kuc, Dariusz; Gawąd, Jerzy

2011-01-01

The paper is focused on application of multi-scale 2D method. Model approach consists of Cellular Automata (CA) model of microstructure development and the finite element code to solve thermo-mechanical problem. Dynamic recrystallization phenomenon is taken into account in 2D CA model which takes advantage of explicit representation of microstructure, including individual grains and grain boundaries. Flow stress is the main material parameter in mechanical part of FE and is calculated on the basis of average dislocation density obtained from CA model. The results attained from the model were validated with the experimental data. In the present study, austenitic steel X3CrNi18-10 was investigated. The examination of microstructure for the initial and final microstructures was carried out, using light microscopy and transmission electron microscopy.

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

An Ecological Approach to Learning Dynamics

ERIC Educational Resources Information Center

Normak, Peeter; Pata, Kai; Kaipainen, Mauri

2012-01-01

New approaches to emergent learner-directed learning design can be strengthened with a theoretical framework that considers learning as a dynamic process. We propose an approach that models a learning process using a set of spatial concepts: learning space, position of a learner, niche, perspective, step, path, direction of a step and step…

Three-dimensional cellular automata as a model of a seismic fault

NASA Astrophysics Data System (ADS)

Gálvez, G.; Muñoz, A.

2017-01-01

The Earth's crust is broken into a series of plates, whose borders are the seismic fault lines and it is where most of the earthquakes occur. This plating system can in principle be described by a set of nonlinear coupled equations describing the motion of the plates, its stresses, strains and other characteristics. Such a system of equations is very difficult to solve, and nonlinear parts leads to a chaotic behavior, which is not predictable. In 1989, Bak and Tang presented an earthquake model based on the sand pile cellular automata. The model though simple, provides similar results to those observed in actual earthquakes. In this work the cellular automata in three dimensions is proposed as a best model to approximate a seismic fault. It is noted that the three-dimensional model reproduces similar properties to those observed in real seismicity, especially, the Gutenberg-Richter law.

A class of cellular automata modeling winnerless competition

NASA Astrophysics Data System (ADS)

Afraimovich, V.; Ordaz, F. C.; Urías, J.

2002-06-01

Neural units introduced by Rabinovich et al. ("Sensory coding with dynamically competitive networks," UCSD and CIT, February 1999) motivate a class of cellular automata (CA) where spatio-temporal encoding is feasible. The spatio-temporal information capacity of a CA is estimated by the information capacity of the attractor set, which happens to be finitely specified. Two-dimensional CA are studied in detail. An example is given for which the attractor is not a subshift.

The impact of teachers' approaches to teaching and students' learning styles on students' approaches to learning in college online biology courses

NASA Astrophysics Data System (ADS)

Hong, Yuh-Fong

With the rapid growth of online courses in higher education institutions, research on quality of learning for online courses is needed. However, there is a notable lack of research in the cited literature providing evidence that online distance education promotes the quality of independent learning to which it aspires. Previous studies focused on academic outcomes and technology applications which do not monitor students' learning processes, such as their approaches to learning. Understanding students' learning processes and factors influencing quality of learning will provide valuable information for instructors and institutions in providing quality online courses and programs. The purpose of this study was to identify and investigate college biology teachers' approaches to teaching and students' learning styles, and to examine the impact of approaches to teaching and learning styles on students' approaches to learning via online instruction. Data collection included eighty-seven participants from five online biology courses at a community college in the southern area of Texas. Data analysis showed the following results. First, there were significant differences in approaches to learning among students with different learning styles. Second, there was a significant difference in students' approaches to learning between classes using different approaches to teaching. Three, the impact of learning styles on students' approaches to learning was not influenced by instructors' approaches to teaching. Two conclusions were obtained from the results. First, individuals with the ability to perceive information abstractly might be more likely to adopt deep approaches to learning than those preferring to perceive information through concrete experience in online learning environments. Second, Teaching Approach Inventory might not be suitable to measure approaches to teaching for online biology courses due to online instructional design and technology limitations. Based on

Simulating Space Radiation-Induced Breast Tumor Incidence Using Automata.

PubMed

Heuskin, A C; Osseiran, A I; Tang, J; Costes, S V

2016-07-01

Estimating cancer risk from space radiation has been an ongoing challenge for decades primarily because most of the reported epidemiological data on radiation-induced risks are derived from studies of atomic bomb survivors who were exposed to an acute dose of gamma rays instead of chronic high-LET cosmic radiation. In this study, we introduce a formalism using cellular automata to model the long-term effects of ionizing radiation in human breast for different radiation qualities. We first validated and tuned parameters for an automata-based two-stage clonal expansion model simulating the age dependence of spontaneous breast cancer incidence in an unexposed U.S. We then tested the impact of radiation perturbation in the model by modifying parameters to reflect both targeted and nontargeted radiation effects. Targeted effects (TE) reflect the immediate impact of radiation on a cell's DNA with classic end points being gene mutations and cell death. They are well known and are directly derived from experimental data. In contrast, nontargeted effects (NTE) are persistent and affect both damaged and undamaged cells, are nonlinear with dose and are not well characterized in the literature. In this study, we introduced TE in our model and compared predictions against epidemiologic data of the atomic bomb survivor cohort. TE alone are not sufficient for inducing enough cancer. NTE independent of dose and lasting ∼100 days postirradiation need to be added to accurately predict dose dependence of breast cancer induced by gamma rays. Finally, by integrating experimental relative biological effectiveness (RBE) for TE and keeping NTE (i.e., radiation-induced genomic instability) constant with dose and LET, the model predicts that RBE for breast cancer induced by cosmic radiation would be maximum at 220 keV/μm. This approach lays the groundwork for further investigation into the impact of chronic low-dose exposure, inter-individual variation and more complex space radiation

Finding and defining the natural automata acting in living plants: Toward the synthetic biology for robotics and informatics in vivo.

PubMed

Kawano, Tomonori; Bouteau, François; Mancuso, Stefano

2012-11-01

The automata theory is the mathematical study of abstract machines commonly studied in the theoretical computer science and highly interdisciplinary fields that combine the natural sciences and the theoretical computer science. In the present review article, as the chemical and biological basis for natural computing or informatics, some plants, plant cells or plant-derived molecules involved in signaling are listed and classified as natural sequential machines (namely, the Mealy machines or Moore machines) or finite state automata. By defining the actions (states and transition functions) of these natural automata, the similarity between the computational data processing and plant decision-making processes became obvious. Finally, their putative roles as the parts for plant-based computing or robotic systems are discussed.

Opinion evolution based on cellular automata rules in small world networks

NASA Astrophysics Data System (ADS)

Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

2010-03-01

In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

Supervisory control of (max,+) automata: extensions towards applications

NASA Astrophysics Data System (ADS)

Lahaye, Sébastien; Komenda, Jan; Boimond, Jean-Louis

2015-12-01

In this paper, supervisory control of (max,+) automata is studied. The synthesis of maximally permissive and just-in-time supervisor, as well as the synthesis of minimally permissive and just-after-time supervisor, are proposed. Results are also specialised to non-decreasing solutions, because only such supervisors can be realised in practice. The inherent issue of rationality raised recently is discussed. An illustration of concepts and results is presented through an example of a flexible manufacturing system.

Learning styles and approaches to learning among medical undergraduates and postgraduates

PubMed Central

2013-01-01

Background The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. Methods We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. Results A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners. Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. Conclusions The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period. PMID:23521845

Learning styles and approaches to learning among medical undergraduates and postgraduates.

PubMed

Samarakoon, Lasitha; Fernando, Tharanga; Rodrigo, Chaturaka

2013-03-25

The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners.Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period.

Finding and defining the natural automata acting in living plants: Toward the synthetic biology for robotics and informatics in vivo

PubMed Central

Kawano, Tomonori; Bouteau, François; Mancuso, Stefano

2012-01-01

The automata theory is the mathematical study of abstract machines commonly studied in the theoretical computer science and highly interdisciplinary fields that combine the natural sciences and the theoretical computer science. In the present review article, as the chemical and biological basis for natural computing or informatics, some plants, plant cells or plant-derived molecules involved in signaling are listed and classified as natural sequential machines (namely, the Mealy machines or Moore machines) or finite state automata. By defining the actions (states and transition functions) of these natural automata, the similarity between the computational data processing and plant decision-making processes became obvious. Finally, their putative roles as the parts for plant-based computing or robotic systems are discussed. PMID:23336016

Long-Term Memory: A State-Space Approach

ERIC Educational Resources Information Center

Kiss, George R.

1972-01-01

Some salient concepts derived from the information sciences and currently used in theories of human memory are critically reviewed. The application of automata theory is proposed as a new approach in this field. The approach is illustrated by applying it to verbal memory. (Author)

Linking Action Learning and Inter-Organisational Learning: The Learning Journey Approach

ERIC Educational Resources Information Center

Schumacher, Thomas

2015-01-01

The article presents and illustrates the learning journey (LJ)--a new management development approach to inter-organisational learning based on observation, reflection and problem-solving. The LJ involves managers from different organisations and applies key concepts of action learning and systemic organisational development. Made up of…

An authenticated image encryption scheme based on chaotic maps and memory cellular automata

NASA Astrophysics Data System (ADS)

Bakhshandeh, Atieh; Eslami, Ziba

2013-06-01

This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.

Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results

NASA Astrophysics Data System (ADS)

Iannone, G.; Troisi, A.

2013-05-01

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

NASA Astrophysics Data System (ADS)

Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

2017-09-01

The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.

Mathematical Models of Elementary Mathematics Learning and Performance. Final Report.

ERIC Educational Resources Information Center

Suppes, Patrick

This project was concerned with the development of mathematical models of elementary mathematics learning and performance. Probabilistic finite automata and register machines with a finite number of registers were developed as models and extensively tested with data arising from the elementary-mathematics strand curriculum developed by the…

Toward a Social Approach to Learning in Community Service Learning

ERIC Educational Resources Information Center

Cooks, Leda; Scharrer, Erica; Paredes, Mari Castaneda

2004-01-01

The authors describe a social approach to learning in community service learning that extends the contributions of three theoretical bodies of scholarship on learning: social constructionism, critical pedagogy, and community service learning. Building on the assumptions about learning described in each of these areas, engagement, identity, and…

A Cellular Automata Model of Bone Formation

PubMed Central

Van Scoy, Gabrielle K.; George, Estee L.; Asantewaa, Flora Opoku; Kerns, Lucy; Saunders, Marnie M.; Prieto-Langarica, Alicia

2017-01-01

Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model. PMID:28189632

A cellular automata model of bone formation.

PubMed

Van Scoy, Gabrielle K; George, Estee L; Opoku Asantewaa, Flora; Kerns, Lucy; Saunders, Marnie M; Prieto-Langarica, Alicia

2017-04-01

Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model. Copyright © 2017 Elsevier Inc. All rights reserved.

Approaches to Learning and Kolb's Learning Styles of Undergraduates with Better Grades

NASA Astrophysics Data System (ADS)

Almeida, Patrícia; Teixeira-Dias, José Joaquim; Martinho, Mariana; Balasooriya, Chinthaka

The purpose of this study is to investigate if the teaching, learning and assessment strategies conceived and implemented in a higher education chemistry course promote the development of conceptual understanding, as intended. Thus, our aim is to analyse the learning styles and the approaches to learning of chemistry undergraduates with better grades. The overall results show that the students with better grades possess the assimilator learning style, that is usually associated to the archetypal chemist. Moreover, the students with the highest grades revealed a conception of learning emphasising understanding. However, these students diverged both in their learning approaches and in their preferences for teaching strategies. The majority of students adopted a deep approach or a combination of a deep and a strategic approach, but half of them revealed their preference for teaching-centred strategies.

Modelling robot's behaviour using finite automata

NASA Astrophysics Data System (ADS)

Janošek, Michal; Žáček, Jaroslav

2017-07-01

This paper proposes a model of a robot's behaviour described by finite automata. We split robot's knowledge into several knowledge bases which are used by the inference mechanism of the robot's expert system to make a logic deduction. Each knowledgebase is dedicated to the particular behaviour domain and the finite automaton helps us switching among these knowledge bases with the respect of actual situation. Our goal is to simplify and reduce complexity of one big knowledgebase splitting it into several pieces. The advantage of this model is that we can easily add new behaviour by adding new knowledgebase and add this behaviour into the finite automaton and define necessary states and transitions.

Combining cellular automata and Lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition.

PubMed

Alemani, Davide; Pappalardo, Francesco; Pennisi, Marzio; Motta, Santo; Brusic, Vladimir

2012-02-28

In the last decades the Lattice Boltzmann method (LB) has been successfully used to simulate a variety of processes. The LB model describes the microscopic processes occurring at the cellular level and the macroscopic processes occurring at the continuum level with a unique function, the probability distribution function. Recently, it has been tried to couple deterministic approaches with probabilistic cellular automata (probabilistic CA) methods with the aim to model temporal evolution of tumor growths and three dimensional spatial evolution, obtaining hybrid methodologies. Despite the good results attained by CA-PDE methods, there is one important issue which has not been completely solved: the intrinsic stochastic nature of the interactions at the interface between cellular (microscopic) and continuum (macroscopic) level. CA methods are able to cope with the stochastic phenomena because of their probabilistic nature, while PDE methods are fully deterministic. Even if the coupling is mathematically correct, there could be important statistical effects that could be missed by the PDE approach. For such a reason, to be able to develop and manage a model that takes into account all these three level of complexity (cellular, molecular and continuum), we believe that PDE should be replaced with a statistic and stochastic model based on the numerical discretization of the Boltzmann equation: The Lattice Boltzmann (LB) method. In this work we introduce a new hybrid method to simulate tumor growth and immune system, by applying Cellular Automata Lattice Boltzmann (CA-LB) approach. Copyright © 2011 Elsevier B.V. All rights reserved.

A novel chaotic based image encryption using a hybrid model of deoxyribonucleic acid and cellular automata

NASA Astrophysics Data System (ADS)

Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi

2015-08-01

Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.

Stair evacuation simulation based on cellular automata considering evacuees’ walk preferences

NASA Astrophysics Data System (ADS)

Ding, Ning; Zhang, Hui; Chen, Tao; Peter, B. Luh

2015-06-01

As a physical model, the cellular automata (CA) model is widely used in many areas, such as stair evacuation. However, existing CA models do not consider evacuees’ walk preferences nor psychological status, and the structure of the basic model is unapplicable for the stair structure. This paper is to improve the stair evacuation simulation by addressing these issues, and a new cellular automata model is established. Several evacuees’ walk preference and how evacuee’s psychology influences their behaviors are introduced into this model. Evacuees’ speeds will be influenced by these features. To validate this simulation, two fire drills held in two high-rise buildings are video-recorded. It is found that the simulation results are similar to the fire drill results. The structure of this model is simple, and it is easy to further develop and utilize in different buildings with various kinds of occupants. Project supported by the National Basic Research Program of China (Grant No. 2012CB719705) and the National Natural Science Foundation of China (Grant Nos. 91224008, 91024032, and 71373139).

Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

NASA Astrophysics Data System (ADS)

Jokar Arsanjani, Jamal; Helbich, Marco; Kainz, Wolfgang; Darvishi Boloorani, Ali

2013-04-01

This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.

Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Snider, Gregory

2000-03-01

Quantum-dot Cellular Automata (QCA) [1] is a promising architecture which employs quantum dots for digital computation. It is a revolutionary approach that holds the promise of high device density and low power dissipation. A basic QCA cell consists of four quantum dots coupled capacitively and by tunnel barriers. The cell is biased to contain two excess electrons within the four dots, which are forced to opposite "corners" of the four-dot cell by mutual Coulomb repulsion. These two possible polarization states of the cell will represent logic "0" and "1". Properly arranged, arrays of these basic cells can implement Boolean logic functions. Experimental results from functional QCA devices built of nanoscale metal dots defined by tunnel barriers will be presented. The experimental devices to be presented consist of Al islands, which we will call quantum dots, interconnected by tunnel junctions and lithographically defined capacitors. Aluminum/ aluminum-oxide/aluminum tunnel junctions were fabricated using a standard e-beam lithography and shadow evaporation technique. The experiments were performed in a dilution refrigerator at a temperature of 70 mK. The operation of a cell is evaluated by direct measurements of the charge state of dots within a cell as the input voltage is changed. The experimental demonstration of a functioning cell will be presented. A line of three cells demonstrates that there are no metastable switching states in a line of cells. A QCA majority gate will also be presented, which is a programmable AND/OR gate and represents the basic building block of QCA systems. The results of recent experiments will be presented. 1. C.S. Lent, P.D. Tougaw, W. Porod, and G.H. Bernstein, Nanotechnology, 4, 49 (1993).

Stochastic cellular automata model of cell migration, proliferation and differentiation: validation with in vitro cultures of muscle satellite cells.

PubMed

Garijo, N; Manzano, R; Osta, R; Perez, M A

2012-12-07

Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving fluid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cellular automata and epidemiological models with spatial dependence

NASA Astrophysics Data System (ADS)

Fuentes, M. A.; Kuperman, M. N.

We present a cellular automata model developed to study the evolution of an infectivity nucleus in several conditions and for two kinds of epidemiologically different diseases. We analyse the role of the model parameters, concerning the epidemiological and demographic aspects of the problem, and of the evolution rules in relation to the spread of such infectious diseases, the arising of periodic temporal modulations related to the infectivity and recovery fronts, and the evolution of travelling waves. Among the obtained results we find analogies to endemic situations and pandemics.

Mammogram segmentation using maximal cell strength updation in cellular automata.

PubMed

Anitha, J; Peter, J Dinesh

2015-08-01

Breast cancer is the most frequently diagnosed type of cancer among women. Mammogram is one of the most effective tools for early detection of the breast cancer. Various computer-aided systems have been introduced to detect the breast cancer from mammogram images. In a computer-aided diagnosis system, detection and segmentation of breast masses from the background tissues is an important issue. In this paper, an automatic segmentation method is proposed to identify and segment the suspicious mass regions of mammogram using a modified transition rule named maximal cell strength updation in cellular automata (CA). In coarse-level segmentation, the proposed method performs an adaptive global thresholding based on the histogram peak analysis to obtain the rough region of interest. An automatic seed point selection is proposed using gray-level co-occurrence matrix-based sum average feature in the coarse segmented image. Finally, the method utilizes CA with the identified initial seed point and the modified transition rule to segment the mass region. The proposed approach is evaluated over the dataset of 70 mammograms with mass from mini-MIAS database. Experimental results show that the proposed approach yields promising results to segment the mass region in the mammograms with the sensitivity of 92.25% and accuracy of 93.48%.

Decentralized learning in Markov games.

PubMed

Vrancx, Peter; Verbeeck, Katja; Nowé, Ann

2008-08-01

Learning automata (LA) were recently shown to be valuable tools for designing multiagent reinforcement learning algorithms. One of the principal contributions of the LA theory is that a set of decentralized independent LA is able to control a finite Markov chain with unknown transition probabilities and rewards. In this paper, we propose to extend this algorithm to Markov games--a straightforward extension of single-agent Markov decision problems to distributed multiagent decision problems. We show that under the same ergodic assumptions of the original theorem, the extended algorithm will converge to a pure equilibrium point between agent policies.

On Matrices, Automata, and Double Counting

NASA Astrophysics Data System (ADS)

Beldiceanu, Nicolas; Carlsson, Mats; Flener, Pierre; Pearson, Justin

Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variables M, with the same constraint defined by a finite-state automaton A on each row of M and a global cardinality constraint gcc on each column of M. We give two methods for deriving, by double counting, necessary conditions on the cardinality variables of the gcc constraints from the automaton A. The first method yields linear necessary conditions and simple arithmetic constraints. The second method introduces the cardinality automaton, which abstracts the overall behaviour of all the row automata and can be encoded by a set of linear constraints. We evaluate the impact of our methods on a large set of nurse rostering problem instances.

Approach to Learning of Sub-Degree Students in Hong Kong

ERIC Educational Resources Information Center

Chan, Yiu Man; Chan, Christine Mei Sheung

2010-01-01

The learning approaches and learning experiences of 404 sub-degree students were assessed by using a Study Process Questionnaire and a Learning Experience Questionnaire. While the learning approaches in this study meant whether students used a deep learning or surface learning approach, the learning experiences referred to students' perceptions…

Hybrid automata models of cardiac ventricular electrophysiology for real-time computational applications.

PubMed

Andalam, Sidharta; Ramanna, Harshavardhan; Malik, Avinash; Roop, Parthasarathi; Patel, Nitish; Trew, Mark L

2016-08-01

Virtual heart models have been proposed for closed loop validation of safety-critical embedded medical devices, such as pacemakers. These models must react in real-time to off-the-shelf medical devices. Real-time performance can be obtained by implementing models in computer hardware, and methods of compiling classes of Hybrid Automata (HA) onto FPGA have been developed. Models of ventricular cardiac cell electrophysiology have been described using HA which capture the complex nonlinear behavior of biological systems. However, many models that have been used for closed-loop validation of pacemakers are highly abstract and do not capture important characteristics of the dynamic rate response. We developed a new HA model of cardiac cells which captures dynamic behavior and we implemented the model in hardware. This potentially enables modeling the heart with over 1 million dynamic cells, making the approach ideal for closed loop testing of medical devices.

Learning Process Questionnaire Manual. Student Approaches to Learning and Studying.

ERIC Educational Resources Information Center

Biggs, John B.

This manual describes the theory behind the Learning Process Questionnaire (LPQ) used in Australia and defines what the subscale and scale scores mean. The LPQ is a 36-item self-report questionnaire that yields scores on three basic motives for learning and three learning strategies, and on the approaches to learning that are formed by these…

Assessing the Impact of Learning Environments on Students' Approaches to Learning: Comparing Conventional and Action Learning Designs

ERIC Educational Resources Information Center

Wilson, Keithia; Fowler, Jane

2005-01-01

This study investigated whether students' approaches to learning were influenced by the design of university courses. Pre- and post-evaluations of the approaches to learning of the same group of students concurrently enrolled in a conventional course (lectures and tutorials) and an action learning-based course (project work, learning groups) were…

Modeling of urban growth using cellular automata (CA) optimized by Particle Swarm Optimization (PSO)

NASA Astrophysics Data System (ADS)

Khalilnia, M. H.; Ghaemirad, T.; Abbaspour, R. A.

2013-09-01

In this paper, two satellite images of Tehran, the capital city of Iran, which were taken by TM and ETM+ for years 1988 and 2010 are used as the base information layers to study the changes in urban patterns of this metropolis. The patterns of urban growth for the city of Tehran are extracted in a period of twelve years using cellular automata setting the logistic regression functions as transition functions. Furthermore, the weighting coefficients of parameters affecting the urban growth, i.e. distance from urban centers, distance from rural centers, distance from agricultural centers, and neighborhood effects were selected using PSO. In order to evaluate the results of the prediction, the percent correct match index is calculated. According to the results, by combining optimization techniques with cellular automata model, the urban growth patterns can be predicted with accuracy up to 75 %.

