Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein
2016-06-01
This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. PMID:27154739
Irregular Cellular Learning Automata.
Esnaashari, Mehdi; Meybodi, Mohammad Reza
2015-08-01
Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integration placement. In this paper, an extension of CLA called irregular CLA (ICLA) is introduced. This extension is obtained by removing the structure regularity assumption in CLA. Irregularity in the structure of ICLA is needed in some applications, such as computer networks, web mining, and grid computing. The concept of expediency has been introduced for ICLA and then, conditions under which an ICLA becomes expedient are analytically found. PMID:25291810
Linear System Control Using Stochastic Learning Automata
NASA Technical Reports Server (NTRS)
Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.
1998-01-01
This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.
Varieties of learning automata: an overview.
Thathachar, M L; Sastry, P S
2002-01-01
Automata models of learning systems introduced in the 1960s were popularized as learning automata (LA) in a survey paper by Narendra and Thathachar (1974). Since then, there have been many fundamental advances in the theory as well as applications of these learning models. In the past few years, the structure of LA, has been modified in several directions to suit different applications. Concepts such as parameterized learning automata (PLA), generalized learning,automata (GLA), and continuous action-set learning automata (CALA) have been proposed, analyzed, and applied to solve many significant learning problems. Furthermore, groups of LA forming teams and feedforward networks have been shown to converge to desired solutions under appropriate learning algorithms. Modules of LA have been used for parallel operation with consequent increase in speed of convergence. All of these concepts and results are relatively new and are scattered in technical literature. An attempt has been made in this paper to bring together the main ideas involved in a unified framework and provide pointers to relevant references. PMID:18244878
Solving multiconstraint assignment problems using learning automata.
Horn, Geir; Oommen, B John
2010-02-01
This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the
Abductive learning of quantized stochastic processes with probabilistic finite automata.
Chattopadhyay, Ishanu; Lipson, Hod
2013-02-13
We present an unsupervised learning algorithm (GenESeSS) to infer the causal structure of quantized stochastic processes, defined as stochastic dynamical systems evolving over discrete time, and producing quantized observations. Assuming ergodicity and stationarity, GenESeSS infers probabilistic finite state automata models from a sufficiently long observed trace. Our approach is abductive; attempting to infer a simple hypothesis, consistent with observations and modelling framework that essentially fixes the hypothesis class. The probabilistic automata we infer have no initial and terminal states, have no structural restrictions and are shown to be probably approximately correct-learnable. Additionally, we establish rigorous performance guarantees and data requirements, and show that GenESeSS correctly infers long-range dependencies. Modelling and prediction examples on simulated and real data establish relevance to automated inference of causal stochastic structures underlying complex physical phenomena. PMID:23277601
Sampling from complex networks using distributed learning automata
NASA Astrophysics Data System (ADS)
Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza
2014-02-01
A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.
Algorithmic crystal chemistry: A cellular automata approach
Krivovichev, S. V.
2012-01-15
Atomic-molecular mechanisms of crystal growth can be modeled based on crystallochemical information using cellular automata (a particular case of finite deterministic automata). In particular, the formation of heteropolyhedral layered complexes in uranyl selenates can be modeled applying a one-dimensional three-colored cellular automaton. The use of the theory of calculations (in particular, the theory of automata) in crystallography allows one to interpret crystal growth as a computational process (the realization of an algorithm or program with a finite number of steps).
On the applications of multiplicity automata in learning
Beimel, A.; Bergadano, F.; Bshouty, N.H.
1996-12-31
Recently the learnability of multiplicity automata attracted a lot of attention, mainly because of its implications on the learnability of several classes of DNF formulae. In this paper we further study the learnability of multiplicity automata. Our starting point is a known theorem from automata theory relating the number of states in a minimal multiplicity automaton for a function f to the rank of a certain matrix F. With this theorem in hand we obtain the following results: (1) A new simple algorithm for learning multiplicity automata in the spirit with a better query complexity. As a result, we improve the complexity for all classes that use the algorithms of and also obtain the best query complexity for several classes known to be learnable by other methods such as decision trees and polynomials over GF(2). (2) We prove the learnability of some new classes that were not known to be learnable before. Most notably, the class of polynomials over finite fields, the class of bounded-degree polynomials over infinite fields, the class of XOR of terms, and a certain class of decision-trees. (3) While multiplicity automata were shown to be useful to prove the learnability of some subclasses of DNF formulae and various other classes, we study the limitations of this method. We prove that this method cannot be used to resolve the learnability of some other open problems such as the learnability of general DNF formulae or even k -term DNF for k = {omega}(log n) or satisfy-s DNF formulae for s = {omega}(1). These results are proven by exhibiting functions in the above classes that require multiplicity automata with superpolynomial number of states.
Incremental Learning of Cellular Automata for Parallel Recognition of Formal Languages
NASA Astrophysics Data System (ADS)
Nakamura, Katsuhiko; Imada, Keita
Parallel language recognition by cellular automata (CAs) is currently an important subject in computation theory. This paper describes incremental learning of one-dimensional, bounded, one-way, cellular automata (OCAs) that recognize formal languages from positive and negative sample strings. The objectives of this work are to develop automatic synthesis of parallel systems and to contribute to the theory of real-time recognition by cellular automata. We implemented methods to learn the rules of OCAs in the Occam system, which is based on grammatical inference of context-free grammars (CFGs) implemented in Synapse. An important feature of Occam is incremental learning by a rule generation mechanism called bridging and the search for rule sets. The bridging looks for and fills gaps in incomplete space-time transition diagrams for positive samples. Another feature of our approach is that the system synthesizes minimal or semi-minimal rule sets of CAs. This paper reports experimental results on learning several OCAs for fundamental formal languages including sets of balanced parentheses and palindromes as well as the set {a n b n c n | n ≥ 1}.
A quantum model for autonomous learning automata
NASA Astrophysics Data System (ADS)
Siomau, Michael
2014-05-01
The idea of information encoding on quantum bearers and its quantum-mechanical processing has revolutionized our world and brought mankind on the verge of enigmatic era of quantum technologies. Inspired by this idea, in present paper, we search for advantages of quantum information processing in the field of machine learning. Exploiting only basic properties of the Hilbert space, superposition principle of quantum mechanics and quantum measurements, we construct a quantum analog for Rosenblatt's perceptron, which is the simplest learning machine. We demonstrate that the quantum perceptron is superior to its classical counterpart in learning capabilities. In particular, we show that the quantum perceptron is able to learn an arbitrary (Boolean) logical function, perform the classification on previously unseen classes and even recognize the superpositions of learned classes—the task of high importance in applied medical engineering.
LAHS: A novel harmony search algorithm based on learning automata
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Yousefi, Moslem; Abdullah, Abdul Hanan; Darus, Amer Nordin
2013-12-01
This study presents a learning automata-based harmony search (LAHS) for unconstrained optimization of continuous problems. The harmony search (HS) algorithm performance strongly depends on the fine tuning of its parameters, including the harmony consideration rate (HMCR), pitch adjustment rate (PAR) and bandwidth (bw). Inspired by the spur-in-time responses in the musical improvisation process, learning capabilities are employed in the HS to select these parameters based on spontaneous reactions. An extensive numerical investigation is conducted on several well-known test functions, and the results are compared with the HS algorithm and its prominent variants, including the improved harmony search (IHS), global-best harmony search (GHS) and self-adaptive global-best harmony search (SGHS). The numerical results indicate that the LAHS is more efficient in finding optimum solutions and outperforms the existing HS algorithm variants.
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
Adaptive stochastic cellular automata: Applications
NASA Astrophysics Data System (ADS)
Qian, S.; Lee, Y. C.; Jones, R. D.; Barnes, C. W.; Flake, G. W.; O'Rourke, M. K.; Lee, K.; Chen, H. H.; Sun, G. Z.; Zhang, Y. Q.; Chen, D.; Giles, C. L.
1990-09-01
The stochastic learning cellular automata model has been applied to the problem of controlling unstable systems. Two example unstable systems studied are controlled by an adaptive stochastic cellular automata algorithm with an adaptive critic. The reinforcement learning algorithm and the architecture of the stochastic CA controller are presented. Learning to balance a single pole is discussed in detail. Balancing an inverted double pendulum highlights the power of the stochastic CA approach. The stochastic CA model is compared to conventional adaptive control and artificial neural network approaches.