Evolution of Cellular Automata toward a LIFE-Like Rule Guided by 1/ƒ Noise

NASA Astrophysics Data System (ADS)

Ninagawa, Shigeru

There is evidence in favor of a relationship between the presence of 1/ƒ noise and computational universality in cellular automata. To confirm the relationship, we search for two-dimensional cellular automata with a 1/ƒ power spectrum by means of genetic algorithms. The power spectrum is calculated from the evolution of the state of the cell, starting from a random initial configuration. The fitness is estimated by the power spectrum with consideration of the spectral similarity to the 1/ƒ spectrum. The result shows that the rule with the highest fitness over the most runs exhibits a 1/ƒ type spectrum and its transition function and behavior are quite similar to those of the Game of Life, which is known to be a computationally universal cellular automaton. These results support the relationship between the presence of 1/ƒ noise and computational universality.

A dynamically reconfigurable logic cell: from artificial neural networks to quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Naqvi, Syed Rameez; Akram, Tallha; Iqbal, Saba; Haider, Sajjad Ali; Kamran, Muhammad; Muhammad, Nazeer

2018-02-01

Considering the lack of optimization support for Quantum-dot Cellular Automata, we propose a dynamically reconfigurable logic cell capable of implementing various logic operations by means of artificial neural networks. The cell can be reconfigured to any 2-input combinational logic gate by altering the strength of connections, called weights and biases. We demonstrate how these cells may appositely be organized to perform multi-bit arithmetic and logic operations. The proposed work is important in that it gives a standard implementation of an 8-bit arithmetic and logic unit for quantum-dot cellular automata with minimal area and latency overhead. We also compare the proposed design with a few existing arithmetic and logic units, and show that it is more area efficient than any equivalent available in literature. Furthermore, the design is adaptable to 16, 32, and 64 bit architectures.

Simulation of elastic wave propagation using cellular automata and peridynamics, and comparison with experiments

DOE PAGES

Nishawala, Vinesh V.; Ostoja-Starzewski, Martin; Leamy, Michael J.; ...

2015-09-10

Peridynamics is a non-local continuum mechanics formulation that can handle spatial discontinuities as the governing equations are integro-differential equations which do not involve gradients such as strains and deformation rates. This paper employs bond-based peridynamics. Cellular Automata is a local computational method which, in its rectangular variant on interior domains, is mathematically equivalent to the central difference finite difference method. However, cellular automata does not require the derivation of the governing partial differential equations and provides for common boundary conditions based on physical reasoning. Both methodologies are used to solve a half-space subjected to a normal load, known as Lamb’smore » Problem. The results are compared with theoretical solution from classical elasticity and experimental results. Furthermore, this paper is used to validate our implementation of these methods.« less

Evaluation of the dispersion effect in through movement bicycles at signalized intersection via cellular automata simulation

NASA Astrophysics Data System (ADS)

Jiang, Hang; Ma, Yongjian; Jiang, Lin; Chen, Guozhou; Wang, Dongwei

2018-05-01

At signalized intersection areas, bicycle traffic presents a dispersion feature which may influence the movements of vehicles during peak period. The primary objective of this study is to simulate the dispersion effect in through-movement bicycle traffic at intersection areas and evaluate its influence on through-movement traffic. A cellular automata (CA) model is developed and validated to simulate the operations of through-movement bicycle traffic departing from two types of intersection approaches. Simulation results show that bicycles benefit from the dispersion effect when they depart from the approach with an exclusive right-turn vehicle lane. But when bicycles travel from the approach with a shared right-turn and through vehicle lane, the dispersion effect will result in friction interference and block interference on through-movement vehicles. Bicycle interferences reduce the vehicle speed and increase the delay of through-movement vehicles. The policy implications in regard to the dispersion effect from two types of approaches are discussed to improve the performance of through-movement traffic operations at signalized intersections.

Evoked prior learning experience and approach to learning as predictors of academic achievement.

PubMed

Trigwell, Keith; Ashwin, Paul; Millan, Elena S

2013-09-01

In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students' perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. To investigate how students' evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. A 77-item questionnaire was used to gather students' self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was

ChemApproach: Validation of a Questionnaire to Assess the Learning Approaches of Chemistry Students

ERIC Educational Resources Information Center

Lastusaari, Mika; Laakkonen, Eero; Murtonen, Mari

2016-01-01

The theory of learning approaches has proven to be one of the most powerful theories explaining university students' learning. However, learning approaches are sensitive to the situation and the content of learning. Chemistry has its own specific features that should be considered when exploring chemistry students' learning habits, specifically…

A Janus-Faced Approach to Learning. A Critical Discussion of Habermas' Pragmatic Approach

ERIC Educational Resources Information Center

Italia, Salvatore

2017-01-01

A realist approach to learning is what I propose here. This is based on a non-epistemic dimension whose presence is a necessary assumption for a concept of learning of a life-world as complementary to learning within a life-world. I develop my approach in opposition to Jürgen Habermas' pragmatic approach, which seems to lack of something from a…

A novel FPGA-programmable switch matrix interconnection element in quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Hashemi, Sara; Rahimi Azghadi, Mostafa; Zakerolhosseini, Ali; Navi, Keivan

2015-04-01

The Quantum-dot cellular automata (QCA) is a novel nanotechnology, promising extra low-power, extremely dense and very high-speed structure for the construction of logical circuits at a nanoscale. In this paper, initially previous works on QCA-based FPGA's routing elements are investigated, and then an efficient, symmetric and reliable QCA programmable switch matrix (PSM) interconnection element is introduced. This element has a simple structure and offers a complete routing capability. It is implemented using a bottom-up design approach that starts from a dense and high-speed 2:1 multiplexer and utilise it to build the target PSM interconnection element. In this study, simulations of the proposed circuits are carried out using QCAdesigner, a layout and simulation tool for QCA circuits. The results demonstrate high efficiency of the proposed designs in QCA-based FPGA routing.

Dengue fever spreading based on probabilistic cellular automata with two lattices

NASA Astrophysics Data System (ADS)

Pereira, F. M. M.; Schimit, P. H. T.

2018-06-01

Modeling and simulation of mosquito-borne diseases have gained attention due to a growing incidence in tropical countries in the past few years. Here, we study the dengue spreading in a population modeled by cellular automata, where there are two lattices to model the human-mosquitointeraction: one lattice for human individuals, and one lattice for mosquitoes in order to enable different dynamics in populations. The disease considered is the dengue fever with one, two or three different serotypes coexisting in population. Although many regions exhibit the incidence of only one serotype, here we set a complete framework to also study the occurrence of two and three serotypes at the same time in a population. Furthermore, the flexibility of the model allows its use to other mosquito-borne diseases, like chikungunya, yellow fever and malaria. An approximation of the cellular automata is proposed in terms of ordinary differential equations; the spreading of mosquitoes is studied and the influence of some model parameters are analyzed with numerical simulations. Finally, a method to combat dengue spreading is simulated based on a reduction of mosquito birth and mosquito bites in population.

PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.

PubMed

Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold

2016-01-21

The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. Copyright © 2015 Elsevier Ltd. All rights reserved.

A new distributed systems scheduling algorithm: a swarm intelligence approach

NASA Astrophysics Data System (ADS)

Haghi Kashani, Mostafa; Sarvizadeh, Raheleh; Jameii, Mahdi

2011-12-01

The scheduling problem in distributed systems is known as an NP-complete problem, and methods based on heuristic or metaheuristic search have been proposed to obtain optimal and suboptimal solutions. The task scheduling is a key factor for distributed systems to gain better performance. In this paper, an efficient method based on memetic algorithm is developed to solve the problem of distributed systems scheduling. With regard to load balancing efficiently, Artificial Bee Colony (ABC) has been applied as local search in the proposed memetic algorithm. The proposed method has been compared to existing memetic-Based approach in which Learning Automata method has been used as local search. The results demonstrated that the proposed method outperform the above mentioned method in terms of communication cost.

Using Cellular Automata for Parking Recommendations in Smart Environments

PubMed Central

Horng, Gwo-Jiun

2014-01-01

In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space. PMID:25153671

From QCA (Quantum Cellular Automata) to Organocatalytic Reactions with Stabilized Carbenium Ions.

PubMed

Gualandi, Andrea; Mengozzi, Luca; Manoni, Elisabetta; Giorgio Cozzi, Pier

2016-06-01

What do quantum cellular automata (QCA), "on water" reactions, and SN 1-type organocatalytic transformations have in common? The link between these distant arguments is the practical access to useful intermediates and key products through the use of stabilized carbenium ions. Over 10 years, starting with a carbenium ion bearing a ferrocenyl group, to the 1,3-benzodithiolylium carbenium ion, our group has exploited the use of these intermediates in useful and practical synthetic transformations. In particular, we have applied the use of carbenium ions to stereoselective organocatalytic alkylation reactions, showing a possible solution for the "holy grail of organocatalysis". Examples of the use of these quite stabilized intermediates are now also considered in organometallic chemistry. On the other hand, the stable carbenium ions are also applied to tailored molecules adapted to quantum cellular automata, a new possible paradigm for computation. Carbenium ions are not a problem, they can be a/the solution! © 2016 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Heutagogy: An alternative practice based learning approach.

PubMed

Bhoyrub, John; Hurley, John; Neilson, Gavin R; Ramsay, Mike; Smith, Margaret

2010-11-01

Education has explored and utilised multiple approaches in attempts to enhance the learning and teaching opportunities available to adult learners. Traditional pedagogy has been both directly and indirectly affected by andragogy and transformational learning, consequently widening our understandings and approaches toward view teaching and learning. Within the context of nurse education, a major challenge has been to effectively apply these educational approaches to the complex, unpredictable and challenging environment of practice based learning. While not offered as a panacea to such challenges, heutagogy is offered in this discussion paper as an emerging and potentially highly congruent educational framework to place around practice based learning. Being an emergent theory its known conceptual underpinnings and possible applications to nurse education need to be explored and theoretically applied. Through placing the adult learner at the foreground of grasping learning opportunities as they unpredictability emerge from a sometimes chaotic environment, heutagogy can be argued as offering the potential to minimise many of the well published difficulties of coordinating practice with faculty teaching and learning. Copyright © 2010 Elsevier Ltd. All rights reserved.

Construction of phase diagrams for nanoscaled Ising thin films on the honeycomb lattice using cellular automata simulation approach

NASA Astrophysics Data System (ADS)

Ghaemi, Mehrdad; Javadi, Nabi

2017-11-01

The phase diagrams of the three-layer Ising model on the honeycomb lattice with a diluted surface have been constructed using the probabilistic cellular automata based on Glauber algorithm. The effects of the exchange interactions on the phase diagrams have been investigated. A general mathematical expression for the critical temperature is obtained in terms of relative coupling r = J1/J and Δs = (Js/J) - 1, where J and Js represent the nearest neighbor coupling within inner- and surface-layers, respectively, and each magnetic site in the surface-layer is coupled with the nearest neighbor site in the inner-layer via the exchange coupling J1. In the case of antiferromagnetic coupling between surface-layer and inner-layer, system reveals many interesting phenomena, such as the possibility of existence of compensation line before the critical temperature.

All-DNA finite-state automata with finite memory

PubMed Central

Wang, Zhen-Gang; Elbaz, Johann; Remacle, F.; Levine, R. D.; Willner, Itamar

2010-01-01

Biomolecular logic devices can be applied for sensing and nano-medicine. We built three DNA tweezers that are activated by the inputs H+/OH-; ; nucleic acid linker/complementary antilinker to yield a 16-states finite-state automaton. The outputs of the automata are the configuration of the respective tweezers (opened or closed) determined by observing fluorescence from a fluorophore/quencher pair at the end of the arms of the tweezers. The system exhibits a memory because each current state and output depend not only on the source configuration but also on past states and inputs. PMID:21135212

Growth and Decay in Life-Like Cellular Automata

NASA Astrophysics Data System (ADS)

Eppstein, David

Since the study of life began, many have asked: is it unique in the universe, or are there other interesting forms of life elsewhere? Before we can answer that question, we should ask others: What makes life special? If we happen across another system with life-like behavior, how would we be able to recognize it? We are speaking, of course, of the mathematical systems of cellular automata, of the fascinating patterns that have been discovered and engineered in Conway's Game of Life, and of the possible existence of other cellular automaton rules with equally complex behavior to that of Life.

A Cognitive Approach to e-Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greitzer, Frank L.; Rice, Douglas M.; Eaton, Sharon L.

2003-12-01

Like traditional classroom instruction, distributed learning derives from passive training paradigms. Just as student-centered classroom teaching methods have been applied over several decades of classroom instruction, interactive approaches have been encouraged for distributed learning. While implementation of multimedia-based training features may appear to produce active learning, sophisticated use of multimedia features alone does not necessarily enhance learning. This paper describes the results of applying cognitive science principles to enhance learning in a student-centered, distributed learning environment, and lessons learned in developing and delivering this training. Our interactive, scenario-based approach exploits multimedia technology within a systematic, cognitive framework for learning. Themore » basis of the application of cognitive principles is the innovative use of multimedia technology to implement interaction elements. These simple multimedia interactions, which are used to support new concepts, are later combined with other interaction elements to create more complex, integrated practical exercises. This technology-based approach may be applied in a variety of training and education contexts, but is especially well suited for training of equipment operators and maintainers. For example, it has been used in a sustainment training application for the United States Army's Combat Support System Automated Information System Interface (CAISI). The CAISI provides a wireless communications capability that allows various logistics systems to communicate across the battlefield. Based on classroom training material developed by the CAISI Project Office, the Pacific Northwest National Laboratory designed and developed an interactive, student-centered distributed-learning application for CAISI operators and maintainers. This web-based CAISI training system is also distributed on CD media for use on individual computers, and material developed for the

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning

PubMed Central

Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie

2016-01-01

Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807

Fuzzy automata and pattern matching

NASA Technical Reports Server (NTRS)

Setzer, C. B.; Warsi, N. A.

1986-01-01

A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.

Students' Questions: Building a Bridge between Kolb's Learning Styles and Approaches to Learning

ERIC Educational Resources Information Center

de Jesus, Helena T. Pedrosa; Almeida, Patricia Albergaria; Teixeira-Dias, Jose Joaquim; Watts, Mike

2006-01-01

Purpose: The purpose of this study is to identify the types of questions that students ask during the learning of chemistry; discuss the role of students' questions in the process of constructing knowledge, and investigate the relationship between students' questions, approaches to learning, and learning styles. Design/methodology/approach: The…

Do Learning Approaches of Medical Students Affect Their Satisfaction with Problem-Based Learning?

ERIC Educational Resources Information Center

Gurpinar, Erol; Kulac, Esin; Tetik, Cihat; Akdogan, Ilgaz; Mamakli, Sumer

2013-01-01

The aim of this research was to determine the satisfaction of medical students with problem-based learning (PBL) and their approaches to learning to investigate the effect of learning approaches on their levels of satisfaction. The study group was composed of medical students from three different universities, which apply PBL at different levels…

Investigative Primary Science: A Problem-Based Learning Approach

ERIC Educational Resources Information Center

Etherington, Matthew B.

2011-01-01

This study reports on the success of using a problem-based learning approach (PBL) as a pedagogical mode of learning open inquiry science within a traditional four-year undergraduate elementary teacher education program. In 2010, a problem-based learning approach to teaching primary science replaced the traditional content driven syllabus. During…

The scientific learning approach using multimedia-based maze game to improve learning outcomes

NASA Astrophysics Data System (ADS)

Setiawan, Wawan; Hafitriani, Sarah; Prabawa, Harsa Wara

2016-02-01

The objective of curriculum 2013 is to improve the quality of education in Indonesia, which leads to improving the quality of learning. The scientific approach and supported empowerment media is one approach as massaged of curriculum 2013. This research aims to design a labyrinth game based multimedia and apply in the scientific learning approach. This study was conducted in one of the Vocational School in Subjects of Computer Network on 2 (two) classes of experimental and control. The method used Mix Method Research (MMR) which combines qualitative in multimedia design, and quantitative in the study of learning impact. The results of a survey showed that the general of vocational students like of network topology material (68%), like multimedia (74%), and in particular, like interactive multimedia games and flash (84%). Multimediabased maze game developed good eligibility based on media and material aspects of each value 840% and 82%. Student learning outcomes as a result of using a scientific approach to learning with a multimediabased labyrinth game increase with an average of gain index about (58%) and higher than conventional multimedia with index average gain of 0.41 (41%). Based on these results the scientific approach to learning by using multimediabased labyrinth game can improve the quality of learning and increase understanding of students. Multimedia of learning based labyrinth game, which developed, got a positive response from the students with a good qualification level (75%).

An Automation Framework for Neural Nets that Learn

ERIC Educational Resources Information Center

Kilmer, W. L.; Arbib, M. A.

1973-01-01

A discussion of several types of formal neurons, many of whose functions are modifiable by their own input stimuli. The language of finite automata is used to mathematicize the problem of adaptation sufficiently to remove some ambiguities of Brindley's approach. (Author)

Learning Families: Intergenerational Approach to Literacy Teaching and Learning

ERIC Educational Resources Information Center

Hanemann, Ulrike, Ed.

2015-01-01

Within a learning family, every member is a lifelong learner. A family literacy and learning approach is more likely to break the intergenerational cycle of low education and inadequate literacy skills, particularly among disadvantaged families and communities. The selection of case studies presented in this compilation show that for an…

Energy dissipation dataset for reversible logic gates in quantum dot-cellular automata.

PubMed

Bahar, Ali Newaz; Rahman, Mohammad Maksudur; Nahid, Nur Mohammad; Hassan, Md Kamrul

2017-02-01

This paper presents an energy dissipation dataset of different reversible logic gates in quantum-dot cellular automata. The proposed circuits have been designed and verified using QCADesigner simulator. Besides, the energy dissipation has been calculated under three different tunneling energy level at temperature T =2 K. For estimating the energy dissipation of proposed gates; QCAPro tool has been employed.

Design of a fault-tolerant reversible control unit in molecular quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Bahadori, Golnaz; Houshmand, Monireh; Zomorodi-Moghadam, Mariam

Quantum-dot cellular automata (QCA) is a promising emerging nanotechnology that has been attracting considerable attention due to its small feature size, ultra-low power consuming, and high clock frequency. Therefore, there have been many efforts to design computational units based on this technology. Despite these advantages of the QCA-based nanotechnologies, their implementation is susceptible to a high error rate. On the other hand, using the reversible computing leads to zero bit erasures and no energy dissipation. As the reversible computation does not lose information, the fault detection happens with a high probability. In this paper, first we propose a fault-tolerant control unit using reversible gates which improves on the previous design. The proposed design is then synthesized to the QCA technology and is simulated by the QCADesigner tool. Evaluation results indicate the performance of the proposed approach.

Economic Gardening through Entrepreneurship Education: A Service-Learning Approach

ERIC Educational Resources Information Center

Desplaces, David E.; Wergeles, Fred; McGuigan, Patrick

2009-01-01

This article outlines the implementation of a service-learning approach in an entrepreneurship programme using an "economic gardening" strategy. Economic Gardening through Service-Learning (EGS-L) is an approach to economic development that helps local businesses and students grow through a facilitated learning process. Learning is made possible…

Reversible Flip-Flops in Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Rad, Samaneh Kazemi; Heikalabad, Saeed Rasouli

2017-09-01

Quantum-dot cellular automata is a new technology to design the efficient combinational and sequential circuits at the nano-scale. This technology has many desirable advantages compared to the CMOS technology such as low power consumption, less occupation area and low latency. These features make it suitable for use in flip-flop design. In this paper, with knowing the characteristics of reversible logic, we design new structures for flip-flops. The operations of these structures are evaluated with QCADesigner Version 2.0.3 simulator. In addition, we calculate the power dissipation of these structures by QCAPro tool. The results illustrated that proposed structures are efficient compared to the previous ones.

Wolfram's class IV automata and a good life

NASA Astrophysics Data System (ADS)

McIntosh, Harold V.

1990-09-01

A comprehensive discussion of Wolfram's four classes of cellular automata is given, with the intention of relating them to Conway's criteria for a good game of Life. Although it is known that such classifications cannot be entirely rigorous, much information about the behavior of an automaton can be gleaned from the statistical properties of its transition table. Still more information can be deduced from the mean field approximation to its state densities, in particular, from the distribution of horizontal and diagonal tangents of the latter. In turn these characteristics can be related to the presence or absence of certain loops in the de Bruijn diagram of the automaton.

Fire and Heat Spreading Model Based on Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Samartsev, A. A.; Rezchikov, A. F.; Kushnikov, V. A.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikov, O. V.; Shulga, T. E.; Tverdokhlebov, V. A.; Fominykh, D. S.

2018-05-01

The distinctive feature of the proposed fire and heat spreading model in premises is the reduction of the computational complexity due to the use of the theory of cellular automata with probability rules of behavior. The possibilities and prospects of using this model in practice are noted. The proposed model has a simple mechanism of integration with agent-based evacuation models. The joint use of these models could improve floor plans and reduce the time of evacuation from premises during fires.

A solution to the biodiversity paradox by logical deterministic cellular automata.

PubMed

Kalmykov, Lev V; Kalmykov, Vyacheslav L

2015-06-01

The paradox of biological diversity is the key problem of theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. The principle is important as the basis for ecological theory. On a relatively simple model we show a mechanism of indefinite coexistence of complete competitors which violates the known formulations of the competitive exclusion principle. This mechanism is based on timely recovery of limiting resources and their spatio-temporal allocation between competitors. Because of limitations of the black-box modeling there was a problem to formulate the exclusion principle correctly. Our white-box multiscale model of two-species competition is based on logical deterministic individual-based cellular automata. This approach provides an automatic deductive inference on the basis of a system of axioms, and gives a direct insight into mechanisms of the studied system. It is one of the most promising methods of artificial intelligence. We reformulate and generalize the competitive exclusion principle and explain why this formulation provides a solution of the biodiversity paradox. In addition, we propose a principle of competitive coexistence.

Traffic jam dynamics in stochastic cellular automata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagel, K.; Schreckenberg, M.

1995-09-01

Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA)more » and in NRW (Germany) for large scale microsimulations of network traffic.« less

Quantum cellular automata

NASA Astrophysics Data System (ADS)

Porod, Wolfgang; Lent, Craig S.; Bernstein, Gary H.

1994-06-01

The Notre Dame group has developed a new paradigm for ultra-dense and ultra-fast information processing in nanoelectronic systems. These Quantum Cellular Automata (QCA's) are the first concrete proposal for a technology based on arrays of coupled quantum dots. The basic building block of these cellular arrays is the Notre Dame Logic Cell, as it has been called in the literature. The phenomenon of Coulomb exclusion, which is a synergistic interplay of quantum confinement and Coulomb interaction, leads to a bistable behavior of each cell which makes possible their use in large-scale cellular arrays. The physical interaction between neighboring cells has been exploited to implement logic functions. New functionality may be achieved in this fashion, and the Notre Dame group invented a versatile majority logic gate. In a series of papers, the feasibility of QCA wires, wire crossing, inverters, and Boolean logic gates was demonstrated. A major finding is that all logic functions may be integrated in a hierarchial fashion which allows the design of complicated QCA structures. The most complicated system which was simulated to date is a one-bit full adder consisting of some 200 cells. In addition to exploring these new concepts, efforts are under way to physically realize such structures both in semiconductor and metal systems. Extensive modeling work of semiconductor quantum dot structures has helped identify optimum design parameters for QCA experimental implementations.

Learning Approaches, Demographic Factors to Predict Academic Outcomes

ERIC Educational Resources Information Center

Nguyen, Tuan Minh

2016-01-01

Purpose: The purpose of this paper is to predict academic outcome in math and math-related subjects using learning approaches and demographic factors. Design/Methodology/Approach: ASSIST was used as the instrumentation to measure learning approaches. The study was conducted in the International University of Vietnam with 616 participants. An…

Efficient dual approach to distance metric learning.

PubMed

Shen, Chunhua; Kim, Junae; Liu, Fayao; Wang, Lei; van den Hengel, Anton

2014-02-01

Distance metric learning is of fundamental interest in machine learning because the employed distance metric can significantly affect the performance of many learning methods. Quadratic Mahalanobis metric learning is a popular approach to the problem, but typically requires solving a semidefinite programming (SDP) problem, which is computationally expensive. The worst case complexity of solving an SDP problem involving a matrix variable of size D×D with O(D) linear constraints is about O(D(6.5)) using interior-point methods, where D is the dimension of the input data. Thus, the interior-point methods only practically solve problems exhibiting less than a few thousand variables. Because the number of variables is D(D+1)/2, this implies a limit upon the size of problem that can practically be solved around a few hundred dimensions. The complexity of the popular quadratic Mahalanobis metric learning approach thus limits the size of problem to which metric learning can be applied. Here, we propose a significantly more efficient and scalable approach to the metric learning problem based on the Lagrange dual formulation of the problem. The proposed formulation is much simpler to implement, and therefore allows much larger Mahalanobis metric learning problems to be solved. The time complexity of the proposed method is roughly O(D(3)), which is significantly lower than that of the SDP approach. Experiments on a variety of data sets demonstrate that the proposed method achieves an accuracy comparable with the state of the art, but is applicable to significantly larger problems. We also show that the proposed method can be applied to solve more general Frobenius norm regularized SDP problems approximately.

On complexity and homogeneity measures in predicting biological aggressiveness of prostate cancer; Implication of the cellular automata model of tumor growth.

PubMed

Tanase, Mihai; Waliszewski, Przemyslaw

2015-12-01

We propose a novel approach for the quantitative evaluation of aggressiveness in prostate carcinomas. The spatial distribution of cancer cell nuclei was characterized by the global spatial fractal dimensions D0, D1, and D2. Two hundred eighteen prostate carcinomas were stratified into the classes of equivalence using results of ROC analysis. A simulation of the cellular automata mix defined a theoretical frame for a specific geometric representation of the cell nuclei distribution called a local structure correlation diagram (LSCD). The LSCD and dispersion Hd were computed for each carcinoma. Data mining generated some quantitative criteria describing tumor aggressiveness. Alterations in tumor architecture along progression were associated with some changes in both shape and the quantitative characteristics of the LSCD consistent with those in the automata mix model. Low-grade prostate carcinomas with low complexity and very low biological aggressiveness are defined by the condition D0 < 1.545 and Hd < 38. High-grade carcinomas with high complexity and very high biological aggressiveness are defined by the condition D0 > 1.764 and Hd < 38. The novel homogeneity measure Hd identifies carcinomas with very low aggressiveness within the class of complexity C1 or carcinomas with very high aggressiveness in the class C7. © 2015 Wiley Periodicals, Inc.

Understanding Fatty Acid Metabolism through an Active Learning Approach

ERIC Educational Resources Information Center

Fardilha, M.; Schrader, M.; da Cruz e Silva, O. A. B.; da Cruz e Silva, E. F.

2010-01-01

A multi-method active learning approach (MALA) was implemented in the Medical Biochemistry teaching unit of the Biomedical Sciences degree at the University of Aveiro, using problem-based learning as the main learning approach. In this type of learning strategy, students are involved beyond the mere exercise of being taught by listening. Less…

Undergraduate students' earth science learning: relationships among conceptions, approaches, and learning self-efficacy in Taiwan

NASA Astrophysics Data System (ADS)

Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen

2016-06-01

In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to explore the relationships among undergraduates' conceptions of, approaches to, and self-efficacy for learning earth science by adopting the structural equation modeling technique. A total of 268 Taiwanese undergraduates (144 females) participated in this study. Three instruments were modified to assess the students' conceptions of, approaches to, and self-efficacy for learning earth science. The results indicated that students' conceptions of learning made a significant contribution to their approaches to learning, which were consequently correlated with their learning self-efficacy. More specifically, students with stronger agreement that learning earth science involves applying the knowledge and skills learned to unknown problems were prone to possess higher confidence in learning earth science. Moreover, students viewing earth science learning as understanding earth science knowledge were more likely to adopt meaningful strategies to learn earth science, and hence expressed a higher sense of self-efficacy. Based on the results, practical implications and suggestions for future research are discussed.

The Neurona at Home project: Simulating a large-scale cellular automata brain in a distributed computing environment

NASA Astrophysics Data System (ADS)

Acedo, L.; Villanueva-Oller, J.; Moraño, J. A.; Villanueva, R.-J.

2013-01-01

The Berkeley Open Infrastructure for Network Computing (BOINC) has become the standard open source solution for grid computing in the Internet. Volunteers use their computers to complete an small part of the task assigned by a dedicated server. We have developed a BOINC project called Neurona@Home whose objective is to simulate a cellular automata random network with, at least, one million neurons. We consider a cellular automata version of the integrate-and-fire model in which excitatory and inhibitory nodes can activate or deactivate neighbor nodes according to a set of probabilistic rules. Our aim is to determine the phase diagram of the model and its behaviour and to compare it with the electroencephalographic signals measured in real brains.

Development of Scientific Approach Based on Discovery Learning Module

NASA Astrophysics Data System (ADS)

Ellizar, E.; Hardeli, H.; Beltris, S.; Suharni, R.

2018-04-01

Scientific Approach is a learning process, designed to make the students actively construct their own knowledge through stages of scientific method. The scientific approach in learning process can be done by using learning modules. One of the learning model is discovery based learning. Discovery learning is a learning model for the valuable things in learning through various activities, such as observation, experience, and reasoning. In fact, the students’ activity to construct their own knowledge were not optimal. It’s because the available learning modules were not in line with the scientific approach. The purpose of this study was to develop a scientific approach discovery based learning module on Acid Based, also on electrolyte and non-electrolyte solution. The developing process of this chemistry modules use the Plomp Model with three main stages. The stages are preliminary research, prototyping stage, and the assessment stage. The subject of this research was the 10th and 11th Grade of Senior High School students (SMAN 2 Padang). Validation were tested by the experts of Chemistry lecturers and teachers. Practicality of these modules had been tested through questionnaire. The effectiveness had been tested through experimental procedure by comparing student achievement between experiment and control groups. Based on the findings, it can be concluded that the developed scientific approach discovery based learning module significantly improve the students’ learning in Acid-based and Electrolyte solution. The result of the data analysis indicated that the chemistry module was valid in content, construct, and presentation. Chemistry module also has a good practicality level and also accordance with the available time. This chemistry module was also effective, because it can help the students to understand the content of the learning material. That’s proved by the result of learning student. Based on the result can conclude that chemistry module based on

Assessing Students' Development in Learning Approaches According to Initial Learning Profiles: A Person-Oriented Perspective

ERIC Educational Resources Information Center

Vanthournout, Gert; Coertjens, Liesje; Gijbels, David; Donche, Vincent; Van Petegem, Peter

2013-01-01

Research regarding the development of students' learning approaches have at times reported unexpected or lack of expected changes. The current study explores the idea of differential developments in learning approaches according to students' initial learning profiles as a possible explanation for these outcomes. A learning profile is conceived as…

Mixed-Valence Molecular Unit for Quantum Cellular Automata: Beyond the Born-Oppenheimer Paradigm through the Symmetry-Assisted Vibronic Approach.

PubMed

Clemente-Juan, Juan Modesto; Palii, Andrew; Coronado, Eugenio; Tsukerblat, Boris

2016-08-09

In this article, we focus on the electron-vibrational problem of the tetrameric mixed-valence (MV) complexes proposed for implementation as four-dot molecular quantum cellular automata (mQCA).1 Although the adiabatic approximation explored in ref 2 is an appropriate tool for the qualitative analysis of the basic characteristics of mQCA, like vibronic trapping of the electrons encoding binary information and cell-cell response, it loses its accuracy providing moderate vibronic coupling and fails in the description of the discrete pattern of the vibronic levels. Therefore, a precise solution of the quantum-mechanical vibronic problem is of primary importance for the evaluation of the shapes of the electron transfer optical absorption bands and quantitative analysis of the main parameters of tetrameric quantum cells. Here, we go beyond the Born-Oppenheimer paradigm and present a solution of the quantum-mechanical pseudo Jahn-Teller (JT) vibronic problem in bielectronic MV species (exemplified by the tetra-ruthenium complexes) based on the recently developed symmetry-assisted approach.3,4 The mathematical approach to the vibronic eigenproblem takes into consideration the point symmetry basis, and therefore, the total matrix of the JT Hamiltonian is blocked to the maximum extent. The submatrices correspond to the irreducible representations (irreps) of the point group. With this tool, we also extend the theory of the mQCA cell beyond the limit of prevailing Coulomb repulsion in the electronic pair (adopted in ref 2), and therefore, the general pseudo-JT problems for spin-singlet ((1)B1g, 2(1)A1g, (1)B2g, (1)Eu) ⊗ (b1g + eu) and spin-triplet states ((3)A2g, (3)B1g, 2(3)Eu) ⊗ (b1g + eu) in a square-planar bielectronic system are solved. The obtained symmetry-adapted electron-vibrational functions are employed for the calculation of the profiles (shape functions) of the charge transfer absorption bands in the tetrameric MV complexes and for the discussion of the

Game-theoretic cooperativity in networks of self-interested units

NASA Astrophysics Data System (ADS)

Barto, Andrew G.

1986-08-01

The behavior of theoretical neural networks is often described in terms of competition and cooperation. I present an approach to network learning that is related to game and team problems in which competition and cooperation have more technical meanings. I briefly describe the application of stochastic learning automata to game and team problems and then present an adaptive element that is a synthesis of aspects of stochastic learning automata and typical neuron-like adaptive elements. These elements act as self-interested agents that work toward improving their performance with respect to their individual preference orderings. Networks of these elements can solve a variety of team decision problems, some of which take the form of layered networks in which the ``hidden units'' become appropriate functional components as they attempt to improve their own payoffs.

Machine Learning Approaches for Clinical Psychology and Psychiatry.

PubMed

Dwyer, Dominic B; Falkai, Peter; Koutsouleris, Nikolaos

2018-05-07

Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an accessible understanding of why this approach is important for future practice given its potential to augment decisions associated with the diagnosis, prognosis, and treatment of people suffering from mental illness using clinical and biological data. To this end, the limitations of current statistical paradigms in mental health research are critiqued, and an introduction is provided to critical machine learning methods used in clinical studies. A selective literature review is then presented aiming to reinforce the usefulness of machine learning methods and provide evidence of their potential. In the context of promising initial results, the current limitations of machine learning approaches are addressed, and considerations for future clinical translation are outlined.

Interrelations between Self-Efficacy and Learning Approaches: A Developmental Approach

ERIC Educational Resources Information Center

Phan, Huy Phuong

2011-01-01

Two major theoretical frameworks in educational psychology, namely student approaches to learning (SAL) and self-efficacy have been used extensively to explain and predict students' learning and academic achievement. There is a substantial body of research studies, for example, that documents the positive interrelations between individuals'…

Strategies for using cellular automata to locate constrained layer damping on vibrating structures

NASA Astrophysics Data System (ADS)

Chia, C. M.; Rongong, J. A.; Worden, K.

2009-01-01

It is often hard to optimise constrained layer damping (CLD) for structures more complicated than simple beams and plates as its performance depends on its location, the shape of the applied patch, the mode shapes of the structure and the material properties. This paper considers the use of cellular automata (CA) in conjunction with finite element analysis to obtain an efficient coverage of CLD on structures. The effectiveness of several different sets of local rules governing the CA are compared against each other for a structure with known optimum coverage—namely a plate. The algorithm which attempts to replicate most closely known optimal configurations is considered the most successful. This algorithm is then used to generate an efficient CLD treatment that targets several modes of a curved composite panel. To validate the modelling approaches used, results are also presented of a comparison between theoretical and experimentally obtained modal properties of the damped curved panel.

a Predator-Prey Model Based on the Fully Parallel Cellular Automata

NASA Astrophysics Data System (ADS)

He, Mingfeng; Ruan, Hongbo; Yu, Changliang

We presented a predator-prey lattice model containing moveable wolves and sheep, which are characterized by Penna double bit strings. Sexual reproduction and child-care strategies are considered. To implement this model in an efficient way, we build a fully parallel Cellular Automata based on a new definition of the neighborhood. We show the roles played by the initial densities of the populations, the mutation rate and the linear size of the lattice in the evolution of this model.

Mosquito population dynamics from cellular automata-based simulation

NASA Astrophysics Data System (ADS)

Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning

2016-02-01

In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-based model for simulating dispersal of the vector. In simulation, each individual vector is able to move to other grid based on a random walk. Our model is also capable to represent immunity factor for each grid. We simulate the model to evaluate its correctness. Based on the simulations, we can conclude that our model is correct. However, our model need to be improved to find a realistic parameters to match real data.

A cellular automata model of SARS epidemic spreading

NASA Astrophysics Data System (ADS)

Xu, Tian; Zhang, Peipei; Su, Beibei; Jiang, Yumai; He, Da-Ren

2004-03-01

We suggest a cellular automata model for a simulation on the process of SARS spreading in Beijing. Suppose a number of people are located in a two-dimensional lattice, in which a certain portion belongs to immune and others belong to acceptive. In every time step each of the acceptive people may become ill with a certain probability if one of his 8 neighbors is a SARS patient. At same time all the people have another possibility to change their positions. Each patient will recover or die after different number of days. A recovered patient becomes immune. The numerical simulation by this model leads to the results, which are in a good agreement with the practical statistical data.

Mathematics Literacy on Problem Based Learning with Indonesian Realistic Mathematics Education Approach Assisted E-Learning Edmodo

NASA Astrophysics Data System (ADS)

Wardono; Waluya, S. B.; Mariani, Scolastika; Candra D, S.

2016-02-01

This study aims to find out that there are differences in mathematical literacy ability in content Change and Relationship class VII Junior High School 19, Semarang by Problem Based Learning (PBL) model with an Indonesian Realistic Mathematics Education (called Pendidikan Matematika Realistik Indonesia or PMRI in Indonesia) approach assisted Elearning Edmodo, PBL with a PMRI approach, and expository; to know whether the group of students with learning PBL models with PMRI approach and assisted E-learning Edmodo can improve mathematics literacy; to know that the quality of learning PBL models with a PMRI approach assisted E-learning Edmodo has a good category; to describe the difficulties of students in working the problems of mathematical literacy ability oriented PISA. This research is a mixed methods study. The population was seventh grade students of Junior High School 19, Semarang Indonesia. Sample selection is done by random sampling so that the selected experimental class 1, class 2 and the control experiment. Data collected by the methods of documentation, tests and interviews. From the results of this study showed average mathematics literacy ability of students in the group PBL models with a PMRI approach assisted E-learning Edmodo better than average mathematics literacy ability of students in the group PBL models with a PMRI approach and better than average mathematics literacy ability of students in the expository models; Mathematics literacy ability in the class using the PBL model with a PMRI approach assisted E-learning Edmodo have increased and the improvement of mathematics literacy ability is higher than the improvement of mathematics literacy ability of class that uses the model of PBL learning with PMRI approach and is higher than the improvement of mathematics literacy ability of class that uses the expository models; The quality of learning using PBL models with a PMRI approach assisted E-learning Edmodo have very good category.

Project Management Approaches for Online Learning Design

ERIC Educational Resources Information Center

Eby, Gulsun; Yuzer, T. Volkan

2013-01-01

Developments in online learning and its design are areas that continue to grow in order to enhance students' learning environments and experiences. However, in the implementation of new technologies, the importance of properly and fairly overseeing these courses is often undervalued. "Project Management Approaches for Online Learning Design"…

Teaching of anatomical sciences: A blended learning approach.

PubMed

Khalil, Mohammed K; Abdel Meguid, Eiman M; Elkhider, Ihsan A

2018-04-01

Blended learning is the integration of different learning approaches, new technologies, and activities that combine traditional face-to-face teaching methods with authentic online methodologies. Although advances in educational technology have helped to expand the selection of different pedagogies, the teaching of anatomical sciences has been challenged by implementation difficulties and other limitations. These challenges are reported to include lack of time, costs, and lack of qualified teachers. Easy access to online information and advances in technology make it possible to resolve these limitations by adopting blended learning approaches. Blended learning strategies have been shown to improve students' academic performance, motivation, attitude, and satisfaction, and to provide convenient and flexible learning. Implementation of blended learning strategies has also proved cost effective. This article provides a theoretical foundation for blended learning and proposes a validated framework for the design of blended learning activities in the teaching and learning of anatomical sciences. Clin. Anat. 31:323-329, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Machine Learning Approaches in Cardiovascular Imaging.

PubMed

Henglin, Mir; Stein, Gillian; Hushcha, Pavel V; Snoek, Jasper; Wiltschko, Alexander B; Cheng, Susan

2017-10-01

Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine learning methods can now address data-related problems ranging from simple analytic queries of existing measurement data to the more complex challenges involved in analyzing raw images. To date, machine learning has been used in 2 broad and highly interconnected areas: automation of tasks that might otherwise be performed by a human and generation of clinically important new knowledge. Most cardiovascular imaging studies have focused on task-oriented problems, but more studies involving algorithms aimed at generating new clinical insights are emerging. Continued expansion in the size and dimensionality of cardiovascular imaging databases is driving strong interest in applying powerful deep learning methods, in particular, to analyze these data. Overall, the most effective approaches will require an investment in the resources needed to appropriately prepare such large data sets for analyses. Notwithstanding current technical and logistical challenges, machine learning and especially deep learning methods have much to offer and will substantially impact the future practice and science of cardiovascular imaging. © 2017 American Heart Association, Inc.

Comparing Team Learning Approaches through the Lens of Activity Theory

ERIC Educational Resources Information Center

Park, Sunyoung; Cho, Yonjoo; Yoon, Seung Won; Han, Heeyoung

2013-01-01

Purpose: The purpose of this study is to examine the distinctive features of three team learning approaches (action learning, problem-based learning, and project-based learning), compare and contrast them, and discuss implications for practice and research. Design/methodology/approach: The authors used Torraco's integrative literature review…

Learning styles and approaches to learning mathematics of students majoring in elementary education: a three-year study.

PubMed

Alkhateeb, Haitham M; Mji, Andile

2009-10-01

The goal of this 3-yr. study was to explore the learning styles and approaches to learning mathematics of elementary education majors. Two questionnaires, the Learning Style Inventory and the Approaches to Learning Mathematics Questionnaire, were administered to 149 women and 32 men (M = 20.1 yr., SD. = 2.1; range = 18-31). All were in their first or second years of college and enrolled in Mathematics for Elementary School Teachers at a Midwestern U.S. university. Results on the Learning Style Inventory indicated that a majority scored as either Accommodators, i.e., they primarily followed learning modes involving Active Experimentation and Concrete Experience, or as Divergers, i.e., approaching learning by focusing on Concrete Experience and Reflective Observation. A weak but statistically significant association was observed on the Approaches questionnaire between the Surface Approach and Reflective Observation.

Learner Performance in Multimedia Learning Arrangements: An Analysis across Instructional Approaches

ERIC Educational Resources Information Center

Eysink, Tessa H. S.; de Jong, Ton; Berthold, Kirsten; Kolloffel, Bas; Opfermann, Maria; Wouters, Pieter

2009-01-01

In this study, the authors compared four multimedia learning arrangements differing in instructional approach on effectiveness and efficiency for learning: (a) hypermedia learning, (b) observational learning, (c) self-explanation-based learning, and (d) inquiry learning. The approaches all advocate learners' active attitude toward the learning…

Bridging the Gaps between Learning and Teaching through Recognition of Students' Learning Approaches: A Case Study

ERIC Educational Resources Information Center

Malie, Senian; Akir, Oriah

2012-01-01

Learning approaches, learning methods and learning environments have different effects on students? academic performance. However, they are not the sole factors that impact students? academic achievement. The aims of this research are three-fold: to determine the learning approaches preferred by most students and the impact of the learning…

Subgrouping Automata: automatic sequence subgrouping using phylogenetic tree-based optimum subgrouping algorithm.

PubMed

Seo, Joo-Hyun; Park, Jihyang; Kim, Eun-Mi; Kim, Juhan; Joo, Keehyoung; Lee, Jooyoung; Kim, Byung-Gee

2014-02-01

Sequence subgrouping for a given sequence set can enable various informative tasks such as the functional discrimination of sequence subsets and the functional inference of unknown sequences. Because an identity threshold for sequence subgrouping may vary according to the given sequence set, it is highly desirable to construct a robust subgrouping algorithm which automatically identifies an optimal identity threshold and generates subgroups for a given sequence set. To meet this end, an automatic sequence subgrouping method, named 'Subgrouping Automata' was constructed. Firstly, tree analysis module analyzes the structure of tree and calculates the all possible subgroups in each node. Sequence similarity analysis module calculates average sequence similarity for all subgroups in each node. Representative sequence generation module finds a representative sequence using profile analysis and self-scoring for each subgroup. For all nodes, average sequence similarities are calculated and 'Subgrouping Automata' searches a node showing statistically maximum sequence similarity increase using Student's t-value. A node showing the maximum t-value, which gives the most significant differences in average sequence similarity between two adjacent nodes, is determined as an optimum subgrouping node in the phylogenetic tree. Further analysis showed that the optimum subgrouping node from SA prevents under-subgrouping and over-subgrouping. Copyright © 2013. Published by Elsevier Ltd.

Cellular automata model for traffic flow at intersections in internet of vehicles

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

2018-03-01

Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

Self-regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison Between Professional Training and English Learning.

PubMed

Tseng, Min-Chen; Chen, Chia-Cheng

2017-06-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between students' professional training and English learning. The participants consisted of 344 arts majors. The Academic Self-Regulation Questionnaire and the Revised Learning Process Questionnaire were adopted to examine students' self-regulatory behaviors and their approaches to learning. The results show that a positive and significant correlation was found in students' self-regulatory behaviors between professional training and English learning. The results indicated that increases in using self-regulatory behaviors in professional training were associated with increases in applying self-regulatory behaviors in learning English. Seeking assistance, self-evaluation, and planning and organizing were significant predictors for learning English. In addition, arts students used the deep approach more often than the surface approach in both their professional training and English learning. A positive correlation was found in DA, whereas a negative correlation was shown in SA between students' self-regulatory behaviors and their approaches to learning. Students with high self-regulation adopted a deep approach, and they applied the surface approach less in professional training and English learning. In addition, a SEM model confirmed that DA had a positive influence; however, SA had a negative influence on self-regulatory behaviors.