Solving initial and boundary value problems using learning automata particle swarm optimization
NASA Astrophysics Data System (ADS)
Nemati, Kourosh; Mariyam Shamsuddin, Siti; Darus, Maslina
2015-05-01
In this article, the particle swarm optimization (PSO) algorithm is modified to use the learning automata (LA) technique for solving initial and boundary value problems. A constrained problem is converted into an unconstrained problem using a penalty method to define an appropriate fitness function, which is optimized using the LA-PSO method. This method analyses a large number of candidate solutions of the unconstrained problem with the LA-PSO algorithm to minimize an error measure, which quantifies how well a candidate solution satisfies the governing ordinary differential equations (ODEs) or partial differential equations (PDEs) and the boundary conditions. This approach is very capable of solving linear and nonlinear ODEs, systems of ordinary differential equations, and linear and nonlinear PDEs. The computational efficiency and accuracy of the PSO algorithm combined with the LA technique for solving initial and boundary value problems were improved. Numerical results demonstrate the high accuracy and efficiency of the proposed method.
Distributed learning automata-based algorithm for community detection in complex networks
NASA Astrophysics Data System (ADS)
Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza
2016-03-01
Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.
Learning to construct pushdown automata for accepting deterministic context-free languages
NASA Astrophysics Data System (ADS)
Sen, Sandip; Janakiraman, Janani
1992-03-01
Genetic algorithms (GAs) are a class of probabilistic optimization algorithms which utilize ideas from natural genetics. In this paper, we apply the genetic algorithm to a difficult machine learning problem, viz., to learn the description of pushdown automata (PDA) to accept a context-free language (CFL), given legal and illegal sentences of the language. Previous work has involved the use of GAs in learning descriptions for finite state machines for accepting regular languages. CFLs are known to properly include regular languages, and hence, the learning problem addressed here is of a greater complexity. The ability to accept context free languages can be applied to a number of practical problems like text processing, speech recognition, etc.
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.
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 Multi-Teacher Learning Automata Computing Model for Graph Partitioning Problems
NASA Astrophysics Data System (ADS)
Ikebo, Shigeya; Qian, Fei; Hirata, Hironori
Graph partitioning is an important problem that has extensive applications in many areas, including VLSI design, scientific computing, data mining, geographical information systems and job scheduling. The graph partitioning problem (GPP) is NP-complete. There are several heuristic algorithms developed finding a reasonably good resolution. The most famous partitioning methods are simulated annealing (SA) and mean field algorithm (MFA) known to produce good partition for a wide class of problems, and they are used quite extensively. However these methods are very expensive in time and very sensitive in parameters tuning methods. In this paper, a new parameter-free algorithm for GPP has been proposed. The algorithm has been constructed using the S-model learning automata with multi-teacher random environments. As shown in our experiments, the proposed algorithm has some advantages superior to SA, MFA and ParMeTiS.
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.
NASA Astrophysics Data System (ADS)
Afshar, M. H.; Rohani, M.
2012-01-01
In this article, cellular automata based hybrid methods are proposed for the optimal design of sewer networks and their performance is compared with some of the common heuristic search methods. The problem of optimal design of sewer networks is first decomposed into two sub-optimization problems which are solved iteratively in a two stage manner. In the first stage, the pipe diameters of the network are assumed fixed and the nodal cover depths of the network are determined by solving a nonlinear sub-optimization problem. A cellular automata (CA) method is used for the solution of the optimization problem with the network nodes considered as the cells and their cover depths as the cell states. In the second stage, the nodal cover depths calculated from the first stage are fixed and the pipe diameters are calculated by solving a second nonlinear sub-optimization problem. Once again a CA method is used to solve the optimization problem of the second stage with the pipes considered as the CA cells and their corresponding diameters as the cell states. Two different updating rules are derived and used for the CA of the second stage depending on the treatment of the pipe diameters. In the continuous approach, the pipe diameters are considered as continuous variables and the corresponding updating rule is derived mathematically from the original objective function of the problem. In the discrete approach, however, an adhoc updating rule is derived and used taking into account the discrete nature of the pipe diameters. The proposed methods are used to optimally solve two sewer network problems and the results are presented and compared with those obtained by other methods. The results show that the proposed CA based hybrid methods are more efficient and effective than the most powerful search methods considered in this work.
NASA Technical Reports Server (NTRS)
Havelund, Klaus
2014-01-01
We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.
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.
Finite state automata resulting from temporal information maximization and a temporal learning rule.