Preliminary cellular-automata forecast of permit activity from 1998 to 2010, Idaho and Western Montana

USGS Publications Warehouse

Raines, G.L.; Zientek, M.L.; Causey, J.D.; Boleneus, D.E.

2002-01-01

For public land management in Idaho and western Montana, the U.S. Forest Service (USFS) has requested that the U.S. Geological Survey (USGS) predict where mineral-related activity will occur in the next decade. Cellular automata provide an approach to simulation of this human activity. Cellular automata (CA) are defined by an array of cells, which evolve by a simple transition rule, the automaton. Based on exploration trends, we assume that future exploration will focus in areas of past exploration. Spatial-temporal information about mineral-related activity, that is permits issued by USFS and Bureau of Land Management (BLM) in the last decade, and spatial information about undiscovered resources, provide a basis to calibrate a CA. The CA implemented is a modified annealed voting rule that simulates mineral-related activity with spatial and temporal resolution of 1 mi2 and 1 year based on activity from 1989 to 1998. For this CA, the state of the economy and exploration technology is assumed constant for the next decade. The calibrated CA reproduces the 1989-1998-permit activity with an agreement of 94%, which increases to 98% within one year. Analysis of the confusion matrix and kappa correlation statistics indicates that the CA underestimates high activity and overestimates low activity. Spatially, the major differences between the actual and calculated activity are that the calculated activity occurs in a slightly larger number of small patches and is slightly more uneven than the actual activity. Using the calibrated CA in a Monte Carlo simulation projecting from 1998 to 2010, an estimate of the probability of mineral activity shows high levels of activity in Boise, Caribou, Elmore, Lincoln, and western Valley counties in Idaho and Beaverhead, Madison, and Stillwater counties in Montana, and generally low activity elsewhere. ?? 2002 International Association for Mathematical Geology.

In silico characterization of cell-cell interactions using a cellular automata model of cell culture.

PubMed

Kihara, Takanori; Kashitani, Kosuke; Miyake, Jun

2017-07-14

Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell-cell interactions using experimentally obtained images of cultured cells. We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 10 4 cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell-cell adhesion, and cell-cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell-cell adhesion and cell-cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell-cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell-cell adhesion and weak cell-cell contact inhibition. Simulated MSCs exhibited high cell-cell adhesion and positive cell-cell contact inhibition. Simulated A7r5 cells exhibited low cell-cell adhesion and strong cell-cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images. Our simulation approach is an easy method for evaluating the cell-cell interaction properties of cells.

Cells as strain-cued automata

NASA Astrophysics Data System (ADS)

Cox, Brian N.; Snead, Malcolm L.

2016-02-01

We argue in favor of representing living cells as automata and review demonstrations that autonomous cells can form patterns by responding to local variations in the strain fields that arise from their individual or collective motions. An autonomous cell's response to strain stimuli is assumed to be effected by internally-generated, internally-powered forces, which generally move the cell in directions other than those implied by external energy gradients. Evidence of cells acting as strain-cued automata have been inferred from patterns observed in nature and from experiments conducted in vitro. Simulations that mimic particular cases of pattern forming share the idealization that cells are assumed to pass information among themselves solely via mechanical boundary conditions, i.e., the tractions and displacements present at their membranes. This assumption opens three mechanisms for pattern formation in large cell populations: wavelike behavior, kinematic feedback in cell motility that can lead to sliding and rotational patterns, and directed migration during invasions. Wavelike behavior among ameloblast cells during amelogenesis (the formation of dental enamel) has been inferred from enamel microstructure, while strain waves in populations of epithelial cells have been observed in vitro. One hypothesized kinematic feedback mechanism, "enhanced shear motility", accounts successfully for the spontaneous formation of layered patterns during amelogenesis in the mouse incisor. Directed migration is exemplified by a theory of invader cells that sense and respond to the strains they themselves create in the host population as they invade it: analysis shows that the strain fields contain positional information that could aid the formation of cell network structures, stabilizing the slender geometry of branches and helping govern the frequency of branch bifurcation and branch coalescence (the formation of closed networks). In simulations of pattern formation in

Component-Based Approach in Learning Management System Development

ERIC Educational Resources Information Center

Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

2013-01-01

The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…

Integrated approaches to perceptual learning.

PubMed

Jacobs, Robert A

2010-04-01

New technologies and new ways of thinking have recently led to rapid expansions in the study of perceptual learning. We describe three themes shared by many of the nine articles included in this topic on Integrated Approaches to Perceptual Learning. First, perceptual learning cannot be studied on its own because it is closely linked to other aspects of cognition, such as attention, working memory, decision making, and conceptual knowledge. Second, perceptual learning is sensitive to both the stimulus properties of the environment in which an observer exists and to the properties of the tasks that the observer needs to perform. Moreover, the environmental and task properties can be characterized through their statistical regularities. Finally, the study of perceptual learning has important implications for society, including implications for science education and medical rehabilitation. Contributed articles relevant to each theme are summarized. Copyright © 2010 Cognitive Science Society, Inc.

Group investigation with scientific approach in mathematics learning

NASA Astrophysics Data System (ADS)

Indarti, D.; Mardiyana; Pramudya, I.

2018-03-01

The aim of this research is to find out the effect of learning model toward mathematics achievement. This research is quasi-experimental research. The population of research is all VII grade students of Karanganyar regency in the academic year of 2016/2017. The sample of this research was taken using stratified cluster random sampling technique. Data collection was done based on mathematics achievement test. The data analysis technique used one-way ANOVA following the normality test with liliefors method and homogeneity test with Bartlett method. The results of this research is the mathematics learning using Group Investigation learning model with scientific approach produces the better mathematics learning achievement than learning with conventional model on material of quadrilateral. Group Investigation learning model with scientific approach can be used by the teachers in mathematics learning, especially in the material of quadrilateral, which is can improve the mathematics achievement.

Pre-Service English Teachers in Blended Learning Environment in Respect to Their Learning Approaches

ERIC Educational Resources Information Center

Yilmaz, M. Betul; Orhan, Feza

2010-01-01

Blended learning environment (BLE) is increasingly used in the world, especially in university degrees and it is based on integrating web-based learning and face-to-face (FTF) learning environments. Besides integrating different learning environments, BLE also addresses to students with different learning approaches. The "learning…

A cellular automata model of land cover change to integrate urban growth with open space conservation

EPA Science Inventory

The preservation of riparian zones and other environmentally sensitive areas has long been recognized as one of the most cost-effective methods of managing stormwater and providing a broad range of ecosystem services. In this research, a cellular automata (CA)—Markov chain model ...

A Guided Discovery Approach for Learning Metabolic Pathways

ERIC Educational Resources Information Center

Schultz, Emeric

2005-01-01

Learning the wealth of information in metabolic pathways is both challenging and overwhelming for students. A step-by-step guided discovery approach to the learning of the chemical steps in gluconeogenesis and the citric acid cycle is described. This approach starts from concepts the student already knows, develops these further in a logical…

The detection and stabilisation of limit cycle for deterministic finite automata

NASA Astrophysics Data System (ADS)

Han, Xiaoguang; Chen, Zengqiang; Liu, Zhongxin; Zhang, Qing

2018-04-01

In this paper, the topological structure properties of deterministic finite automata (DFA), under the framework of the semi-tensor product of matrices, are investigated. First, the dynamics of DFA are converted into a new algebraic form as a discrete-time linear system by means of Boolean algebra. Using this algebraic description, the approach of calculating the limit cycles of different lengths is given. Second, we present two fundamental concepts, namely, domain of attraction of limit cycle and prereachability set. Based on the prereachability set, an explicit solution of calculating domain of attraction of a limit cycle is completely characterised. Third, we define the globally attractive limit cycle, and then the necessary and sufficient condition for verifying whether all state trajectories of a DFA enter a given limit cycle in a finite number of transitions is given. Fourth, the problem of whether a DFA can be stabilised to a limit cycle by the state feedback controller is discussed. Criteria for limit cycle-stabilisation are established. All state feedback controllers which implement the minimal length trajectories from each state to the limit cycle are obtained by using the proposed algorithm. Finally, an illustrative example is presented to show the theoretical results.

The relationship between learning preferences (styles and approaches) and learning outcomes among pre-clinical undergraduate medical students.

PubMed

Liew, Siaw-Cheok; Sidhu, Jagmohni; Barua, Ankur

2015-03-11

Learning styles and approaches of individual undergraduate medical students vary considerably and as a consequence, their learning needs also differ from one student to another. This study was conducted to identify different learning styles and approaches of pre-clinical, undergraduate medical students and also to determine the relationships of learning preferences with performances in the summative examinations. A cross-sectional study was conducted among randomly selected 419 pre-clinical, undergraduate medical students of the International Medical University (IMU) in Kuala Lumpur. The number of students from Year 2 was 217 while that from Year 3 was 202. The Visual, Auditory, Read/Write, Kinesthetic (VARK) and the Approaches and Study Skills Inventory for Students (ASSIST) questionnaires were used for data collection. This study revealed that 343 students (81.9%) had unimodal learning style, while the remaining 76 (18.1%) used a multimodal learning style. Among the unimodal learners, a majority (30.1%) were of Kinesthetic (K) type. Among the middle and high achievers in summative examinations, a majority had unimodal (Kinaesthetic) learning style (30.5%) and were also strategic/deep learners (79.4%). However, the learning styles and approaches did not contribute significantly towards the learning outcomes in summative examinations. A majority of the students in this study had Unimodal (Kinesthetic) learning style. The learning preferences (styles and approaches) did not contribute significantly to the learning outcomes. Future work to re-assess the viability of these learning preferences (styles and approaches) after the incorporation of teaching-learning instructions tailored specifically to the students will be beneficial to help medical teachers in facilitating students to become more capable learners.

Constructivist Learning Approach in Science Teaching

ERIC Educational Resources Information Center

Demirci, Cavide

2009-01-01

Constructivism is not a new concept. It has its roots in philosophy and has been applied to sociology and anthropology, as well as cognitive psychology and education. The aim of this research is to reveal if there is a significant difference between the means of achievement and retention learning scores of constructivist learning approach applied…

Index Theory of One Dimensional Quantum Walks and Cellular Automata

NASA Astrophysics Data System (ADS)

Gross, D.; Nesme, V.; Vogts, H.; Werner, R. F.

2012-03-01

If a one-dimensional quantum lattice system is subject to one step of a reversible discrete-time dynamics, it is intuitive that as much "quantum information" as moves into any given block of cells from the left, has to exit that block to the right. For two types of such systems — namely quantum walks and cellular automata — we make this intuition precise by defining an index, a quantity that measures the "net flow of quantum information" through the system. The index supplies a complete characterization of two properties of the discrete dynamics. First, two systems S 1, S 2 can be "pieced together", in the sense that there is a system S which acts like S 1 in one region and like S 2 in some other region, if and only if S 1 and S 2 have the same index. Second, the index labels connected components of such systems: equality of the index is necessary and sufficient for the existence of a continuous deformation of S 1 into S 2. In the case of quantum walks, the index is integer-valued, whereas for cellular automata, it takes values in the group of positive rationals. In both cases, the map {S mapsto ind S} is a group homomorphism if composition of the discrete dynamics is taken as the group law of the quantum systems. Systems with trivial index are precisely those which can be realized by partitioned unitaries, and the prototypes of systems with non-trivial index are shifts.

Design of Learning Objects for Concept Learning: Effects of Multimedia Learning Principles and an Instructional Approach

ERIC Educational Resources Information Center

Chiu, Thomas K. F.; Churchill, Daniel

2016-01-01

Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…

An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

PubMed

Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong

2012-10-01

In this paper, a novel lesion segmentation within breast ultrasound (BUS) image based on the cellular automata principle is proposed. Its energy transition function is formulated based on global image information difference and local image information difference using different energy transfer strategies. First, an energy decrease strategy is used for modeling the spatial relation information of pixels. For modeling global image information difference, a seed information comparison function is developed using an energy preserve strategy. Then, a texture information comparison function is proposed for considering local image difference in different regions, which is helpful for handling blurry boundaries. Moreover, two neighborhood systems (von Neumann and Moore neighborhood systems) are integrated as the evolution environment, and a similarity-based criterion is used for suppressing noise and reducing computation complexity. The proposed method was applied to 205 clinical BUS images for studying its characteristic and functionality, and several overlapping area error metrics and statistical evaluation methods are utilized for evaluating its performance. The experimental results demonstrate that the proposed method can handle BUS images with blurry boundaries and low contrast well and can segment breast lesions accurately and effectively.

Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

NASA Technical Reports Server (NTRS)

Gabrielian, Armen

1991-01-01

Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

Micro-simulation of vehicle conflicts involving right-turn vehicles at signalized intersections based on cellular automata.

PubMed

Chai, C; Wong, Y D

2014-02-01

At intersection, vehicles coming from different directions conflict with each other. Improper geometric design and signal settings at signalized intersection will increase occurrence of conflicts between road users and results in a reduction of the safety level. This study established a cellular automata (CA) model to simulate vehicular interactions involving right-turn vehicles (as similar to left-turn vehicles in US). Through various simulation scenarios for four case cross-intersections, the relationships between conflict occurrences involving right-turn vehicles with traffic volume and right-turn movement control strategies are analyzed. Impacts of traffic volume, permissive right-turn compared to red-amber-green (RAG) arrow, shared straight-through and right-turn lane as well as signal setting are estimated from simulation results. The simulation model is found to be able to provide reasonable assessment of conflicts through comparison of existed simulation approach and observed accidents. Through the proposed approach, prediction models for occurrences and severity of vehicle conflicts can be developed for various geometric layouts and traffic control strategies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Forward-Oriented Design for Learning: Illustrating the Approach

ERIC Educational Resources Information Center

Dimitriadis, Yannis; Goodyear, Peter

2013-01-01

This paper concerns sustainable approaches to design for learning, emphasising the need for designs to be able to thrive outside of the protective niches of project-based innovation. It builds on the "in medias res" framework and more specifically on a forward-oriented approach to design for learning: one that takes a pro-active design…

Exam Success at Undergraduate and Graduate-Entry Medical Schools: Is Learning Style or Learning Approach More Important? A Critical Review Exploring Links Between Academic Success, Learning Styles, and Learning Approaches Among School-Leaver Entry ("Traditional") and Graduate-Entry ("Nontraditional") Medical Students.

PubMed

Feeley, Anne-Marie; Biggerstaff, Deborah L

2015-01-01

PHENOMENON: The literature on learning styles over many years has been replete with debate and disagreement. Researchers have yet to elucidate exactly which underlying constructs are measured by the many learning styles questionnaires available. Some academics question whether learning styles exist at all. When it comes to establishing the value of learning styles for medical students, a further issue emerges. The demographics of medical students in the United Kingdom have changed in recent years, so past studies may not be applicable to students today. We wanted to answer a very simple, practical question: what can the literature on learning styles tell us that we can use to help today's medical students succeed academically at medical school? We conducted a literature review to synthesise the available evidence on how two different aspects of learning-the way in which students like to receive information in a learning environment (termed learning "styles") and the motivations that drive their learning (termed learning "approaches")-can impact on medical students' academic achievement. Our review confirms that although learning "styles" do not correlate with exam performance, learning "approaches" do: those with "strategic" and "deep" approaches to learning (i.e., motivated to do well and motivated to learn deeply respectively) perform consistently better in medical school examinations. Changes in medical school entrant demographics in the past decade have not altered these correlations. Optimistically, our review reveals that students' learning approaches can change and more adaptive approaches may be learned. Insights: For educators wishing to help medical students succeed academically, current evidence demonstrates that helping students develop their own positive learning approach using "growth mind-set" is a more effective (and more feasible) than attempting to alter students' learning styles. This conclusion holds true for both "traditional" and graduate

A Cellular Automata Model of Infection Control on Medical Implants

PubMed Central

Prieto-Langarica, Alicia; Kojouharov, Hristo; Chen-Charpentier, Benito; Tang, Liping

2011-01-01

S. epidermidis infections on medically implanted devices are a common problem in modern medicine due to the abundance of the bacteria. Once inside the body, S. epidermidis gather in communities called biofilms and can become extremely hard to eradicate, causing the patient serious complications. We simulate the complex S. epidermidis-Neutrophils interactions in order to determine the optimum conditions for the immune system to be able to contain the infection and avoid implant rejection. Our cellular automata model can also be used as a tool for determining the optimal amount of antibiotics for combating biofilm formation on medical implants. PMID:23543851

Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches

ERIC Educational Resources Information Center

Wang, Victor C. X.

2010-01-01

As adult learners and educators pioneer the use of technology in the new century, attention has been focused on developing strategic approaches to effectively integrate adult learning and technology in different learning environments. "Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches" provides innovative…

An image encryption algorithm based on 3D cellular automata and chaotic maps

NASA Astrophysics Data System (ADS)

Del Rey, A. Martín; Sánchez, G. Rodríguez

2015-05-01

A novel encryption algorithm to cipher digital images is presented in this work. The digital image is rendering into a three-dimensional (3D) lattice and the protocol consists of two phases: the confusion phase where 24 chaotic Cat maps are applied and the diffusion phase where a 3D cellular automata is evolved. The encryption method is shown to be secure against the most important cryptanalytic attacks.

Learning approaches and learning difficulties: a comparison of Indian and Nepali dental science students.

PubMed

Mayya, Shreemathi S; Rao, A Krishna; Ramnarayan, K

2002-11-01

This study explored the difference in learning approaches and difficulties of Nepali and Indian undergraduate students of dental science. A locally developed inventory was used to measure learning approach and learning difficulties. Data collected from 166 Indians and 69 Nepalis were compared. The scores on various scales of the inventory indicate that Nepalis are more fearful and less confident regarding examination and course completion and have significantly less positive perception about academic capability. Indian students scored significantly higher on motivation, interest, and deep processing. The language problem was significantly greater for Nepali students. Higher percentages of Nepalis experienced various academic and nonacademic problems. The study highlights the need to consider difference in learning approach among the students of health science courses that admit students from different academic, nonacademic, and cultural backgrounds.

Approach for Using Learner Satisfaction to Evaluate the Learning Adaptation Policy

ERIC Educational Resources Information Center

Jeghal, Adil; Oughdir, Lahcen; Tairi, Hamid; Radouane, Abdelhay

2016-01-01

The learning adaptation is a very important phase in a learning situation in human learning environments. This paper presents the authors' approach used to evaluate the effectiveness of learning adaptive systems. This approach is based on the analysis of learner satisfaction notices collected by a questionnaire on a learning situation; to analyze…

Problem Posing with Realistic Mathematics Education Approach in Geometry Learning

NASA Astrophysics Data System (ADS)

Mahendra, R.; Slamet, I.; Budiyono

2017-09-01

One of the difficulties of students in the learning of geometry is on the subject of plane that requires students to understand the abstract matter. The aim of this research is to determine the effect of Problem Posing learning model with Realistic Mathematics Education Approach in geometry learning. This quasi experimental research was conducted in one of the junior high schools in Karanganyar, Indonesia. The sample was taken using stratified cluster random sampling technique. The results of this research indicate that the model of Problem Posing learning with Realistic Mathematics Education Approach can improve students’ conceptual understanding significantly in geometry learning especially on plane topics. It is because students on the application of Problem Posing with Realistic Mathematics Education Approach are become to be active in constructing their knowledge, proposing, and problem solving in realistic, so it easier for students to understand concepts and solve the problems. Therefore, the model of Problem Posing learning with Realistic Mathematics Education Approach is appropriately applied in mathematics learning especially on geometry material. Furthermore, the impact can improve student achievement.

Looking at Learning Approaches from the Angle of Student Profiles

ERIC Educational Resources Information Center

Kyndt, Eva; Dochy, Filip; Struyven, Katrien; Cascallar, Eduardo

2012-01-01

This study starts with investigating the relation of perceived workload, motivation for learning and working memory capacity (WMC) with students' approaches to learning. Secondly, this study investigates if differences exist between different student profiles concerning their approach to the learning and the influence of workloads thereon. Results…

Approaches to Learning and Study Orchestrations in High School Students

ERIC Educational Resources Information Center

Cano, Francisco

2007-01-01

In the framework of the SAL (Students' approaches to learning) position, the learning experience (approaches to learning and study orchestrations) of 572 high school students was explored, examining its interrelationships with some personal and familial variables. Three major results emerged. First, links were found between family's intellectual…

Revising a Design Course from a Lecture Approach to a Project-Based Learning Approach

ERIC Educational Resources Information Center

Kunberger, Tanya

2013-01-01

In order to develop the evaluative skills necessary for successful performance of design, a senior, Geotechnical Engineering course was revised to immerse students in the complexity of the design process utilising a project-based learning (PBL) approach to instruction. The student-centred approach stresses self-directed group learning, which…

The Relationship between Learning Approaches of Prospective Teachers and Their Academic Achievement

ERIC Educational Resources Information Center

Gurlen, Eda; Turan, Sevgi; Senemoglu, Nuray

2013-01-01

To prepare for future professional challenges, prospective teachers should acquire the capabilities for independent learning. Prospective teachers should know how to learn effectively. In this article, prospective teachers' learning approaches, learning preference and the relationship between learning preference, learning approaches with…

Bioinformatics algorithm based on a parallel implementation of a machine learning approach using transducers

NASA Astrophysics Data System (ADS)

Roche-Lima, Abiel; Thulasiram, Ruppa K.

2012-02-01

Finite automata, in which each transition is augmented with an output label in addition to the familiar input label, are considered finite-state transducers. Transducers have been used to analyze some fundamental issues in bioinformatics. Weighted finite-state transducers have been proposed to pairwise alignments of DNA and protein sequences; as well as to develop kernels for computational biology. Machine learning algorithms for conditional transducers have been implemented and used for DNA sequence analysis. Transducer learning algorithms are based on conditional probability computation. It is calculated by using techniques, such as pair-database creation, normalization (with Maximum-Likelihood normalization) and parameters optimization (with Expectation-Maximization - EM). These techniques are intrinsically costly for computation, even worse when are applied to bioinformatics, because the databases sizes are large. In this work, we describe a parallel implementation of an algorithm to learn conditional transducers using these techniques. The algorithm is oriented to bioinformatics applications, such as alignments, phylogenetic trees, and other genome evolution studies. Indeed, several experiences were developed using the parallel and sequential algorithm on Westgrid (specifically, on the Breeze cluster). As results, we obtain that our parallel algorithm is scalable, because execution times are reduced considerably when the data size parameter is increased. Another experience is developed by changing precision parameter. In this case, we obtain smaller execution times using the parallel algorithm. Finally, number of threads used to execute the parallel algorithm on the Breezy cluster is changed. In this last experience, we obtain as result that speedup is considerably increased when more threads are used; however there is a convergence for number of threads equal to or greater than 16.

Investigating the Efficiency of Scenario Based Learning and Reflective Learning Approaches in Teacher Education

ERIC Educational Resources Information Center

Hursen, Cigdem; Fasli, Funda Gezer

2017-01-01

The main purpose of this research is to investigate the efficiency of scenario based learning and reflective learning approaches in teacher education. The impact of applications of scenario based learning and reflective learning on prospective teachers' academic achievement and views regarding application and professional self-competence…

Algebraic properties of automata associated to Petri nets and applications to computation in biological systems.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Biochemical and genetic regulatory networks are often modeled by Petri nets. We study the algebraic structure of the computations carried out by Petri nets from the viewpoint of algebraic automata theory. Petri nets comprise a formalized graphical modeling language, often used to describe computation occurring within biochemical and genetic regulatory networks, but the semantics may be interpreted in different ways in the realm of automata. Therefore, there are several different ways to turn a Petri net into a state-transition automaton. Here, we systematically investigate different conversion methods and describe cases where they may yield radically different algebraic structures. We focus on the existence of group components of the corresponding transformation semigroups, as these reflect symmetries of the computation occurring within the biological system under study. Results are illustrated by applications to the Petri net modelling of intermediary metabolism. Petri nets with inhibition are shown to be computationally rich, regardless of the particular interpretation method. Along these lines we provide a mathematical argument suggesting a reason for the apparent all-pervasiveness of inhibitory connections in living systems.

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

E-learning and blended learning in textile engineering education: a closed feedback loop approach

NASA Astrophysics Data System (ADS)

Charitopoulos, A.; Vassiliadis, S.; Rangoussi, M.; Koulouriotis, D.

2017-10-01

E-learning has gained a significant role in typical education and in professional training, thanks to the flexibility it offers to the time and location parameters of the education event framework. Purely e-learning scenarios are mostly limited either to Open University-type higher education institutions or to graduate level or professional degrees; blended learning scenarios are progressively becoming popular thanks to their balanced approach. The aim of the present work is to propose approaches that exploit the e-learning and the blended-learning scenarios for Textile Engineering education programmes, especially for multi-institutional ones. The “E-Team” European MSc degree programme organized by AUTEX is used as a case study. The proposed solution is based on (i) a free and open-source e-learning platform (moodle) and (ii) blended learning educational scenarios. Educational challenges addressed include student engagement, student error / failure handling, as well as collaborative learning promotion and support.

Science of learning is learning of science: why we need a dialectical approach to science education research

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael

2012-06-01

Research on learning science in informal settings and the formal (sometimes experimental) study of learning in classrooms or psychological laboratories tend to be separate domains, even drawing on different theories and methods. These differences make it difficult to compare knowing and learning observed in one paradigm/context with those observed in the other. Even more interestingly, the scientists studying science learning rarely consider their own learning in relation to the phenomena they study. A dialectical, reflexive approach to learning, however, would theorize the movement of an educational science (its learning and development) as a special and general case—subject matter and method—of the phenomenon of learning (in/of) science. In the dialectical approach to the study of science learning, therefore, subject matter, method, and theory fall together. This allows for a perspective in which not only disparate fields of study—school science learning and learning in everyday life—are integrated but also where the progress in the science of science learning coincides with its topic. Following the articulation of a contradictory situation on comparing learning in different settings, I describe the dialectical approach. As a way of providing a concrete example, I then trace the historical movement of my own research group as it simultaneously and alternately studied science learning in formal and informal settings. I conclude by recommending cultural-historical, dialectical approaches to learning and interaction analysis as a context for fruitful interdisciplinary research on science learning within and across different settings.

The Design of Fault Tolerant Quantum Dot Cellular Automata Based Logic

NASA Technical Reports Server (NTRS)

Armstrong, C. Duane; Humphreys, William M.; Fijany, Amir

2002-01-01

As transistor geometries are reduced, quantum effects begin to dominate device performance. At some point, transistors cease to have the properties that make them useful computational components. New computing elements must be developed in order to keep pace with Moore s Law. Quantum dot cellular automata (QCA) represent an alternative paradigm to transistor-based logic. QCA architectures that are robust to manufacturing tolerances and defects must be developed. We are developing software that allows the exploration of fault tolerant QCA gate architectures by automating the specification, simulation, analysis and documentation processes.

Learning environment, approaches to learning and learning preferences: medical students versus general education students.

PubMed

Ullah, Raza

2016-05-01

The main objective of the study was to see whether medical students use more desirable approaches to studying than general education students. Survey method was used to collect data from both the medical students and the general education students. The survey of the medical students was carried out between January and March, 2012. The survey was administered to all the medical students present in lecture halls on day of data collection, while general education students were randomly selected from four subject areas at two universities. In total, 976 medical students and 912 general students participated in the study. Of the general students, 494(54%) were boys and 418(46%)were girls with an overall mean age of 20.53±1.77 years (range: 17-27 years). The medical students' perceptions of their learning environment and their learning preferences were broadly similar to that of general education students with the exception of workload. The medical students perceived the workload to be less appropriate (Mean = 2.06±0.72) than the students in general education (Mean = 2.84±0.90). The medical students were more likely to use the deep approach to studying (Mean = 3.66±0.59) than the students in general education (Mean = 3.16±0.91). The students in general education were slightly more likely to use the organized studying (Mean = 3.44±0.90) than the medical students (Mean =3.23±0.90). Both medical students and the students in general education tended to use the surface approaches along with other approaches to studying. There was not a great difference between the medical students and the students pursuing general education with regard to perceptions of the learning environment and approaches to learning.

Collective dynamics in heterogeneous networks of neuronal cellular automata

NASA Astrophysics Data System (ADS)

Manchanda, Kaustubh; Bose, Amitabha; Ramaswamy, Ramakrishna

2017-12-01

We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r - b - 1 refractory states, and can show 'spiking' or 'bursting' behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs-Rényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent.

A Study of Chaos in Cellular Automata

NASA Astrophysics Data System (ADS)

Kamilya, Supreeti; Das, Sukanta

This paper presents a study of chaos in one-dimensional cellular automata (CAs). The communication of information from one part of the system to another has been taken into consideration in this study. This communication is formalized as a binary relation over the set of cells. It is shown that this relation is an equivalence relation and all the cells form a single equivalence class when the cellular automaton (CA) is chaotic. However, the communication between two cells is sometimes blocked in some CAs by a subconfiguration which appears in between the cells during evolution. This blocking of communication by a subconfiguration has been analyzed in this paper with the help of de Bruijn graph. We identify two types of blocking — full and partial. Finally a parameter has been developed for the CAs. We show that the proposed parameter performs better than the existing parameters.

Towards a Standards-Based Approach to E-Learning Personalization Using Reusable Learning Objects.

ERIC Educational Resources Information Center

Conlan, Owen; Dagger, Declan; Wade, Vincent

E-Learning systems that produce personalized course offerings for the learner are often expensive, both from a time and financial perspective, to develop and maintain. Learning content personalized to a learners' cognitive preferences has been shown to produce more effective learning, however many approaches to realizing this form of…

An energy and cost efficient majority-based RAM cell in quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Khosroshahy, Milad Bagherian; Moaiyeri, Mohammad Hossein; Navi, Keivan; Bagherzadeh, Nader

Nanotechnologies, notably quantum-dot cellular automata, have achieved major attentions for their prominent features as compared to the conventional CMOS circuitry. Quantum-dot cellular automata, particularly owning to its considerable reduction in size, high switching speed and ultra-low energy consumption, is considered as a potential alternative for the CMOS technology. As the memory unit is one of the most essential components in a digital system, designing a well-optimized QCA random access memory (RAM) cell is an important area of research. In this paper, a new five-input majority gate is presented which is suitable for implementing efficient single-layer QCA circuits. In addition, a new RAM cell with set and reset capabilities is designed based on the proposed majority gate, which has an efficient and low-energy structure. The functionality, performance and energy consumption of the proposed designs are evaluated based on the QCADesigner and QCAPro tools. According to the simulation results, the proposed RAM design leads to on average 38% lower total energy dissipation, 25% smaller area, 20% lower cell count, 28% lower delay and 60% lower QCA cost as compared to its previous counterparts.

Attitudes toward and approaches to learning first-year university mathematics.

PubMed

Alkhateeb, Haitham M; Hammoudi, Lakhdar

2006-08-01

This study examined the relationship for 180 undergraduate students enrolled in a first-year university calculus course between attitudes toward mathematics and approaches to learning mathematics using the Mathematics Attitude Scale and the Approaches to Learning Mathematics Questionnaire, respectively. Regression analyses indicated that scores for the Mathematics Attitude Scale were negatively related to scores for the Surface Approach and accounted for 10.4% of the variance and scores for the Mathematics Attitude Scale were positively related to scores for the Deep Approach to learning mathematics and accounted for 31.7% of the variance.

A Learning Cycle Approach To Introducing Osmosis.

ERIC Educational Resources Information Center

Lawson, Anton E.

2000-01-01

Presents an inquiry activity with a learning cycle approach to engage students in testing their own hypotheses about how molecules move through cell membranes. Offers student materials and teacher materials, including teaching tips for each phase of the learning cycle. (Contains 11 references.) (ASK)

Inquisitivism or "The HHHMMM??? What Does This Button Do?" Approach to Learning.

ERIC Educational Resources Information Center

Harapnuik, Dwayne

This paper discusses the development of a learning approach based on the unique needs of adult learners who are required to learn and use new information technologies. It establishes how the "Inquisitivism" learning approach has evolved from a synthesis of key cognitive learning theories into one cohesive approach and how the…

Developing an International Distance Education Program: A Blended Learning Approach

ERIC Educational Resources Information Center

Mathur, Ravisha; Oliver, Lisa

2007-01-01

Building a dynamic international distance education program can be a complex operation. The purpose of this paper is to discuss a model for global learning that utilizes a blended learning approach. This paper will describe how a blended learning approach was implemented in an international instructional technology Master's program to the benefit…

Learning Styles in the e-Learning Environment: The Approaches and Research on Longitudinal Changes

ERIC Educational Resources Information Center

Doulik, Pavel; Skoda, Jiri; Simonova, Ivana

2017-01-01

The paper focuses on the field of learning styles in e-learning. The study is structured in two main parts: (1) a brief overview of traditional approaches to learning styles is presented and their role in the process of instruction is set; this part results in the reflection of current state, when learning styles are considered within e-learning;…

Students' Studying and Approaches to Learning in Introductory Biology

PubMed Central

2004-01-01

This exploratory study was conducted in an introductory biology course to determine 1) how students used the large lecture environment to create their own learning tasks during studying and 2) whether meaningful learning resulted from the students' efforts. Academic task research from the K–12 education literature and student approaches to learning research from the postsecondary education literature provided the theoretical framework for the mixed methods study. The subject topic was cell division. Findings showed that students 1) valued lectures to develop what they believed to be their own understanding of the topic; 2) deliberately created and engaged in learning tasks for themselves only in preparation for the unit exam; 3) used course resources, cognitive operations, and study strategies that were compatible with surface and strategic, rather than deep, approaches to learning; 4) successfully demonstrated competence in answering familiar test questions aligned with their surface and strategic approaches to studying and learning; and 5) demonstrated limited meaningful understanding of the significance of cell division processes. Implications for introductory biology education are discussed. PMID:15592598

Interrelations among University Students' Approaches to Learning, Regulation of Learning, and Cognitive and Attributional Strategies: A Person Oriented Approach

ERIC Educational Resources Information Center

Heikkila, Annamari; Niemivirta, Markku; Nieminen, Juha; Lonka, Kirsti

2011-01-01

This study investigated the relationships among approaches to learning, regulation of learning, cognitive and attributional strategies, stress, exhaustion, and study success. University students (N = 437) from three faculties filled in a questionnaire concerning their self-reported study behaviour, cognitive strategies, and well-being. Their…

Simulations of Living Cell Origins Using a Cellular Automata Model

NASA Astrophysics Data System (ADS)

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Simulations of living cell origins using a cellular automata model.

PubMed

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Comparison of student's learning achievement through realistic mathematics education (RME) approach and problem solving approach on grade VII

NASA Astrophysics Data System (ADS)

Ilyas, Muhammad; Salwah

2017-02-01

The type of this research was experiment. The purpose of this study was to determine the difference and the quality of student's learning achievement between students who obtained learning through Realistic Mathematics Education (RME) approach and students who obtained learning through problem solving approach. This study was a quasi-experimental research with non-equivalent experiment group design. The population of this study was all students of grade VII in one of junior high school in Palopo, in the second semester of academic year 2015/2016. Two classes were selected purposively as sample of research that was: year VII-5 as many as 28 students were selected as experiment group I and VII-6 as many as 23 students were selected as experiment group II. Treatment that used in the experiment group I was learning by RME Approach, whereas in the experiment group II by problem solving approach. Technique of data collection in this study gave pretest and posttest to students. The analysis used in this research was an analysis of descriptive statistics and analysis of inferential statistics using t-test. Based on the analysis of descriptive statistics, it can be concluded that the average score of students' mathematics learning after taught using problem solving approach was similar to the average results of students' mathematics learning after taught using realistic mathematics education (RME) approach, which are both at the high category. In addition, It can also be concluded that; (1) there was no difference in the results of students' mathematics learning taught using realistic mathematics education (RME) approach and students who taught using problem solving approach, (2) quality of learning achievement of students who received RME approach and problem solving approach learning was same, which was at the high category.

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

PubMed

Chung, Michael Jae-Yoon; Friesen, Abram L; Fox, Dieter; Meltzoff, Andrew N; Rao, Rajesh P N

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.

(Re)Conceptualizing Design Approaches for Mobile Language Learning

ERIC Educational Resources Information Center

Hoven, Debra; Palalas, Agnieszka

2011-01-01

An exploratory study conducted at George Brown College in Toronto, Canada between 2007 and 2009 investigated language learning with mobile devices as an approach to augmenting ESP learning by taking learning outside the classroom into the real-world context. In common with findings at other community colleges, this study identified inadequate…

Investigations of Students' Motivation Towards Learning Secondary School Physics through Mastery Learning Approach

ERIC Educational Resources Information Center

Changeiywo, Johnson M.; Wambugu, P. W.; Wachanga, S. W.

2011-01-01

Teaching method is a major factor that affects students' motivation to learn physics. This study investigated the effects of using mastery learning approach (MLA) on secondary school students' motivation to learn physics. Solomon four non-equivalent control group design under the quasi-experimental research method was used in which a random sample…

Can Learning Motivation Predict Learning Achievement? A Case Study of a Mobile Game-Based English Learning Approach

ERIC Educational Resources Information Center

Tsai, Chia-Hui; Cheng, Ching-Hsue; Yeh, Duen-Yian; Lin, Shih-Yun

2017-01-01

This study applied a quasi-experimental design to investigate the influence and predictive power of learner motivation for achievement, employing a mobile game-based English learning approach. A system called the Happy English Learning System, integrating learning material into a game-based context, was constructed and installed on mobile devices…

The Effects of Brain Based Learning Approach on Motivation and Students Achievement in Mathematics Learning

NASA Astrophysics Data System (ADS)

Mekarina, M.; Ningsih, Y. P.

2017-09-01

This classroom action research is based by the facts that the students motivation and achievement mathematics learning is less. One of the factors causing is learning that does not provide flexibility to students to empower the potential of the brain optimally. The aim of this research was to improve the student motivation and achievement in mathematics learning by implementing brain based learning approach. The subject of this research was student of grade XI in senior high school. The research consisted of two cycles. Data of student achievement from test, and the student motivation through questionnaire. Furthermore, the finding of this research showed the result of the analysis was the implementation of brain based learning approach can improve student’s achievement and motivation in mathematics learning.

Investigating Teachers' Views of Student-Centred Learning Approach

ERIC Educational Resources Information Center

Seng, Ernest Lim Kok

2014-01-01

Conventional learning is based on low levels of students' participation where students are rarely expected to ask questions or to challenge the theories of the academic. A paradigm shift in curriculum has resulted in implementing student-centred learning (SCL) approach, putting students as the centre of the learning process. This mode of…

Molecular quantum cellular automata cell design trade-offs: latching vs. power dissipation.

PubMed

Rahimi, Ehsan; Reimers, Jeffrey R

2018-06-20

The use of molecules to enact quantum cellular automata (QCA) cells has been proposed as a new way for performing electronic logic operations at sub-nm dimensions. A key question that arises concerns whether chemical or physical processes are to be exploited. The use of chemical reactions allows the state of a switch element to be latched in molecular form, making the output of a cell independent of its inputs, but costs energy to do the reaction. Alternatively, if purely electronic polarization is manipulated then no internal latching occurs, but no power is dissipated provided the fields from the inputs change slowly compared to the molecular response times. How these scenarios pan out is discussed by considering calculated properties of the 1,4-diallylbutane cation, a species often used as a paradigm for molecular electronic switching. Utilized are results from different calculation approaches that depict the ion either as a charge-localized mixed-valence compound functioning as a bistable switch, or else as an extremely polarizable molecule with a delocalized electronic structure. Practical schemes for using molecular cells in QCA and other devices emerge.

JiFUNzeni: A Blended Learning Approach for Sustainable Teachers' Professional Development

ERIC Educational Resources Information Center

Onguko, Brown Bully

2014-01-01

JiFUNzeni blended learning approach is a sustainable approach to provision of professional development (PD) for those in challenging educational contexts. JiFUNzeni approach emphasizes training regional experts to create blended learning content, working with appropriate technology while building content repositories. JiFUNzeni approach was…

Enhancing the Teaching-Learning Process: A Knowledge Management Approach

ERIC Educational Resources Information Center

Bhusry, Mamta; Ranjan, Jayanthi

2012-01-01

Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

PubMed Central

Chung, Michael Jae-Yoon; Friesen, Abram L.; Fox, Dieter; Meltzoff, Andrew N.; Rao, Rajesh P. N.

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration. PMID:26536366

A Guided Discovery Approach for Learning Glycolysis.

ERIC Educational Resources Information Center

Schultz, Emeric

1997-01-01

Argues that more attention should be given to teaching students how to learn the rudiments of specific metabolic pathways. This approach describes a unique way of learning the glycolytic pathway in stepwise fashion. The pedagogy involves clear rote components that are connected to a set of generalizations that develop and enhance important…

Cyber Asynchronous versus Blended Cyber Approach in Distance English Learning

ERIC Educational Resources Information Center

Ge, Zi-Gang

2012-01-01

This study aims to compare the single cyber asynchronous learning approach with the blended cyber learning approach in distance English education. Two classes of 70 students participated in this study, which lasted one semester of about four months, with one class using the blended approach for their English study and the other only using the…

Decomposition of timed automata for solving scheduling problems

NASA Astrophysics Data System (ADS)

Nishi, Tatsushi; Wakatake, Masato

2014-03-01

A decomposition algorithm for scheduling problems based on timed automata (TA) model is proposed. The problem is represented as an optimal state transition problem for TA. The model comprises of the parallel composition of submodels such as jobs and resources. The procedure of the proposed methodology can be divided into two steps. The first step is to decompose the TA model into several submodels by using decomposable condition. The second step is to combine individual solution of subproblems for the decomposed submodels by the penalty function method. A feasible solution for the entire model is derived through the iterated computation of solving the subproblem for each submodel. The proposed methodology is applied to solve flowshop and jobshop scheduling problems. Computational experiments demonstrate the effectiveness of the proposed algorithm compared with a conventional TA scheduling algorithm without decomposition.

An Asynchronous Cellular Automata-Based Adaptive Illumination Facility

NASA Astrophysics Data System (ADS)

Bandini, Stefania; Bonomi, Andrea; Vizzari, Giuseppe; Acconci, Vito

The term Ambient Intelligence refers to electronic environments that are sensitive and responsive to the presence of people; in the described scenario the environment itself is endowed with a set of sensors (to perceive humans or other physical entities such as dogs, bicycles, etc.), interacting with a set of actuators (lights) that choose their actions (i.e. state of illumination) in an attempt improve the overall experience of these users. The model for the interaction and action of sensors and actuators is an asynchronous Cellular Automata (CA) with memory, supporting a self-organization of the system as a response to the presence and movements of people inside it. The paper will introduce the model, as well as an ad hoc user interface for the specification of the relevant parameters of the CA transition rule that determines the overall system behaviour.

Artificial neuron-glia networks learning approach based on cooperative coevolution.

PubMed

Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B

2015-06-01

Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

Learning from Tutorials: A Qualitative Study of Approaches to Learning and Perceptions of Tutorial Interaction

ERIC Educational Resources Information Center

Herrmann, Kim Jesper

2014-01-01

This study examines differences in university students' approaches to learning when attending tutorials as well as variation in students' perceptions of tutorials as an educational arena. In-depth qualitative analysis of semi-structured interviews with undergraduates showed how surface and deep approaches to learning were revealed in the…

Do Students Develop towards More Deep Approaches to Learning during Studies? A Systematic Review on the Development of Students' Deep and Surface Approaches to Learning in Higher Education

ERIC Educational Resources Information Center

Asikainen, Henna; Gijbels, David

2017-01-01

The focus of the present paper is on the contribution of the research in the student approaches to learning tradition. Several studies in this field have started from the assumption that students' approaches to learning develop towards more deep approaches to learning in higher education. This paper reports on a systematic review of longitudinal…

An Expert System-based Context-Aware Ubiquitous Learning Approach for Conducting Science Learning Activities

ERIC Educational Resources Information Center

Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Wen-Hung

2013-01-01

Context-aware ubiquitous learning has been recognized as being a promising approach that enables students to interact with real-world learning targets with supports from the digital world. Several researchers have indicated the importance of providing learning guidance or hints to individual students during the context-aware ubiquitous learning…

Concept Based Approach for Adaptive Personalized Course Learning System

ERIC Educational Resources Information Center

Salahli, Mehmet Ali; Özdemir, Muzaffer; Yasar, Cumali

2013-01-01

One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…

Understanding Observational Learning: An Interbehavioral Approach

PubMed Central

Fryling, Mitch J; Johnston, Cristin; Hayes, Linda J

2011-01-01

Observational learning is an important area in the field of psychology and behavior science more generally. Given this, it is essential that behavior analysts articulate a sound theory of how behavior change occurs through observation. This paper begins with an overview of seminal research in the area of observational learning, followed by a consideration of common behavior analytic conceptualizations of these findings. The interbehavioral perspective is then outlined, shedding light on some difficulties with the existing behavior analytic approaches. The implications of embracing the interbehavioral perspective for understanding the most complex sorts of behavior, including those involved in observational learning are considered. PMID:22532764

Web-Based Teaching and Learning Approach (WBTLA) Usability in Institutions of Higher Learning in Malaysia

ERIC Educational Resources Information Center

Nordin, Abu Bakar; Alias, Norlidah

2013-01-01

Today teachers in schools and lecturers in institutions of higher learning are endowed with a wide range of new teaching experiences through web-based teaching and learning approaches (WBTLA), which was not possible before through the traditional classroom approach. With the use of WBTLA emerged problems related to usability in technical,…

Simple and Flexible Self-Reproducing Structures in Asynchronous Cellular Automata and Their Dynamics

NASA Astrophysics Data System (ADS)

Huang, Xin; Lee, Jia; Yang, Rui-Long; Zhu, Qing-Sheng

2013-03-01

Self-reproduction on asynchronous cellular automata (ACAs) has attracted wide attention due to the evident artifacts induced by synchronous updating. Asynchronous updating, which allows cells to undergo transitions independently at random times, might be more compatible with the natural processes occurring at micro-scale, but the dark side of the coin is the increment in the complexity of an ACA in order to accomplish stable self-reproduction. This paper proposes a novel model of self-timed cellular automata (STCAs), a special type of ACAs, where unsheathed loops are able to duplicate themselves reliably in parallel. The removal of sheath cannot only allow various loops with more flexible and compact structures to replicate themselves, but also reduce the number of cell states of the STCA as compared to the previous model adopting sheathed loops [Y. Takada, T. Isokawa, F. Peper and N. Matsui, Physica D227, 26 (2007)]. The lack of sheath, on the other hand, often tends to cause much more complicated interactions among loops, when all of them struggle independently to stretch out their constructing arms at the same time. In particular, such intense collisions may even cause the emergence of a mess of twisted constructing arms in the cellular space. By using a simple and natural method, our self-reproducing loops (SRLs) are able to retract their arms successively, thereby disentangling from the mess successfully.