Wennekers, Thomas; Ay, Nihat
2005-10-01
We extend Linkser's Infomax principle for feedforward neural networks to a measure for stochastic interdependence that captures spatial and temporal signal properties in recurrent systems. This measure, stochastic interaction, quantifies the Kullback-Leibler divergence of a Markov chain from a product of split chains for the single unit processes. For unconstrained Markov chains, the maximization of stochastic interaction, also called Temporal Infomax, has been previously shown to result in almost deterministic dynamics. This letter considers Temporal Infomax on constrained Markov chains, where some of the units are clamped to prescribed stochastic processes providing input to the system. Temporal Infomax in that case leads to finite state automata, either completely deterministic or weakly nondeterministic. Transitions between internal states of these systems are almost perfectly predictable given the complete current state and the input, but the activity of each single unit alone is virtually random. The results are demonstrated by means of computer simulations and confirmed analytically. It is furthermore shown numerically that Temporal Infomax leads to a high information flow from the input to internal units and that a simple temporal learning rule can approximately achieve the optimization of temporal interaction. We relate these results to experimental data concerning the correlation dynamics and functional connectivities observed in multiple electrode recordings. PMID:16105225
Baba, Norio; Mogami, Yoshio
2006-08-01
A new learning algorithm for the hierarchical structure learning automata (HSLA) operating in the nonstationary multiteacher environment (NME) is proposed. The proposed algorithm is derived by extending the original relative reward-strength algorithm to be utilized in the HSLA operating in the general NME. It is shown that the proposed algorithm ensures convergence with probability 1 to the optimal path under a certain type of the NME. Several computer-simulation results, which have been carried out in order to compare the relative performance of the proposed algorithm in some NMEs against those of the two of the fastest algorithms today, confirm the effectiveness of the proposed algorithm. PMID:16903364
Modelling approaches for coastal simulation based on cellular automata: the need and potential.
Dearing, J A; Richmond, N; Plater, A J; Wolf, J; Prandle, D; Coulthard, T J
2006-04-15
The paper summarizes the theoretical and practical needs for cellular automata (CA)-type models in coastal simulation, and describes early steps in the development of a CA-based model for estuarine sedimentation. It describes the key approaches and formulae used for tidal, wave and sediment processes in a prototype integrated cellular model for coastal simulation designed to simulate estuary sedimentary responses during the tidal cycle in the short-term and climate driven changes in sea-level in the long-term. Results of simple model testing for both one-dimensional and two-dimensional models, and a preliminary parameterization for the Blackwater Estuary, UK, are shown. These reveal a good degree of success in using a CA-type model for water and sediment transport as a function of water level and wave height, but tidal current vectors are not effectively simulated in the approach used. The research confirms that a CA-type model for the estuarine sediment system is feasible, with a real prospect for coupling to existing catchment and nearshore beach/cliff models to produce integrated coastal simulators of sediment response to climate, sea-level change and human actions. PMID:16537155
Setny, Piotr; Zacharias, Martin
2010-07-01
A simple, semiheuristic solvation model based on a discrete, BCC grid of solvent cells has been presented. The model utilizes a mean field approach for the calculation of solute-solvent and solvent-solvent interaction energies and a cellular automata based algorithm for the prediction of solvent distribution in the presence of solute. The construction of the effective Hamiltonian for a solvent cell provides an explicit coupling between orientation-dependent water-solute electrostatic interactions and water-water hydrogen bonding. The water-solute dispersion interaction is also explicitly taken into account. The model does not depend on any arbitrary definition of the solute-solvent interface nor does it use a microscopic surface tension for the calculation of nonpolar contributions to the hydration free energies. It is demonstrated that the model provides satisfactory predictions of hydration free energies for drug-like molecules and is able to reproduce the distribution of buried water molecules within protein structures. The model is computationally efficient and is applicable to arbitrary molecules described by atomistic force field. PMID:20552986
Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment
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
Gutowitz, H.A.
1988-11-17
In this lecture the map from a cellular automaton to a sequence of analytical approximations called the local structure theory is described. Connections are drawn between cellular automata and neural network models. It is suggested that the process by which a cellular automaton holds particular probability measures invariant is an appropriate model for biological memory. 20 figs.
Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach
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
Learning deterministic finite automata with a smart state labeling evolutionary algorithm.