The Effects of Discipline on Deep Approaches to Student Learning and College Outcomes

ERIC Educational Resources Information Center

Nelson Laird, Thomas F.; Shoup, Rick; Kuh, George D.; Schwarz, Michael J.

2008-01-01

"Deep learning" represents student engagement in approaches to learning that emphasize integration, synthesis, and reflection. Because learning is a shared responsibility between students and faculty, it is important to determine whether faculty members emphasize deep approaches to learning and to assess how much students employ these approaches.…

A Multi-Faceted Approach to Inquiry-Based Learning

NASA Astrophysics Data System (ADS)

Brudzinski, M. R.; Sikorski, J.

2009-12-01

In order to fully attain the benefits of inquiry-based learning, instructors who typically employ the traditional lecture format need to make several adjustments to their approach. This change in styles can be intimidating and logistically difficult to overcome. A stepwise approach to this transformation is likely to be more manageable for individual faculty or departments. In this session, we will describe several features that we are implementing in our introductory geology course with the ultimate goal of converting to an entirely inquiry-based approach. Our project is part of the Miami University initiative in the top 25 enrolled courses to move towards the “student as scholar” model for engaged learning. Some of the features we developed for our course include: student learning outcomes, student development outcomes, out-of-class content quizzes, in-class conceptests, pre-/post-course assessment, reflective knowledge surveys, and daily group activities.

Enabling model checking for collaborative process analysis: from BPMN to `Network of Timed Automata'

NASA Astrophysics Data System (ADS)

Mallek, Sihem; Daclin, Nicolas; Chapurlat, Vincent; Vallespir, Bruno

2015-04-01

Interoperability is a prerequisite for partners involved in performing collaboration. As a consequence, the lack of interoperability is now considered a major obstacle. The research work presented in this paper aims to develop an approach that allows specifying and verifying a set of interoperability requirements to be satisfied by each partner in the collaborative process prior to process implementation. To enable the verification of these interoperability requirements, it is necessary first and foremost to generate a model of the targeted collaborative process; for this research effort, the standardised language BPMN 2.0 is used. Afterwards, a verification technique must be introduced, and model checking is the preferred option herein. This paper focuses on application of the model checker UPPAAL in order to verify interoperability requirements for the given collaborative process model. At first, this step entails translating the collaborative process model from BPMN into a UPPAAL modelling language called 'Network of Timed Automata'. Second, it becomes necessary to formalise interoperability requirements into properties with the dedicated UPPAAL language, i.e. the temporal logic TCTL.

A new simulation system of traffic flow based on cellular automata principle

NASA Astrophysics Data System (ADS)

Shan, Junru

2017-05-01

Traffic flow is a complex system of multi-behavior so it is difficult to give a specific mathematical equation to express it. With the rapid development of computer technology, it is an important method to study the complex traffic behavior by simulating the interaction mechanism between vehicles and reproduce complex traffic behavior. Using the preset of multiple operating rules, cellular automata is a kind of power system which has discrete time and space. It can be a good simulation of the real traffic process and a good way to solve the traffic problems.

Student Learning Approaches in the UAE: The Case for the Achieving Domain

ERIC Educational Resources Information Center

McLaughlin, James; Durrant, Philip

2017-01-01

The deep versus surface learning approach dichotomy has dominated recent research in student learning approach dimensions. However, the achievement dimension may differ in importance in non-Western and vocational tertiary settings. The aim was to assess how Emirati tertiary students could be characterized in terms of their learning approaches. The…

"Revisiting" the South Pacific Approaches to Learning: A Confirmatory Factor Analysis Study

ERIC Educational Resources Information Center

Phan, Huy P.; Deo, Bisun

2008-01-01

There has been substantial research evidence concerning the learning approaches of students in Western and non-Western contexts. Nonetheless, it has been a decade since research in the South Pacific was conducted on the learning approaches of tertiary students. The present research examined the learning approaches of Fijian and other Pacific…

Synthesizing Technology Adoption and Learners' Approaches towards Active Learning in Higher Education

ERIC Educational Resources Information Center

Chan, Kevin; Cheung, George; Wan, Kelvin; Brown, Ian; Luk, Green

2015-01-01

In understanding how active and blended learning approaches with learning technologies engagement in undergraduate education, current research models tend to undermine the effect of learners' variations, particularly regarding their styles and approaches to learning, on intention and use of learning technologies. This study contributes to further…

Demarcating Advanced Learning Approaches from Methodological and Technological Perspectives

ERIC Educational Resources Information Center

Horvath, Imre; Peck, David; Verlinden, Jouke

2009-01-01

In the field of design and engineering education, the fast and expansive evolution of information and communication technologies is steadily converting traditional learning approaches into more advanced ones. Facilitated by Broadband (high bandwidth) personal computers, distance learning has developed into web-hosted electronic learning. The…

The Wonder Approach to learning

PubMed Central

L’Ecuyer, Catherine

2014-01-01

Wonder, innate in the child, is an inner desire to learn that awaits reality in order to be awakened. Wonder is at the origin of reality-based consciousness, thus of learning. The scope of wonder, which occurs at a metaphysical level, is greater than that of curiosity. Unfortunate misinterpretations of neuroscience have led to false brain-based ideas in the field of education, all of these based on the scientifically wrong assumption that children’s learning depends on an enriched environment. These beliefs have re-enforced the Behaviorist Approach to education and to parenting and have contributed to deadening our children’s sense of wonder. We suggest wonder as the center of all motivation and action in the child. Wonder is what makes life genuinely personal. Beauty is what triggers wonder. Wonder attunes to beauty through sensitivity and is unfolded by secure attachment. When wonder, beauty, sensitivity and secure attachment are present, learning is meaningful. On the contrary, when there is no volitional dimension involved (no wonder), no end or meaning (no beauty) and no trusting predisposition (secure attachment), the rigid and limiting mechanical process of so-called learning through mere repetition become a deadening and alienating routine. This could be described as training, not as learning, because it does not contemplate the human being as a whole. PMID:25339882

Meaningful Learning in the Teaching of Culture: The Project Based Learning Approach

ERIC Educational Resources Information Center

Kean, Ang Chooi; Kwe, Ngu Moi

2014-01-01

This paper reports on a collaborative effort taken by a team of three teacher educators in using the Project Based Learning (PBL) approach in the teaching of Japanese culture with the aim to investigate the presence of actual "meaningful learning" among 15 students of a 12-Week Preparatory Japanese Language course under a teacher…

Students' approaches to learning in clinical interprofessional context.

PubMed

Hylin, Uffe; Lonka, Kirsti; Ponzer, Sari

2011-01-01

Health care professionals are supposed to work in teams. Students in health care need to learn how to collaborate during their undergraduate education. Interprofessional learning environments, where collaboration is necessary, may be differently accepted by students depending on their approach to learning. We investigated health care students' evaluations of interprofessional clinical training in relation to their study orientations. The participants were 369 students (40 occupational therapy-, 85 medical-, 52 physiotherapy-, and 192 nursing students) attending an IPE course at a Swedish University Hospital. Data were collected by questionnaires measuring orientations to studying and attitudes towards the clinical training and the IPE concept before and after the training. The response rate was 77 %. Study groups were formed by a cluster analysis on the basis of the students' learning orientations. Three clusters were found: Low collaboration-, Collaborative Constructivist-, and Cookbook groups. These clusters were related to different professions and how students perceived their interprofessional learning environment. Study orientations appear to play a role in the way students evaluate interprofessional training. This should be taken into account in instruction. Students with a 'Cookbook' approach to learning showed an increased understanding of interprofessional collaboration after the course.

History dependent quantum random walks as quantum lattice gas automata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shakeel, Asif, E-mail: asif.shakeel@gmail.com, E-mail: dmeyer@math.ucsd.edu, E-mail: plove@haverford.edu; Love, Peter J., E-mail: asif.shakeel@gmail.com, E-mail: dmeyer@math.ucsd.edu, E-mail: plove@haverford.edu; Meyer, David A., E-mail: asif.shakeel@gmail.com, E-mail: dmeyer@math.ucsd.edu, E-mail: plove@haverford.edu

Quantum Random Walks (QRW) were first defined as one-particle sectors of Quantum Lattice Gas Automata (QLGA). Recently, they have been generalized to include history dependence, either on previous coin (internal, i.e., spin or velocity) states or on previous position states. These models have the goal of studying the transition to classicality, or more generally, changes in the performance of quantum walks in algorithmic applications. We show that several history dependent QRW can be identified as one-particle sectors of QLGA. This provides a unifying conceptual framework for these models in which the extra degrees of freedom required to store the historymore » information arise naturally as geometrical degrees of freedom on the lattice.« less

The study of effectiveness of blended learning approach for medical training courses.

PubMed

Karamizadeh, Z; Zarifsanayei, N; Faghihi, A A; Mohammadi, H; Habibi, M

2012-01-01

Blended learning as a method of learning that includes face to face learning, pure E-learning and didactic learning. This study aims to investigate the efficacy of medical education by this approach. This interventional study was performed in 130 students at different clinical levels participating in class sessions on "congenital adrenal hyperplasia and ambiguous genitalia". Sampling was done gradually during 6 months and all of them filled a pretest questionnaire and received an educational compact disk. One week later, a presence class session was held in a question and answer and problem solving method. Two to four weeks later, they filled a posttest questionnaire. There was a significant correlation between pretest and posttest scores and the posttest scores were significantly more than the pretest ones. Sub-specialized residents had the most and the students had the least attitude towards blended learning approach. There was a significant correlation between the research samples' accessibility to computer and their attitude and satisfaction to blended learning approach. Findings generally showed that the blended learning was an effective approach in making a profound learning of academic subjects.

The colloquial approach: An active learning technique

NASA Astrophysics Data System (ADS)

Arce, Pedro

1994-09-01

This paper addresses the very important problem of the effectiveness of teaching methodologies in fundamental engineering courses such as transport phenomena. An active learning strategy, termed the colloquial approach, is proposed in order to increase student involvement in the learning process. This methodology is a considerable departure from traditional methods that use solo lecturing. It is based on guided discussions, and it promotes student understanding of new concepts by directing the student to construct new ideas by building upon the current knowledge and by focusing on key cases that capture the essential aspects of new concepts. The colloquial approach motivates the student to participate in discussions, to develop detailed notes, and to design (or construct) his or her own explanation for a given problem. This paper discusses the main features of the colloquial approach within the framework of other current and previous techniques. Problem-solving strategies and the need for new textbooks and for future investigations based on the colloquial approach are also outlined.

Family, Learning Environments, Learning Approaches, and Student Outcomes in a Malaysian Private University

ERIC Educational Resources Information Center

Kek, Megan A. Yih Chyn; Darmawan, I. Gusti Ngurah; Chen, Yu Sui

2007-01-01

This article presents the quantitative findings from a mixed methods study of students and faculty at a private medical university in Malaysia. In particular, the relationships among students' individual characteristics, general self-efficacy, family context, university and classroom learning environments, curriculum, approaches to learning, and…

Actively Teaching Research Methods with a Process Oriented Guided Inquiry Learning Approach

ERIC Educational Resources Information Center

Mullins, Mary H.

2017-01-01

Active learning approaches have shown to improve student learning outcomes and improve the experience of students in the classroom. This article compares a Process Oriented Guided Inquiry Learning style approach to a more traditional teaching method in an undergraduate research methods course. Moving from a more traditional learning environment to…

Variability in University Students' Use of Technology: An "Approaches to Learning" Perspective

ERIC Educational Resources Information Center

Mimirinis, Mike

2016-01-01

This study reports the results of a cross-case study analysis of how students' approaches to learning are demonstrated in blended learning environments. It was initially propositioned that approaches to learning as key determinants of the quality of student learning outcomes are demonstrated specifically in how students utilise technology in…

Contextual Teaching and Learning Approach of Mathematics in Primary Schools

NASA Astrophysics Data System (ADS)

Selvianiresa, D.; Prabawanto, S.

2017-09-01

The Contextual Teaching and Learning (CTL) approach is an approach involving active students in the learning process to discover the concepts learned through to knowledge and experience of the students. Similar to Piaget’s opinion that learning gives students an actives trying to do new things by relating their experiences and building their own minds. When students to connecting mathematics with real life, then students can looking between a conceptual to be learned with a concept that has been studied. So that, students can developing of mathematical connection ability. This research is quasi experiment with a primary school in the city of Kuningan. The result showed that CTL learning can be successful, when learning used a collaborative interaction with students, a high level of activity in the lesson, a connection to real-world contexts, and an integration of science content with other content and skill areas. Therefore, CTL learning can be applied by techer to mathematics learning in primary schools.

An ensemble rank learning approach for gene prioritization.

PubMed

Lee, Po-Feng; Soo, Von-Wun

2013-01-01

Several different computational approaches have been developed to solve the gene prioritization problem. We intend to use the ensemble boosting learning techniques to combine variant computational approaches for gene prioritization in order to improve the overall performance. In particular we add a heuristic weighting function to the Rankboost algorithm according to: 1) the absolute ranks generated by the adopted methods for a certain gene, and 2) the ranking relationship between all gene-pairs from each prioritization result. We select 13 known prostate cancer genes in OMIM database as training set and protein coding gene data in HGNC database as test set. We adopt the leave-one-out strategy for the ensemble rank boosting learning. The experimental results show that our ensemble learning approach outperforms the four gene-prioritization methods in ToppGene suite in the ranking results of the 13 known genes in terms of mean average precision, ROC and AUC measures.

Harnessing the Power of Learning Management Systems: An E-Learning Approach for Professional Development.

PubMed

White, Meagan; Shellenbarger, Teresa

E-learning provides an alternative approach to traditional professional development activities. A learning management system may help nursing professional development practitioners deliver content more efficiently and effectively; however, careful consideration is needed during planning and implementation. This article provides essential information in the selection and use of a learning management system for professional development.

Investigating the interrelationships among conceptions of, approaches to, and self-efficacy in learning science

NASA Astrophysics Data System (ADS)

Zheng, Lanqin; Dong, Yan; Huang, Ronghuai; Chang, Chun-Yen; Bhagat, Kaushal Kumar

2018-01-01

The purpose of this study was to examine the relations between primary school students' conceptions of, approaches to, and self-efficacy in learning science in Mainland China. A total of 1049 primary school students from Mainland China participated in this study. Three instruments were adapted to measure students' conceptions of learning science, approaches to learning science, and self-efficacy. The exploratory factor analysis and confirmatory factor analysis were adopted to validate three instruments. The path analysis was employed to understand the relationships between conceptions of learning science, approaches to learning science, and self-efficacy. The findings indicated that students' lower level conceptions of learning science positively influenced their surface approaches in learning science. Higher level conceptions of learning science had a positive influence on deep approaches and a negative influence on surface approaches to learning science. Furthermore, self-efficacy was also a hierarchical construct and can be divided into the lower level and higher level. Only students' deep approaches to learning science had a positive influence on their lower and higher level of self-efficacy in learning science. The results were discussed in the context of the implications for teachers and future studies.

Modeling and predicting urban growth pattern of the Tokyo metropolitan area based on cellular automata

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.

Learning Behavior and Achievement Analysis of a Digital Game-Based Learning Approach Integrating Mastery Learning Theory and Different Feedback Models

ERIC Educational Resources Information Center

Yang, Kai-Hsiang

2017-01-01

It is widely accepted that the digital game-based learning approach has the advantage of stimulating students' learning motivation, but simply using digital games in the classroom does not guarantee satisfactory learning achievement, especially in the case of the absence of a teacher. Integrating appropriate learning strategies into a game can…

Student-Centred Learning Environments: An Investigation into Student Teachers' Instructional Preferences and Approaches to Learning

ERIC Educational Resources Information Center

Baeten, Marlies; Dochy, Filip; Struyven, Katrien; Parmentier, Emmeline; Vanderbruggen, Anne

2016-01-01

The use of student-centred learning environments in education has increased. This study investigated student teachers' instructional preferences for these learning environments and how these preferences are related to their approaches to learning. Participants were professional Bachelor students in teacher education. Instructional preferences and…

Exact results of 1D traffic cellular automata: The low-density behavior of the Fukui-Ishibashi model

NASA Astrophysics Data System (ADS)

Salcido, Alejandro; Hernández-Zapata, Ernesto; Carreón-Sierra, Susana

2018-03-01

The maximum entropy states of the cellular automata models for traffic flow in a single-lane with no anticipation are presented and discussed. The exact analytical solutions for the low-density behavior of the stochastic Fukui-Ishibashi traffic model were obtained and compared with computer simulations of the model. An excellent agreement was found.

The Learning of Consumer Skills in Adolescents: An Eclectic Approach.

ERIC Educational Resources Information Center

Kuo, Cheng

A study investigated the learning of consumer skills by adolescents, using two theoretical approaches--the social learning and the family communication pattern approaches. It was hypothesized that (1) assuming that parents are more experienced consumers than are adolescents, frequent discussion with parents on consumption matters are likely to…

Manpower Development for Workers in Tertiary Institutions: Distance Learning Approach

ERIC Educational Resources Information Center

Hassan, Moshood Ayinde

2011-01-01

The purpose of this study is to determine the extent to which workers patronize distance learning approach to further their education. Other purposes include: determine problems facing workers in the process of improving their knowledge and skills through distance learning approach; establish the level of attainment of manpower development…

Dental students' perception of their approaches to learning in a PBL programme.

PubMed

Haghparast, H; Ghorbani, A; Rohlin, M

2017-08-01

To compare dental students' perceptions of their learning approaches between different years of a problem-based learning (PBL) programme. The hypothesis was that in a comparison between senior and junior students, the senior students would perceive themselves as having a higher level of deep learning approach and a lower level of surface learning approach than junior students would. This hypothesis was based on the fact that senior students have longer experience of a student-centred educational context, which is supposed to underpin student learning. Students of three cohorts (first year, third year and fifth year) of a PBL-based dental programme were asked to respond to a questionnaire (R-SPQ-2F) developed to analyse students' learning approaches, that is deep approach and surface approach, using four subscales including deep strategy, surface strategy, deep motive and surface motive. The results of the three cohorts were compared using a one-way analysis of variance (ANOVA). A P-value was set at <0.05 for statistical significance. The fifth-year students demonstrated a lower surface approach than the first-year students (P = 0.020). There was a significant decrease in surface strategy from the first to the fifth year (P = 0.003). No differences were found concerning deep approach or its subscales (deep strategy and deep motive) between the mean scores of the three cohorts. The results did not show the expected increased depth in learning approaches over the programme years. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Self-Regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison between Professional Training and English Learning

ERIC Educational Resources Information Center

Tseng, Min-chen; Chen, Chia-cheng

2017-01-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between…

Object Synthesis in Conway's Game of Life and Other Cellular Automata

NASA Astrophysics Data System (ADS)

Niemiec, Mark D.

Of the very large number of cellular automata rules in existence, a relatively small number of rules may be considered interesting. Some of the features that make such rules interesting permit patterns to expand, contract, separate into multiple sub-patterns, or combine with other patterns. Such rules generally include still-lifes, oscillators, spaceships, spaceship guns, and puffer trains. Such structures can often be used to construct more complicated computational circuitry, and rules that contain them can often be shown to be computationally universal. Conway's Game of Life is one rule that has been well-studied for several decades, and has been shown to be very fruitful in this regard.

Teaching and Learning as Communication: A Cultural Approach.

ERIC Educational Resources Information Center

Chen, Zhuojun (Joyce)

With an ethnographic approach, this paper focused on the process of students' learning. It examines students' feelings about learning environments and expectations of college education, as well as professors' experiences with college teaching and their views of teachers' role in contemporary society. Unstructured, intensive interviews were…

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Students awareness of learning styles and their perceptions to a mixed method approach for learning.

PubMed

Bhagat, Anumeha; Vyas, Rashmi; Singh, Tejinder

2015-08-01

Individualization of instructional method does not contribute significantly to learning outcomes although it is known that students have differing learning styles (LSs). Hence, in order to maximally enhance learning, one must try to use a mixed method approach. Our hypothesis was that awareness of preferred LS and motivation to incorporate multiple learning strategies might enhance learning outcomes. Our aim was to determine the impact of awareness of LS among medical undergraduates and motivating students to use mixed methods of learning. Before awareness lecture, LS preferences were determined using Visual, Aural, Read/Write, and Kinesthetic (VARK) questionnaire. Awareness of LS was assessed using a validated questionnaire. Through a lecture, students were oriented to various LSs, impact of LS on their performance, and benefit of using mixed method approach for learning. Subsequently, group discussions were organized. After 3 months, VARK preferences and awareness of LSs were reassessed. Student narratives were collected. Qualitative analysis of the data was done. There was a significant increase in the number of students who were aware of LS. The number of participants showing a change in VARK scores for various modalities of learning was also significant (P < 0.001). Thus, awareness of LSs motivated students to adapt other learning strategies and use mixed methods for learning.

Effects of the Digital Game-Development Approach on Elementary School Students' Learning Motivation, Problem Solving, and Learning Achievement

ERIC Educational Resources Information Center

Chu, Hui-Chun; Hung, Chun-Ming

2015-01-01

In this study, the game-based development approach is proposed for improving the learning motivation, problem solving skills, and learning achievement of students. An experiment was conducted on a learning activity of an elementary school science course to evaluate the performance of the proposed approach. A total of 59 sixth graders from two…

Superficial and deep learning approaches among medical students in an interdisciplinary integrated curriculum.

PubMed

Mirghani, Hisham M; Ezimokhai, Mutairu; Shaban, Sami; van Berkel, Henk J M

2014-01-01

Students' learning approaches have a significant impact on the success of the educational experience, and a mismatch between instructional methods and the learning approach is very likely to create an obstacle to learning. Educational institutes' understanding of students' learning approaches allows those institutes to introduce changes in their curriculum content, instructional format, and assessment methods that will allow students to adopt deep learning techniques and critical thinking. The objective of this study was to determine and compare learning approaches among medical students following an interdisciplinary integrated curriculum. This was a cross-sectional study in which an electronic questionnaire using the Biggs two-factor Study Process Questionnaire (SPQ) with 20 questions was administered. Of a total of 402 students at the medical school, 214 (53.2%) completed the questionnaire. There was a significant difference in the mean score of superficial approach, motive and strategy between students in the six medical school years. However, no significant difference was observed in the mean score of deep approach, motive and strategy. The mean score for years 1 and 2 showed a significantly higher surface approach, surface motive and surface strategy when compared with students in years 4-6 in medical school. The superficial approach to learning was mostly preferred among first and second year medical students, and the least preferred among students in the final clinical years. These results may be useful in creating future teaching, learning and assessment strategies aiming to enhance a deep learning approach among medical students. Future studies are needed to investigate the reason for the preferred superficial approach among medical students in their early years of study.

Approaches to Learning in a Second Year Chemical Engineering Course.

ERIC Educational Resources Information Center

Case, Jennifer M.; Gunstone, Richard F.

2003-01-01

Investigates student approaches to learning in a second year chemical engineering course by means of a qualitative research project which utilized interview and journal data from a group of 11 students. Identifies three approaches to learning: (1) conceptual; (2) algorithmic; and (3) information-based. Presents student responses to a series of…

Learning approaches as predictors of academic performance in first year health and science students.

PubMed

Salamonson, Yenna; Weaver, Roslyn; Chang, Sungwon; Koch, Jane; Bhathal, Ragbir; Khoo, Cheang; Wilson, Ian

2013-07-01

To compare health and science students' demographic characteristics and learning approaches across different disciplines, and to examine the relationship between learning approaches and academic performance. While there is increasing recognition of a need to foster learning approaches that improve the quality of student learning, little is known about students' learning approaches across different disciplines, and their relationships with academic performance. Prospective, correlational design. Using a survey design, a total of 919 first year health and science students studying in a university located in the western region of Sydney from the following disciplines were recruited to participate in the study - i) Nursing: n = 476, ii) Engineering: n = 75, iii) Medicine: n = 77, iv) Health Sciences: n = 204, and v) Medicinal Chemistry: n = 87. Although there was no statistically significant difference in the use of surface learning among the five discipline groups, there were wide variations in the use of deep learning approach. Furthermore, older students and those with English as an additional language were more likely to use deep learning approach. Controlling for hours spent in paid work during term-time and English language usage, both surface learning approach (β = -0.13, p = 0.001) and deep learning approach (β = 0.11, p = 0.009) emerged as independent and significant predictors of academic performance. Findings from this study provide further empirical evidence that underscore the importance for faculty to use teaching methods that foster deep instead of surface learning approaches, to improve the quality of student learning and academic performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Healthcare students' experiences when integrating e-learning and flipped classroom instructional approaches.

PubMed

Telford, Mark; Senior, Emma

2017-06-08

This article describes the experiences of undergraduate healthcare students taking a module adopting a 'flipped classroom' approach. Evidence suggests that flipped classroom as a pedagogical tool has the potential to enhance student learning and to improve healthcare practice. This innovative approach was implemented within a healthcare curriculum and in a module looking at public health delivered at the beginning of year two of a 3-year programme. The focus of the evaluation study was on the e-learning resources used in the module and the student experiences of these; with a specific aim to evaluate this element of the flipped classroom approach. A mixed-methods approach was adopted and data collected using questionnaires, which were distributed across a whole cohort, and a focus group involving ten participants. Statistical analysis of the data showed the positive student experience of engaging with e-learning. The thematic analysis identified two key themes; factors influencing a positive learning experience and the challenges when developing e-learning within a flipped classroom approach. The study provides guidance for further developments and improvements when developing e-learning as part of the flipped classroom approach.

Learning in First-Year Biology: Approaches of Distance and On-Campus Students

NASA Astrophysics Data System (ADS)

Quinn, Frances Catherine

2011-01-01

This paper aims to extend previous research into learning of tertiary biology, by exploring the learning approaches adopted by two groups of students studying the same first-year biology topic in either on-campus or off-campus "distance" modes. The research involved 302 participants, who responded to a topic-specific version of the Study Process Questionnaire, and in-depth interviews with 16 of these students. Several quantitative analytic techniques, including cluster analysis and Rasch differential item functioning analysis, showed that the younger, on-campus cohort made less use of deep approaches, and more use of surface approaches than the older, off-campus group. At a finer scale, clusters of students within these categories demonstrated different patterns of learning approach. Students' descriptions of their learning approaches at interview provided richer complementary descriptions of the approach they took to their study in the topic, showing how deep and surface approaches were manifested in the study context. These findings are critically analysed in terms of recent literature questioning the applicability of learning approaches theory in mass education, and their implications for teaching and research in undergraduate biology.

Inclusive Approach to the Psycho-Pedagogical Assistance of Distance Learning

ERIC Educational Resources Information Center

Akhmetova, Daniya Z.

2014-01-01

Author focuses on three groups of problems: quality of distance learning and e-learning; necessity to develop the facilitation skills for teachers who work using distance learning technologies; realization of inclusive approach for the organization of distance learning in inclusive groups where people with disabilities study with people without…

Implementing Project Based Learning Approach to Graphic Design Course

ERIC Educational Resources Information Center

Riyanti, Menul Teguh; Erwin, Tuti Nuriah; Suriani, S. H.

2017-01-01

The purpose of this study was to develop a learning model based Commercial Graphic Design Drafting project-based learning approach, was chosen as a strategy in the learning product development research. University students as the target audience of this model are the students of the fifth semester Visual Communications Design Studies Program…

A stochastic parameterization for deep convection using cellular automata

NASA Astrophysics Data System (ADS)

Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.

2012-12-01

Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in

Organizational Approach to the Ergonomic Examination of E-Learning Modules

ERIC Educational Resources Information Center

Lavrov, Evgeniy; Kupenko, Olena; Lavryk, Tetiana; Barchenko, Natalia

2013-01-01

With a significant increase in the number of e-learning resources the issue of quality is of current importance. An analysis of existing scientific and methodological literature shows the variety of approaches, methods and tools to evaluate e-learning materials. This paper proposes an approach based on the procedure for estimating parameters of…

Student-Teachers' Approaches to Learning, Academic Performance and Teaching Efficacy

ERIC Educational Resources Information Center

Swee-Choo, Pauline Goh; Kung-Teck, Wong; Osman, Rosma

2012-01-01

Purpose: It is argued that the approaches to learning of students undergoing teacher training are likely to be related to their teaching and learning environment, especially as they move from a more regimented, structured learning environment in school to a tertiary learning environment that encourages more independent thinking and perhaps…

E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education

NASA Astrophysics Data System (ADS)

Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.

2017-01-01

E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.

Undergraduate Students' Earth Science Learning: Relationships among Conceptions, Approaches, and Learning Self-Efficacy in Taiwan

ERIC Educational Resources Information Center

Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen

2016-01-01

In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to…

Early warning of illegal development for protected areas by integrating cellular automata with neural networks.

PubMed

Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian

2013-11-30

Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Workplace-based assessment and students' approaches to learning: a qualitative inquiry.

PubMed

Al-Kadri, Hanan M; Al-Kadi, Mohammed T; Van Der Vleuten, Cees P M

2013-01-01

We have performed this research to assess the effect of work-place based assessment (WBA) practice on medical students' learning approaches. The research was conducted at the King Saud bin Abdulaziz University for Health Sciences, College of Medicine from 1 March to 31 July 2012. We conducted a qualitative, phenomenological research utilizing semi-structured individual interviews with medical students exposed to WBA. The audio-taped interviews were transcribed verbatim, analyzed, and themes were identified. We preformed investigators' triangulation, member checking with clinical supervisors and we triangulated the data with a similar research performed prior to the implementation of WBA. WBA results in variable learning approaches. Based on several affecting factors; clinical supervisors, faculty-given feedback, and assessment function, students may swing between surface, deep and effort and achievement learning approaches. Students' and supervisors' orientations on the process of WBA, utilization of peer feedback and formative rather than summative assessment facilitate successful implementation of WBA and lead to students' deeper approaches to learning. Interestingly, students and their supervisors have contradicting perceptions to WBA. A change in culture to unify students' and supervisors' perceptions of WBA, more accommodation of formative assessment, and feedback may result in students' deeper approach to learning.

Blending Online Learning with Traditional Approaches: Changing Practices

ERIC Educational Resources Information Center

Condie, Rae; Livingston, Kay

2007-01-01

Considerable claims have been made for the development of e-learning, either as stand-alone programmes or alongside more traditional approaches to teaching and learning, for students across school and tertiary education. National initiatives have improved the position of schools in terms of access to hardware and electronic networking, software…

Transforming Community Colleges Using a Learning Outcomes Approach.

ERIC Educational Resources Information Center

Shipley, Dale

Focusing on theories and practices related to outcomes-based learning (OBL), this paper presents arguments for adopting an OBL approach in Canada's community colleges. Introductory sections review internal and external reasons for making changes to the teaching and learning paradigm, such as new demands for training and reduced funding. Part I…

Arts-Based Learning: A New Approach to Nursing Education Using Andragogy.

PubMed

Nguyen, Megan; Miranda, Joyal; Lapum, Jennifer; Donald, Faith

2016-07-01

Learner-oriented strategies focusing on learning processes are needed to prepare nursing students for complex practice situations. An arts-based learning approach uses art to nurture cognitive and emotional learning. Knowles' theory of andragogy aims to develop the skill of learning and can inform the process of implementing arts-based learning. This article explores the use and evaluation of andragogy-informed arts-based learning for teaching nursing theory at the undergraduate level. Arts-based learning activities were implemented and then evaluated by students and instructors using anonymous questionnaires. Most students reported that the activities promoted learning. All instructors indicated an interest in integrating arts-based learning into the curricula. Facilitators and barriers to mainstreaming arts-based learning were highlighted. Findings stimulate implications for prospective research and education. Findings suggest that arts-based learning approaches enhance learning by supporting deep inquiry and different learning styles. Further exploration of andragogy-informed arts-based learning in nursing and other disciplines is warranted. [J Nurs Educ. 2016;55(7):407-410.]. Copyright 2016, SLACK Incorporated.

Relationships between Learning Approach, Procrastination and Academic Achievement amongst First-Year University Students

ERIC Educational Resources Information Center

Saele, Rannveig Grøm; Dahl, Tove Irene; Sørlie, Tore; Friborg, Oddgeir

2017-01-01

Individual differences in student learning influence academic performance, and two aspects influencing the learning process are the particular learning approach the students use and procrastination behaviour. We examined the relationships between learning approaches, procrastination and academic achievement (measured 1 year later as the grade…

Students' Conception of Learning Environment and Their Approach to Learning and Its Implication on Quality Education

ERIC Educational Resources Information Center

Belaineh, Matheas Shemelis

2017-01-01

Quality of education in higher institutions can be affected by different factors. It partly rests on the learning environment created by teachers and the learning approach students are employing during their learning. The main purpose of this study is to examine the learning environment at Mizan Tepi University from students' perspective and their…

Game-Enhanced Simulation as an Approach to Experiential Learning in Business English

ERIC Educational Resources Information Center

Punyalert, Sansanee

2017-01-01

This dissertation aims to integrate various learning approaches, i.e., multiple literacies, experiential learning, game-enhanced learning, and global simulation, into an extracurricular module, in which it remodels traditional ways of teaching input, specifically, the lexical- and grammatical-only approaches of business English at a private…

Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling

Treesearch

Gary Achtemeier

2012-01-01

A cellular automata fire model represents ‘elements’ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for ‘super-diffusive’ fire spread and coupled surface-layer (2-m) fire–atmosphere processes. Pressure anomalies, which are integrals of the thermal...

Students' Feedback of mDPBL Approach and the Learning Impact towards Computer Networks Teaching and Learning

ERIC Educational Resources Information Center

Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook

2018-01-01

This study presents students' feedback and learning impact on design and development of a multimedia learning in Direct Problem-Based Learning approach (mDPBL) for Computer Networks in Dian Nuswantoro University, Indonesia. This study examined the usefulness, contents and navigation of the multimedia learning as well as learning impacts towards…

Demonstrating and Evaluating an Action Learning Approach to Building Project Management Competence

NASA Technical Reports Server (NTRS)

Kotnour, Tim; Starr, Stan; Steinrock, T. (Technical Monitor)

2001-01-01

This paper contributes a description of an action-learning approach to building project management competence. This approach was designed, implemented, and evaluated for use with the Dynacs Engineering Development Contract at the Kennedy Space Center. The aim of the approach was to improve three levels of competence within the organization: individual project management skills, project team performance. and organizational capabilities such as the project management process and tools. The overall steps to the approach, evaluation results, and lessons learned are presented. Managers can use this paper to design a specific action-learning approach for their organization.

Stochastic cellular automata model for stock market dynamics

NASA Astrophysics Data System (ADS)

Bartolozzi, M.; Thomas, A. W.

2004-04-01

In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.

Learning Outcomes in Vocational Education: A Business Plan Development by Production-Based Learning Model Approach

ERIC Educational Resources Information Center

Kusumaningrum, Indrati; Hidayat, Hendra; Ganefri; Anori, Sartika; Dewy, Mega Silfia

2016-01-01

This article describes the development of a business plan by using production-based learning approach. In addition, this development also aims to maximize learning outcomes in vocational education. Preliminary analysis of curriculum and learning and the needs of the market and society become the basic for business plan development. To produce a…

Benefiting from Customer and Competitor Knowledge: A Market-Based Approach to Organizational Learning

ERIC Educational Resources Information Center

Hoe, Siu Loon

2008-01-01

Purpose: The purpose of this paper is to review the organizational learning, market orientation and learning orientation concepts, highlight the importance of market knowledge to organizational learning and recommend ways in adopting a market-based approach to organizational learning. Design/methodology/approach: The extant organizational learning…

Students awareness of learning styles and their perceptions to a mixed method approach for learning

PubMed Central

Bhagat, Anumeha; Vyas, Rashmi; Singh, Tejinder

2015-01-01

Background: Individualization of instructional method does not contribute significantly to learning outcomes although it is known that students have differing learning styles (LSs). Hence, in order to maximally enhance learning, one must try to use a mixed method approach. Hypothesis: Our hypothesis was that awareness of preferred LS and motivation to incorporate multiple learning strategies might enhance learning outcomes. Aim: Our aim was to determine the impact of awareness of LS among medical undergraduates and motivating students to use mixed methods of learning. Materials and Methods: Before awareness lecture, LS preferences were determined using Visual, Aural, Read/Write, and Kinesthetic (VARK) questionnaire. Awareness of LS was assessed using a validated questionnaire. Through a lecture, students were oriented to various LSs, impact of LS on their performance, and benefit of using mixed method approach for learning. Subsequently, group discussions were organized. After 3 months, VARK preferences and awareness of LSs were reassessed. Student narratives were collected. Qualitative analysis of the data was done. Results: There was a significant increase in the number of students who were aware of LS. The number of participants showing a change in VARK scores for various modalities of learning was also significant (P < 0.001). Conclusion: Thus, awareness of LSs motivated students to adapt other learning strategies and use mixed methods for learning. PMID:26380214

Neonatal nurses' perceptions of a work-based learning approach.

PubMed

Stanley, Helen; Simmons, Susanne

2011-09-01

To examine how senior neonatal nurses perceive their experience of a continuing professional development module on their practice. A qualitative approach was used. Focus group interviews were held with five senior neonatal nurses at band 6 and 7. Discussions were taped and transcribed verbatim and field notes captured non-verbal communication. Four themes emerged: work-based learning as a new way of learning; barriers to learning at work; professional role development; and complexities of evaluating such learning. Work-based learning emerged as an active form of learning that can develop personal and professional skills required in the neonatal workforce.

Assessing reflective thinking and approaches to learning.

PubMed

Dunn, Louise; Musolino, Gina M

2011-01-01

Facilitation of reflective practice is critical for the ongoing demands of health care practitioners. Reflective thinking concepts, grounded in the work of Dewey and Schön, emphasize critical reflection to promote transformation in beliefs and learning necessary for reflective practice. The Reflective Thinking Questionnaire (QRT) and Revised Study Process Questionnaire (RSPQ-2F) assess skill aspects of professional reasoning, with promise for measuring changes over time. The purpose of this study was to examine the reliability and responsiveness and the model validity of reflective thinking and approaches to learning measures for U.S. health professions students enrolled in entry-level occupational (MOT) and physical therapy (DPT) programs. This measurement study addressed reliability and responsiveness of two measures, the QRT and RSPQ-2F, for graduate health professionals. A convenience sample of 125 MOT and DPT students participated in the two-measure, test-retest investigation, with electronic data collection. Outcomes support the stability of the four-scale QRT (ICC 0.63 to 0.82) and the two-scale RSPQ-2F (ICC 0.91 and 0.87). Descriptive data supporting responsiveness are presented. With noted limitations, the results support the use of the QRT and RSPQ-2F measures to assess changes in reflective thinking and approaches to learning. Measurement of these learning outcomes furthers our understanding and knowledge about instructional strategies, development of professional reasoning, and fostering of self-directed learning within MOT and DPT programs.

Effects of a blended learning approach on student outcomes in a graduate-level public health course.

PubMed

Kiviniemi, Marc T

2014-03-11

Blended learning approaches, in which in-person and online course components are combined in a single course, are rapidly increasing in health sciences education. Evidence for the relative effectiveness of blended learning versus more traditional course approaches is mixed. The impact of a blended learning approach on student learning in a graduate-level public health course was examined using a quasi-experimental, non-equivalent control group design. Exam scores and course point total data from a baseline, "traditional" approach semester (n = 28) was compared to that from a semester utilizing a blended learning approach (n = 38). In addition, student evaluations of the blended learning approach were evaluated. There was a statistically significant increase in student performance under the blended learning approach (final course point total d = 0.57; a medium effect size), even after accounting for previous academic performance. Moreover, student evaluations of the blended approach were very positive and the majority of students (83%) preferred the blended learning approach. Blended learning approaches may be an effective means of optimizing student learning and improving student performance in health sciences courses.

Classroom quality and academic skills: Approaches to learning as a moderator.

PubMed

Meng, Christine

2015-12-01

The purpose of this study was to examine whether approaches to learning moderated the association between child care classroom environment and Head Start children's academic skills. The data came from the Head Start Family and Child Experiences Survey (FACES-2003 Cohort). The dataset is a nationally representative longitudinal study of Head Start children. The sample was selected using the stratified 4-stage sampling procedure. Data was collected in fall 2003, spring 2004, spring 2005, and spring 2006 in the first year of kindergarten. Participants included 3- and 4-year-old Head Start children (n = 786; 387 boys, 399 girls; 119 Hispanic children, 280 African American children, 312 Caucasian children). Head Start children's academic skills in letter-word identification, dictation/spelling, and mathematics at the 4 time points were measured by the Woodcock-Johnson Achievement Battery tests. Approaches to learning in fall 2003 was measured by the teacher report of the Preschool Learning Behaviors Scale. Child care classroom quality in fall 2003 was measured by the revised Early Childhood Environment Rating Scale. Results of the linear mixed effects models demonstrated that approaches to learning significantly moderated the effect of child care classroom quality on Head Start children's writing and spelling. Specifically, positive approaches to learning mitigated the negative effect of lower levels of classroom quality on dictation/spelling. Results underscore the important role of approaches to learning as a protective factor. Implications for early childhood educators with an emphasis on learning goals for disengaged children are discussed. (c) 2015 APA, all rights reserved).

Online Learning: Learner Characteristics and Their Approaches to Managing Learning

ERIC Educational Resources Information Center

del Valle, Rodrigo; Duffy, Thomas M.

2009-01-01

Using cluster analysis this study investigated the characteristics of learning strategies learners use in online courses with one-on-one mentoring. Three distinct approaches were identified: "Mastery oriented", "Task focused" and "Minimalist in effort". Despite the widespread concern that students will have difficulty managing their time in online…

Progress testing in the medical curriculum: students' approaches to learning and perceived stress.

PubMed

Chen, Yan; Henning, Marcus; Yielder, Jill; Jones, Rhys; Wearn, Andy; Weller, Jennifer

2015-09-11

Progress Tests (PTs) draw on a common question bank to assess all students in a programme against graduate outcomes. Theoretically PTs drive deep approaches to learning and reduce assessment-related stress. In 2013, PTs were introduced to two year groups of medical students (Years 2 and 4), whereas students in Years 3 and 5 were taking traditional high-stakes assessments. Staged introduction of PTs into our medical curriculum provided a time-limited opportunity for a comparative study. The main purpose of the current study was to compare the impact of PTs on undergraduate medical students' approaches to learning and perceived stress with that of traditional high-stakes assessments. We also aimed to investigate the associations between approaches to learning, stress and PT scores. Undergraduate medical students (N = 333 and N = 298 at Time 1 and Time 2 respectively) answered the Revised Study Process Questionnaire (R-SPQ-2F) and the Perceived Stress Scale (PSS) at two time points to evaluate change over time. The R-SPQ-2F generated a surface approach and a deep approach score; the PSS generated an overall perceived stress score. We found no significant differences between the two groups in approaches to learning at either time point, and no significant changes in approaches to learning over time in either cohort. Levels of stress increased significantly at the end of the year (Time 2) for students in the traditional assessment cohort, but not in the PT cohort. In the PT cohort, surface approach to learning, but not stress, was a significant negative predictor of students' PT scores. While confirming an association between surface approaches to learning and lower PT scores, we failed to demonstrate an effect of PTs on approaches to learning. However, a reduction in assessment-associated stress is an important finding.

A Project-Based Digital Storytelling Approach for Improving Students' Learning Motivation, Problem-Solving Competence and Learning Achievement

ERIC Educational Resources Information Center

Hung, Chun-Ming; Hwang, Gwo-Jen; Huang, Iwen

2012-01-01

Although project-based learning is a well-known and widely used instructional strategy, it remains a challenging issue to effectively apply this approach to practical settings for improving the learning performance of students. In this study, a project-based digital storytelling approach is proposed to cope with this problem. With a…

Safety impacts of red light cameras at signalized intersections based on cellular automata models.

PubMed

Chai, C; Wong, Y D; Lum, K M

2015-01-01

This study applies a simulation technique to evaluate the hypothesis that red light cameras (RLCs) exert important effects on accident risks. Conflict occurrences are generated by simulation and compared at intersections with and without RLCs to assess the impact of RLCs on several conflict types under various traffic conditions. Conflict occurrences are generated through simulating vehicular interactions based on an improved cellular automata (CA) model. The CA model is calibrated and validated against field observations at approaches with and without RLCs. Simulation experiments are conducted for RLC and non-RLC intersections with different geometric layouts and traffic demands to generate conflict occurrences that are analyzed to evaluate the hypothesis that RLCs exert important effects on road safety. The comparison of simulated conflict occurrences show favorable safety impacts of RLCs on crossing conflicts and unfavorable impacts for rear-end conflicts during red/amber phases. Corroborative results are found from broad analysis of accident occurrence. RLCs are found to have a mixed effect on accident risk at signalized intersections: crossing collisions are reduced, whereas rear-end collisions may increase. The specially developed CA model is found to be a feasible safety assessment tool.

Morningness-eveningness preferences, learning approach and academic achievement of undergraduate medical students.