Lucas, Simon M; Reynolds, T Jeff
2005-07-01
Learning a Deterministic Finite Automaton (DFA) from a training set of labeled strings is a hard task that has been much studied within the machine learning community. It is equivalent to learning a regular language by example and has applications in language modeling. In this paper, we describe a novel evolutionary method for learning DFA that evolves only the transition matrix and uses a simple deterministic procedure to optimally assign state labels. We compare its performance with the Evidence Driven State Merging (EDSM) algorithm, one of the most powerful known DFA learning algorithms. We present results on random DFA induction problems of varying target size and training set density. We also studythe effects of noisy training data on the evolutionary approach and on EDSM. On noise-free data, we find that our evolutionary method outperforms EDSM on small sparse data sets. In the case of noisy training data, we find that our evolutionary method consistently outperforms EDSM, as well as other significant methods submitted to two recent competitions. PMID:16013754
Modelling the role of nucleation on recrystallization kinetics: A cellular automata approach
NASA Astrophysics Data System (ADS)
Tripathy, Haraprasanna; Rai, Arun Kumar; Hajra, Raj Narayan; Raju, Subramanian; Saibaba, Saroja
2016-05-01
In present study, a two dimensional cellular automata (CA) simulation has been carried out to study the effect of nucleation mode on the kinetics of recrystallization and microstructure evolution in an austenitic stainless steel. Two different nucleation modes i.e. site saturation and continuous nucleation with interface control growth mechanism has been considered in this modified CA algorithm. The observed Avrami exponent for both nucleation modes shows a better agreement with the theoretical predicted values. The site saturated nucleation mode shows a nearly consistent value of Avrami exponent, whereas in the case of continuous nucleation the exponent shows a little variation during transformation. The simulations in the present work can be applied for the optimization of microstructure and properties in austenitic steels.
NASA Astrophysics Data System (ADS)
Alonso-Sanz, Ramón; Adamatzky, Andy
Actin is a globular protein which forms long polar filaments in eukaryotic. The actin filaments play the roles of cytoskeleton, motility units, information processing and learning. We model actin filament as a double chain of finite state machines, nodes, which take states “0” and “1”. The states are abstractions of absence and presence of a subthreshold charge on actin units corresponding to the nodes. All nodes update their state in parallel to discrete time. A node updates its current state depending on states of two closest neighbors in the node chain and two closest neighbors in the complementary chain. Previous models of actin automata consider momentary state transitions of nodes. We enrich the actin automata model by assuming that states of nodes depend not only on the current states of neighboring node but also on their past states. Thus, we assess the effect of memory of past states on the dynamics of acting automata. We demonstrate in computational experiments that memory slows down propagation of perturbations, decrease entropy of space-time patterns generated, transforms traveling localizations to stationary oscillators, and stationary oscillations to still patterns.
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.
Modeling the “learning process” of the teacher in a tutorial-like system using learning automata.
Oommen, B John; Hashem, M Khaled
2013-12-01
Unlike the field of tutorial systems, where a real-life student interacts and learns from a software system, our research focuses on a new philosophy in which no entity needs to be a real-life individual. Such systems are termed as tutorial-like systems, and research in this field endeavors to model every component of the system using an appropriate learning model [in our case, a learning automaton (LA)].1 While models for the student, the domain, the teacher, etc., have been presented elsewhere, the aim of this paper is to present a new approach to model how the teacher, in this paradigm, of our tutorial-like system "learns and improves his "teaching skills" while being himself an integral component of the system. We propose to model the "learning process" of the teacher by using a higher level LA, referred to as the metateacher, whose task is to assist the teacher himself. Ultimately, the intention is that the latter can communicate the teaching material to the student(s) in a manner customized to the particular student's ability and progress. In short, the teacher will infer the progress of the student and initiate a strategy by which he can "custom-communicate" the material to each individual student. The results that we present in a simulated environment validate the model for the teacher and for the metateacher. The use of the latter can be seen to significantly improve the teaching abilities of the teacher. PMID:23757589
Mitochondrial fusion through membrane automata.
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. PMID:25417022
NASA Technical Reports Server (NTRS)
Hinchey, Michael G. (Inventor); Margaria, Tiziana (Inventor); Rash, James L. (Inventor); Rouff, Christopher A. (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.
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.
Two-lane traffic rules for cellular automata: A systematic approach
Nagel, K. |; Wolf, D.E. |; Wagner, P. |; Simon, P.