PubMed

Akram, Nimra; Khan, Naheed; Ameen, Mehreen; Mahmood, Shahmeera; Shamim, Komal; Amin, Marium; Rana, Qurrat Ul Ain

2018-05-15

Several studies have focused on determining the effect of chronotype and learning approach on academic achievement separately indicating that morning types have an academic advantage over the evening types and so have the deep learners over the surface learners. But, surprisingly none have assessed the possible relationship between chronotype and learning approach. So, the current study aimed to evaluate this association and their individual influence on academic performance as indicated by the Cumulative Grade Point Average (CGPA) as well as the effect of their interaction on academic performance. The study included 345 undergraduate medical students who responded to reduced Morningness-Eveningness Questionnaire and Biggs Revised Two-Factor Study Process Questionnaire. Morning types indulged in deep learning while evening types in surface learning. Morning and evening types did not differ on academic performance but deep learners had better academic outcomes than their counterparts. The interaction between chronotype and learning approach was significant on determining academic achievement. Our findings gave the impression that chronotype could have an impact on academic performance not directly but indirectly through learning approaches.

Investigating Elementary Students' Learning Approaches, Motivational Goals, and Achievement in Science

ERIC Educational Resources Information Center

Hacieminoglu, Esme; Yilmaz-Tuzun, Ozgul; Ertepinar, Hamide

2009-01-01

This study examined the relationships among students' learning approaches, motivational goals, previous science grades, and their science achievement for the concepts related to atomic theory and explored the effects of gender and sociodemographic variables on students' learning approaches, motivational goals, and their science achievement for the…

Effects of a blended learning approach on student outcomes in a graduate-level public health course

PubMed Central

2014-01-01

Background Blended learning approaches, in which in-person and online course components are combined in a single course, are rapidly increasing in health sciences education. Evidence for the relative effectiveness of blended learning versus more traditional course approaches is mixed. Method The impact of a blended learning approach on student learning in a graduate-level public health course was examined using a quasi-experimental, non-equivalent control group design. Exam scores and course point total data from a baseline, “traditional” approach semester (n = 28) was compared to that from a semester utilizing a blended learning approach (n = 38). In addition, student evaluations of the blended learning approach were evaluated. Results There was a statistically significant increase in student performance under the blended learning approach (final course point total d = 0.57; a medium effect size), even after accounting for previous academic performance. Moreover, student evaluations of the blended approach were very positive and the majority of students (83%) preferred the blended learning approach. Conclusions Blended learning approaches may be an effective means of optimizing student learning and improving student performance in health sciences courses. PMID:24612923

Approaches to Studying and Students' Use of a Computer Supported Learning Environment

ERIC Educational Resources Information Center

Foster, Jonathan; Lin, Angela

2007-01-01

Although studies of students' study approaches in face to face learning environments are commonplace, studies investigating the role of students' study approaches in online learning environments is currently a less explored area. This paper presents the findings of a survey aimed at investigating the relationship between students' approaches to…

Meta-Analysis of Jelajah Alam Sekitar (JAS) Approach Implementation in Learning Process

ERIC Educational Resources Information Center

Ngabekti, S.; Ridlo, S.; Peniati, E.; Martanto, R.

2017-01-01

The results of tracer studies on the approach of Jelajah Alam Sekitar (JAS) or environment exploring learning has been detected is used in eight provinces in Indonesia and studied in the learning begin primary school to college. Then, how the effectiveness of the implementation of the JAS approach in improving the learning process. This study uses…

Mixed-valence molecular four-dot unit for quantum cellular automata: Vibronic self-trapping and cell-cell response.

PubMed

Tsukerblat, Boris; Palii, Andrew; Clemente-Juan, Juan Modesto; Coronado, Eugenio

2015-10-07

Our interest in this article is prompted by the vibronic problem of charge polarized states in the four-dot molecular quantum cellular automata (mQCA), a paradigm for nanoelectronics, in which binary information is encoded in charge configuration of the mQCA cell. Here, we report the evaluation of the electronic levels and adiabatic potentials of mixed-valence (MV) tetra-ruthenium (2Ru(ii) + 2Ru(iii)) derivatives (assembled as two coupled Creutz-Taube complexes) for which molecular implementations of quantum cellular automata (QCA) was proposed. The cell based on this molecule includes two holes shared among four spinless sites and correspondingly we employ the model which takes into account the two relevant electron transfer processes (through the side and through the diagonal of the square) as well as the difference in Coulomb energies for different instant positions of localization of the hole pair. The combined Jahn-Teller (JT) and pseudo JT vibronic coupling is treated within the conventional Piepho-Krauzs-Schatz model adapted to a bi-electronic MV species with the square-planar topology. The adiabatic potentials are evaluated for the low lying Coulomb levels in which the antipodal sites are occupied, the case just actual for utilization in mQCA. The conditions for the vibronic self-trapping in spin-singlet and spin-triplet states are revealed in terms of the two actual transfer pathways parameters and the strength of the vibronic coupling. Spin related effects in degrees of the localization which are found for spin-singlet and spin-triplet states are discussed. The polarization of the cell is evaluated and we demonstrate how the partial delocalization caused by the joint action of the vibronic coupling and electron transfer processes influences polarization of a four-dot cell. The results obtained within the adiabatic approach are compared with those based on the numerical solution of the dynamic vibronic problem. Finally, the Coulomb interaction between

Opening Lines: Approaches to the Scholarship of Teaching and Learning.

ERIC Educational Resources Information Center

Hutchings, Pat, Ed.

This publication features reports by eight Carnegie Scholars who are working to develop a scholarship of teaching and learning that will advance the profession of teaching and improve student learning. Following the Introduction, "Approaching the Scholarship of Teaching and Learning" (Pat Hutchings), the papers are: "Investigating Student Learning…

Adult Learning in Health and Safety: Some Issues and Approaches.

ERIC Educational Resources Information Center

O Fathaigh, Mairtin

This document, which was developed for presentation at a seminar on adult learning and safety, examines approaches to occupational safety and health (OSH) learning/training in the workplace. Section 1 examines selected factors affecting adults' learning in workplace OSH programs. The principal dimensions along which individual adult learners will…

Holistic Approach to Learning and Teaching Introductory Object-Oriented Programming

ERIC Educational Resources Information Center

Thota, Neena; Whitfield, Richard

2010-01-01

This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities,…

A Learning Progressions Approach to Early Algebra Research and Practice

ERIC Educational Resources Information Center

Fonger, Nicole L.; Stephens, Ana; Blanton, Maria; Knuth, Eric

2015-01-01

We detail a learning progressions approach to early algebra research and how existing work around learning progressions and trajectories in mathematics and science education has informed our development of a four-component theoretical framework consisting of: a curricular progression of learning goals across big algebraic ideas; an instructional…

Real-Time Extended Interface Automata for Software Testing Cases Generation

PubMed Central

Yang, Shunkun; Xu, Jiaqi; Man, Tianlong; Liu, Bin

2014-01-01

Testing and verification of the interface between software components are particularly important due to the large number of complex interactions, which requires the traditional modeling languages to overcome the existing shortcomings in the aspects of temporal information description and software testing input controlling. This paper presents the real-time extended interface automata (RTEIA) which adds clearer and more detailed temporal information description by the application of time words. We also establish the input interface automaton for every input in order to solve the problems of input controlling and interface covering nimbly when applied in the software testing field. Detailed definitions of the RTEIA and the testing cases generation algorithm are provided in this paper. The feasibility and efficiency of this method have been verified in the testing of one real aircraft braking system. PMID:24892080

A work-based learning approach for clinical support workers on mental health inpatient wards.

PubMed

Kemp, Philip; Gilding, Moorene; Seewooruttun, Khooseal; Walsh, Hannah

2016-09-14

Background With a rise in the number of unqualified staff providing health and social care, and reports raising concerns about the quality of care provided, there is a need to address the learning needs of clinical support workers. This article describes a qualitative evaluation of a service improvement project that involved a work-based learning approach for clinical support workers on mental health inpatient wards. Aim To investigate and identify insights in relation to the content and process of learning using a work-based learning approach for clinical support workers. Method This was a qualitative evaluation of a service improvement project involving 25 clinical support workers at the seven mental health inpatient units in South London and Maudsley NHS Foundation Trust. Three clinical skills tutors were appointed to develop, implement and evaluate the work-based learning approach. Four sources of data were used to evaluate this approach, including reflective journals, qualitative responses to questionnaires, three focus groups involving the clinical support workers and a group interview involving the clinical skills tutors. Data were analysed using thematic analysis. Findings The work-based learning approach was highly valued by the clinical support workers and enhanced learning in practice. Face-to-face learning in practice helped the clinical support workers to develop practice skills and reflective learning skills. Insights relating to the role of clinical support workers were also identified, including the benefits of face-to-face supervision in practice, particularly in relation to the interpersonal aspects of care. Conclusion A work-based learning approach has the potential to enhance care delivery by meeting the learning needs of clinical support workers and enabling them to apply learning to practice. Care providers should consider how the work-based learning approach can be used on a systematic, organisation-wide basis in the context of budgetary

An exploration of the relationship between academic and experiential learning approaches in vocational education.

PubMed

de Jong, Jan A Stavenga; Wierstra, Ronny F A; Hermanussen, José

2006-03-01

Research on individual learning approaches (or learning styles) is split in two traditions, one of which is biased towards academic learning, and the other towards learning from direct experience. In the reported study, the two traditions are linked by investigating the relationships between school-based (academic) and work-based (experiential) learning approaches of students in vocational education programs. Participants were 899 students of a Dutch school for secondary vocational education; 758 provided data on school-based learning, and 407 provided data on work-based learning, resulting in an overlap of 266 students from whom data were obtained on learning in both settings. Learning approaches in school and work settings were measured with questionnaires. Using factor analysis and cluster analysis, items and students were grouped, both with respect to school- and work-based learning. The study identified two academic learning dimensions (constructive learning and reproductive learning), and three experiential learning dimensions (analysis, initiative, and immersion). Construction and analysis were correlated positively, and reproduction and initiative negatively. Cluster analysis resulted in the identification of three school-based learning orientations and three work-based learning orientations. The relation between the two types of learning orientations, expressed in Cramér's V, appeared to be weak. It is concluded that learning approaches are relatively context specific, which implies that neither theoretical tradition can claim general applicability.

Effective Learning Approaches for Sustainability: A Student Perspective

ERIC Educational Resources Information Center

Erskine, Laura; Johnson, Scott D.

2012-01-01

The authors offer an exploratory glimpse into the perceived effectiveness of learning approaches presently being used to teach students about sustainability in a business school setting. Sustainability is a topic of growing importance in business and business education. Using teaching approaches generated through self-reports related to the…

Dynamic and quantitative method of analyzing service consistency evolution based on extended hierarchical finite state automata.

PubMed

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

PubMed Central

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA. PMID:24772033

Using the Learners-as-Ethnographers Approach to Enhance Intercultural Learning among American College Students Learning Chinese as a Foreign Language

ERIC Educational Resources Information Center

Lu, Minhui

2012-01-01

This study explored how the learners-as-ethnographers (LAE) approach facilitated intercultural learning among American students learning Chinese as a foreign language. Two research questions addressed the effectiveness of the LAE approach and students' learning experiences in a non-immersion context. I designed six ethnographic tasks for the…

Revisiting Approaches to Learning in Science and Engineering: A Case Study

ERIC Educational Resources Information Center

Gynnild, V.; Myrhaug, D.

2012-01-01

Several studies have applied the dichotomy of deep and surface approaches to learning in a range of disciplinary contexts. Existing questionnaires have largely assumed the existence of these constructs; however, in a recent study Case and Marshall (2004) described two additional context-specific approaches to learning in engineering. The current…

Phase change cellular automata modeling of GeTe, GaSb and SnSe stacked chalcogenide films

NASA Astrophysics Data System (ADS)

Mihai, C.; Velea, A.

2018-06-01

Data storage needs are increasing at a rapid pace across all economic sectors, so the need for new memory technologies with adequate capabilities is also high. Phase change memories (PCMs) are a leading contender in the emerging race for non-volatile memories due to their fast operation speed, high scalability, good reliability and low power consumption. However, in order to meet the present and future storage demands, PCM technologies must further increase the storage density. Here, we employ a probabilistic cellular automata approach to explore the multi-step threshold switching from the reset (off) to the set (on) state in chalcogenide stacked structures. Simulations have shown that in order to obtain multi-step switching with high contrast among different resistance states, the stacked structure needs to contain materials with a large difference among their crystallization temperatures and careful tuning of strata thicknesses. The crystallization dynamics can be controlled through the external energy pulses applied to the system, in such a way that a balance between nucleation and growth in phase change behavior can be achieved, optimized for PCMs.

Conway's Game of Life is a near-critical metastable state in the multiverse of cellular automata.

PubMed

Reia, Sandro M; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ = 0) and an active phase density, with ρ = 0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ(2D) ≈ 0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

Conway's game of life is a near-critical metastable state in the multiverse of cellular automata

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ =0) and an active phase density, with ρ =0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ2D≈0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

An Approach to Learning by Construction

ERIC Educational Resources Information Center

Bagarukayo, Emily; Weide, Theo; Meijden, Henny

2012-01-01

This paper proposes an innovative idea for providing affordable, sustainable, and meaningful education for students in Least Developed Countries (LDCs). The authors show how a Digital Learning Environment (DLE) can play a central role in community development. The authors develop and validate an approach for introduction of an ICT education…

Land use change modeling through scenario-based cellular automata Markov: improving spatial forecasting.

PubMed

Jahanishakib, Fatemeh; Mirkarimi, Seyed Hamed; Salmanmahiny, Abdolrassoul; Poodat, Fatemeh

2018-05-08

Efficient land use management requires awareness of past changes, present actions, and plans for future developments. Part of these requirements is achieved using scenarios that describe a future situation and the course of changes. This research aims to link scenario results with spatially explicit and quantitative forecasting of land use development. To develop land use scenarios, SMIC PROB-EXPERT and MORPHOL methods were used. It revealed eight scenarios as the most probable. To apply the scenarios, we considered population growth rate and used a cellular automata-Markov chain (CA-MC) model to implement the quantified changes described by each scenario. For each scenario, a set of landscape metrics was used to assess the ecological integrity of land use classes in terms of fragmentation and structural connectivity. The approach enabled us to develop spatial scenarios of land use change and detect their differences for choosing the most integrated landscape pattern in terms of landscape metrics. Finally, the comparison between paired forecasted scenarios based on landscape metrics indicates that scenarios 1-1, 2-2, 3-2, and 4-1 have a more suitable integrity. The proposed methodology for developing spatial scenarios helps executive managers to create scenarios with many repetitions and customize spatial patterns in real world applications and policies.

Towards measuring the semantic capacity of a physical medium demonstrated with elementary cellular automata.

PubMed

Dittrich, Peter

2018-02-01

The organic code concept and its operationalization by molecular codes have been introduced to study the semiotic nature of living systems. This contribution develops further the idea that the semantic capacity of a physical medium can be measured by assessing its ability to implement a code as a contingent mapping. For demonstration and evaluation, the approach is applied to a formal medium: elementary cellular automata (ECA). The semantic capacity is measured by counting the number of ways codes can be implemented. Additionally, a link to information theory is established by taking multivariate mutual information for quantifying contingency. It is shown how ECAs differ in their semantic capacities, how this is related to various ECA classifications, and how this depends on how a meaning is defined. Interestingly, if the meaning should persist for a certain while, the highest semantic capacity is found in CAs with apparently simple behavior, i.e., the fixed-point and two-cycle class. Synergy as a predictor for a CA's ability to implement codes can only be used if context implementing codes are common. For large context spaces with sparse coding contexts synergy is a weak predictor. Concluding, the approach presented here can distinguish CA-like systems with respect to their ability to implement contingent mappings. Applying this to physical systems appears straight forward and might lead to a novel physical property indicating how suitable a physical medium is to implement a semiotic system. Copyright © 2017 Elsevier B.V. All rights reserved.

A Collaborative Game-Based Learning Approach to Improving Students' Learning Performance in Science Courses

ERIC Educational Resources Information Center

Sung, Han-Yu; Hwang, Gwo-Jen

2013-01-01

In this study, a collaborative game-based learning environment is developed by integrating a grid-based Mindtool to facilitate the students to share and organize what they have learned during the game-playing process. To evaluate the effectiveness of the proposed approach, an experiment has been conducted in an elementary school natural science…

A Blended Learning Approach to Teach Fluid Mechanics in Engineering

ERIC Educational Resources Information Center

Rahman, Ataur

2017-01-01

This paper presents a case study on the teaching and learning of fluid mechanics at the University of Western Sydney (UWS), Australia, by applying a blended learning approach (BLA). In the adopted BLA, various flexible learning materials have been made available to the students such as online recorded lectures, online recorded tutorials, hand…

On the topological sensitivity of cellular automata

NASA Astrophysics Data System (ADS)

Baetens, Jan M.; De Baets, Bernard

2011-06-01

Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.

Using Flipped Classroom Approach to Explore Deep Learning in Large Classrooms

ERIC Educational Resources Information Center

Danker, Brenda

2015-01-01

This project used two Flipped Classroom approaches to stimulate deep learning in large classrooms during the teaching of a film module as part of a Diploma in Performing Arts course at Sunway University, Malaysia. The flipped classes utilized either a blended learning approach where students first watched online lectures as homework, and then…

Towards a Semantic E-Learning Theory by Using a Modelling Approach

ERIC Educational Resources Information Center

Yli-Luoma, Pertti V. J.; Naeve, Ambjorn

2006-01-01

In the present study, a semantic perspective on e-learning theory is advanced and a modelling approach is used. This modelling approach towards the new learning theory is based on the four SECI phases of knowledge conversion: Socialisation, Externalisation, Combination and Internalisation, introduced by Nonaka in 1994, and involving two levels of…

The Development of Blended-Learning Teaching Portfolio Course Using TBL Approach

ERIC Educational Resources Information Center

Pardamean, Bens; Prabowo, Harjanto; Muljo, Hery Harjono; Suparyanto, Teddy; Masli, Eryadi K.; Donovan, Jerome

2017-01-01

This article was written to develop a teaching portfolio that helps lecturers maximize the benefits of blended learning, a combination of in-person and online learning, through the use of Team-Based Learning (TBL) teaching and learning approach. Studies show that TBL can provide opportunities in developing teamwork capabilities and enhancing…

A Comparison of Three Approaches to Model Human Behavior

NASA Astrophysics Data System (ADS)

Palmius, Joel; Persson-Slumpi, Thomas

2010-11-01

One way of studying social processes is through the use of simulations. The use of simulations for this purpose has been established as its own field, social simulations, and has been used for studying a variety of phenomena. A simulation of a social setting can serve as an aid for thinking about that social setting, and for experimenting with different parameters and studying the outcomes caused by them. When using the simulation as an aid for thinking and experimenting, the chosen simulation approach will implicitly steer the simulationist towards thinking in a certain fashion in order to fit the model. To study the implications of model choice on the understanding of a setting where human anticipation comes into play, a simulation scenario of a coffee room was constructed using three different simulation approaches: Cellular Automata, Systems Dynamics and Agent-based modeling. The practical implementations of the models were done in three different simulation packages: Stella for Systems Dynamic, CaFun for Cellular automata and SesAM for Agent-based modeling. The models were evaluated both using Randers' criteria for model evaluation, and through introspection where the authors reflected upon how their understanding of the scenario was steered through the model choice. Further the software used for implementing the simulation models was evaluated, and practical considerations for the choice of software package are listed. It is concluded that the models have very different strengths. The Agent-based modeling approach offers the most intuitive support for thinking about and modeling a social setting where the behavior of the individual is in focus. The Systems Dynamics model would be preferable in situations where populations and large groups would be studied as wholes, but where individual behavior is of less concern. The Cellular Automata models would be preferable where processes need to be studied from the basis of a small set of very simple rules. It is

Learning Social Studies through Mastery Approach

ERIC Educational Resources Information Center

Adeyemi, B. A.

2007-01-01

This study examined learning Social Studies by investigating the effectiveness of mastery approach on students' performance in Social Studies of two groups of students drawn from Osun State College of Education, Ila-Orangun and University of Uyo, Ila-Orangun Study Centre which consisted of 200 level Social Studies students and 200 level degree…

Epistemological Belief and Learning Approaches of Students in Higher Institutions of Learning in Malaysia

ERIC Educational Resources Information Center

Ismail, Habsah; Hassan, Aminuddin; Muhamad, Mohd. Mokhtar; Ali, Wan Zah Wan; Konting, Mohd. Majid

2013-01-01

This is an investigation of the students' beliefs about the nature of knowledge or epistemological beliefs, and the relation of these beliefs on their learning approaches. Students chosen as samples of the study were from both public and private higher institutions of learning in Malaysia. The instrument used in the study consists of 49 items…

Finding accurate frontiers: A knowledge-intensive approach to relational learning

NASA Technical Reports Server (NTRS)

Pazzani, Michael; Brunk, Clifford

1994-01-01

An approach to analytic learning is described that searches for accurate entailments of a Horn Clause domain theory. A hill-climbing search, guided by an information based evaluation function, is performed by applying a set of operators that derive frontiers from domain theories. The analytic learning system is one component of a multi-strategy relational learning system. We compare the accuracy of concepts learned with this analytic strategy to concepts learned with an analytic strategy that operationalizes the domain theory.

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

PubMed

Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

2017-08-10

Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

Teaching Reading to Learning Disabled Children: A Fourth Approach.

ERIC Educational Resources Information Center

Bateman, Barbara

The evidence presented in this paper suggests that deficits in selective skills are primary factors in learning disabilities, and that aptitude/treatment interaction models may be useful in devising teaching methods for the reading instruction of learning disabled children. After reviewing various approaches to teaching reading to learning…

Changing Students' Approaches to Learning: A Two-Year Study within a University Teacher Training Course

ERIC Educational Resources Information Center

Gijbels, David; Coertjens, Liesje; Vanthournout, Gert; Struyf, Elke; Van Petegem, Peter

2009-01-01

Inciting a deep approach to learning in students is difficult. The present research poses two questions: can a constructivist learning-assessment environment change students' approaches towards a more deep approach? What effect does additional feedback have on the changes in learning approaches? Two cohorts of students completed questionnaires…

A study for bank effect on ship traffic in narrow water channels using cellular automata

NASA Astrophysics Data System (ADS)

Sun, Zhuo; Cong, Shuang; Pan, Junnan; Zheng, Jianfeng

2017-12-01

In narrow water channels, bank might affect nearby ships due to hydrodynamic forces (bank effect). To avoid accidents, different sailing rules (i.e., lane-changing, speed control) are required. In this paper, a two-lane cellular automata model is proposed to evaluate such phenomena. Numerical experiments show that ships will form a “slow-moving chunk” in the bank area, which will significantly block the flux. As further study demonstrated to alleviate bank effect, ship speed and bank length should be controlled.

An Interactive Approach to Learning and Teaching in Visual Arts Education

ERIC Educational Resources Information Center

Tomljenovic, Zlata

2015-01-01

The present research focuses on modernising the approach to learning and teaching the visual arts in teaching practice, as well as examining the performance of an interactive approach to learning and teaching in visual arts classes with the use of a combination of general and specific (visual arts) teaching methods. The study uses quantitative…

Approaches to Learning and Age in Predicting College Students' Academic Achievement

ERIC Educational Resources Information Center

Cetin, Baris

2016-01-01

The aim of this study is to determine whether the approaches to learning and age are significantly correlated to grade point average (GPA) in early childhood education students. In addition, another purpose of this study is to determine whether approaches to learning and age predicted students' GPAs in the Early Childhood Education Department. The…