1997-11-05
Microscopic modeling of multi-lane traffic is usually done by applying heuristic lane changing rules, and often with unsatisfying results. Recently, a cellular automation model for two-lane traffic was able to overcome some of these problems and to produce a correct density inversion at densities somewhat below the maximum flow density. In this paper, the authors summarize different approaches to lane changing and their results, and propose a general scheme, according to which realistic lane changing rules can be developed. They test this scheme by applying it to several different lane changing rules, which, in spite of their differences, generate similar and realistic results. The authors thus conclude that, for producing realistic results, the logical structure of the lane changing rules, as proposed here, is at least as important as the microscopic details of the rules.
A multi-layer cellular automata approach for algorithmic generation of virtual case studies: VIBe.
Sitzenfrei, R; Fach, S; Kinzel, H; Rauch, W
2010-01-01
Analyses of case studies are used to evaluate new or existing technologies, measures or strategies with regard to their impact on the overall process. However, data availability is limited and hence, new technologies, measures or strategies can only be tested on a limited number of case studies. Owing to the specific boundary conditions and system properties of each single case study, results can hardly be generalized or transferred to other boundary conditions. virtual infrastructure benchmarking (VIBe) is a software tool which algorithmically generates virtual case studies (VCSs) for urban water systems. System descriptions needed for evaluation are extracted from VIBe whose parameters are based on real world case studies and literature. As a result VIBe writes Input files for water simulation software as EPANET and EPA SWMM. With such input files numerous simulations can be performed and the results can be benchmarked and analysed stochastically at a city scale. In this work the approach of VIBe is applied with parameters according to a section of the Inn valley and therewith 1,000 VCSs are generated and evaluated. A comparison of the VCSs with data of real world case studies shows that the real world case studies fit within the parameter ranges of the VCSs. Consequently, VIBe tackles the problem of limited availability of case study data. PMID:20057089
Infrared image enhancement using Cellular Automata
NASA Astrophysics Data System (ADS)
Qi, Wei; Han, Jing; Zhang, Yi; Bai, Lian-fa
2016-05-01
Image enhancement is a crucial technique for infrared images. The clear image details are important for improving the quality of infrared images in computer vision. In this paper, we propose a new enhancement method based on two priors via Cellular Automata. First, we directly learn the gradient distribution prior from the images via Cellular Automata. Second, considering the importance of image details, we propose a new gradient distribution error to encode the structure information via Cellular Automata. Finally, an iterative method is applied to remap the original image based on two priors, further improving the quality of enhanced image. Our method is simple in implementation, easy to understand, extensible to accommodate other vision tasks, and produces more accurate results. Experiments show that the proposed method performs better than other methods using qualitative and quantitative measures.
Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study.
Tîrnăucă, Cristina; Montaña, José L; Ontañón, Santiago; González, Avelino J; Pardo, Luis M
2016-01-01
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. PMID:27347956
Statistical Mechanics of Surjective Cellular Automata
NASA Astrophysics Data System (ADS)
Kari, Jarkko; Taati, Siamak
2015-09-01
Reversible cellular automata are seen as microscopic physical models, and their states of macroscopic equilibrium are described using invariant probability measures. We establish a connection between the invariance of Gibbs measures and the conservation of additive quantities in surjective cellular automata. Namely, we show that the simplex of shift-invariant Gibbs measures associated to a Hamiltonian is invariant under a surjective cellular automaton if and only if the cellular automaton conserves the Hamiltonian. A special case is the (well-known) invariance of the uniform Bernoulli measure under surjective cellular automata, which corresponds to the conservation of the trivial Hamiltonian. As an application, we obtain results indicating the lack of (non-trivial) Gibbs or Markov invariant measures for "sufficiently chaotic" cellular automata. We discuss the relevance of the randomization property of algebraic cellular automata to the problem of approach to macroscopic equilibrium, and pose several open questions. As an aside, a shift-invariant pre-image of a Gibbs measure under a pre-injective factor map between shifts of finite type turns out to be always a Gibbs measure. We provide a sufficient condition under which the image of a Gibbs measure under a pre-injective factor map is not a Gibbs measure. We point out a potential application of pre-injective factor maps as a tool in the study of phase transitions in statistical mechanical models.
Cellular-automata method for phase unwrapping
Ghiglia, D.C.; Mastin, G.A.; Romero, L.A.
1987-01-01
Research into two-dimensional phase unwrapping has uncovered interesting and troublesome inconsistencies that cause path-dependent results. Cellular automata, which are simple, discrete mathematical systems, offered promise of computation in nondirectional, parallel manner. A cellular automaton was discovered that can unwrap consistent phase data in n dimensions in a path-independent manner and can automatically accommodate noise-induced (pointlike) inconsistencies and arbitrary boundary conditions (region partitioning). For data with regional (nonpointlike) inconsistencies, no phase-unwrapping algorithm will converge, including the cellular-automata approach. However, the automata method permits more simple visualization of the regional inconsistencies. Examples of its behavior on one- and two-dimensional data are presented.
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.
Fuzzy tree automata and syntactic pattern recognition.
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. PMID:21869062
Probabilistic cellular automata.
Agapie, Alexandru; Andreica, Anca; Giuclea, Marius
2014-09-01
Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557
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.
Approach to learning disability.
Kulkarni, M; Kalantre, S; Upadhye, S; Karande, S; Ahuja, S
2001-06-01
Learning disabilities (LD) is one of the important causes of poor academic performance in school going children. Learning disabilities are developmental disorders that usually manifest during the period of normal education. These disabilities create a significant gap between the true potential and day to day performance of an individual. Dyslexia, dysgraphia and dyscalculia denote the problem related to reading, writing and mathematics. Perinatal problems are certain neurological conditions, known to be associated with LD; however, genetic predisposition seems to be the most probable etiological factors. Evaluation of a child suspected to be having LD consists of medical examination, vision and hearing test analysis of school performance. The psycho-behaviour assessment and education testing are essential in the process of diagnosis. The experienced persons in the field of LD should interpret the results of such tests. With Individualized Remedial Education Plan (IEP) most children learn to cope up with disability and may get integrated in a regular steam. PMID:11450386
Hybrid Approach to Reinforcement Learning
NASA Astrophysics Data System (ADS)
Boulebtateche, Brahim; Fezari, Mourad; Boughazi, Mohamed
2008-06-01
Reinforcement Learning (RL) is a general framework in which an autonomous agent tries to learn an optimal policy of actions from direct interaction with the surrounding environment (RL). However, one difficulty for the application of RL control is its slow convergence, especially in environments with continuous state space. In this paper, a modified structure of RL is proposed to speed up reinforcement learning control. In this approach, supervision technique is combined with the standard Q-learning, a model-free algorithm of reinforcement learning. The a priori information is provided to the RL by an optimal LQ-controller, used to indicate preferred actions at intermittent times. It is shown that the convergence speed of the supervised RL agent is greatly improved compared to the conventional Q-Learning algorithm. Simulation work and results on the cart-pole balancing problem are given to illustrate the efficiency of the proposed method.
Game level layout generation using evolved cellular automata
NASA Astrophysics Data System (ADS)
Pech, Andrew; Masek, Martin; Lam, Chiou-Peng; Hingston, Philip
2016-01-01
Design of level layouts typically involves the production of a set of levels which are different, yet display a consistent style based on the purpose of a particular level. In this paper, a new approach to the generation of unique level layouts, based on a target set of attributes, is presented. These attributes, which are learned automatically from an example layout, are used for the off-line evolution of a set of cellular automata rules. These rules can then be used for the real-time generation of level layouts that meet the target parameters. The approach is demonstrated on a set of maze-like level layouts. Results are presented to show the effect of various CA parameters and rule representation.
Predictability in cellular automata.
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
The Wonder Approach to learning.
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
The Wonder Approach to learning
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
NASA Astrophysics Data System (ADS)
Bagnoli, Franco; Rechtman, Raúl; El Yacoubi, Samira
2012-12-01
We study the problem of master-slave synchronization and control of totalistic cellular automata. The synchronization mechanism is that of setting a fraction of sites of the slave system equal to those of the master one (pinching synchronization). The synchronization observable is the distance between the two configurations. We present three control strategies that exploit local information (the number of nonzero first-order Boolean derivatives) in order to choose the sites to be synchronized. When no local information is used, we speak of simple pinching synchronization. We find the critical properties of control and discuss the best control strategy compared with simple synchronization.
Clemente-Juan, Juan Modesto; Palii, Andrew; Coronado, Eugenio; Tsukerblat, Boris
2016-08-01
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
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.
Weighted Watson-Crick automata
Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku
2014-07-10
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.
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…
Global properties of cellular automata
Jen, E.
1986-04-01
Cellular automata are discrete mathematical systems that generate diverse, often complicated, behavior using simple deterministic rules. Analysis of the local structure of these rules makes possible a description of the global properties of the associated automata. A class of cellular automata that generate infinitely many aperoidic temporal sequences is defined,a s is the set of rules for which inverses exist. Necessary and sufficient conditions are derived characterizing the classes of ''nearest-neighbor'' rules for which arbitrary finite initial conditions (i) evolve to a homogeneous state; (ii) generate at least one constant temporal sequence.
Modeling biological pathway dynamics with timed automata.
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. PMID:24808226
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.
Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study †
Tîrnăucă, Cristina; Montaña, José L.; Ontañón, Santiago; González, Avelino J.; Pardo, Luis M.
2016-01-01
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. PMID:27347956
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.
Conceptions of Learning and Approaches to Learning in Portuguese Students
ERIC Educational Resources Information Center
Duarte, Antonio M.
2007-01-01
The article describes a study that attempted to characterise Portuguese students' conceptions of learning and approaches to learning. A sample of university students answered open questions on the meaning, process and context of learning. Results, derived from content analysis, replicate most conceptions of learning described by phenomenographical…
Design and Evaluation of Two Blended Learning Approaches: Lessons Learned
ERIC Educational Resources Information Center
Cheung, Wing Sum; Hew, Khe Foon
2011-01-01
In this paper, we share two blended learning approaches used at the National Institute of Education in Singapore. We have been using these two approaches in the last twelve years in many courses ranging from the diploma to graduate programs. For the first blended learning approach, we integrated one asynchronous communication tool with face to…
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.
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"…
E-Learning Approach in Teacher Training
ERIC Educational Resources Information Center
Yucel, Seda A.
2006-01-01
There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational…
Quantum cellular automata without particles
NASA Astrophysics Data System (ADS)
Meyer, David A.; Shakeel, Asif
2016-01-01
Quantum cellular automata (QCA) constitute space and time homogeneous discrete models for quantum field theories (QFTs). Although QFTs are defined without reference to particles, computations are done in terms of Feynman diagrams, which are explicitly interpreted in terms of interacting particles. Similarly, the easiest QCA to construct are quantum lattice gas automata (QLGA). A natural question then is, which QCA are not QLGA? Here we construct a nontrivial example of such a QCA; it provides a simple model in 1 +1 dimensions with no particle interpretation at the scale where the QCA dynamics are homogeneous.
NASA Astrophysics Data System (ADS)
Mendicino, Giuseppe; Pedace, Jessica; Senatore, Alfonso
2015-04-01
Cellular Automata are often used for modeling the evolution in time of environmental systems mainly because they are directly compatible with parallel programming. Nevertheless, defining the optimal time step criterion for integrating forward in time numerical processes can further enhance model computational efficiency. To this aim, a numerical stability analysis of an original overland flow model, within the framework of a fully coupled eco-hydrological system based on the Macroscopic Cellular Automata paradigm, is performed. According to the other modules of the system describing soil water flow, soil-surface-atmosphere fluxes and vegetation dynamics, overland flow model equations were derived through a direct discrete formulation (i.e. no differential equations were discretized), adopting the diffusion wave model as an approximation of the full De Saint Venant equations and including the capability of accounting for specific processes, such as the increasing roughness effects due to vegetation growth or surface-soil water exchanges. Suitable formulations of robust tools usually applied in the stability analyses, such as Courant-Friedrichs-Lewy and von Neumann conditions, were initially derived for the CA-based overland flow model. Afterwards, the theoretical stability conditions were compared to experimental time step constraints through several numerical simulations of a 5-h rain event. Specifically, adopting a constant (i.e. not adaptive) time step for simulations, and discretizing head losses in a way that increases model stability, experimental upper limits preventing numerical instability were found for 13 test cases with different slopes, precipitation intensities, vegetation densities and depths of surface depressions. Even though von Neumann condition and experimental values were well positively correlated, the latter were almost always sensibly lower, excluding cases when free surface gradients tended to zero. Therefore, based on the original method
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…
Probabilistic arithmetic automata and their applications.
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. PMID:22868683
Astrobiological complexity with probabilistic cellular automata.
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. PMID:22832998
Astrobiological Complexity with Probabilistic Cellular Automata
NASA Astrophysics Data System (ADS)
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.
Accelerated learning approaches for maintenance training
Erickson, E.J.
1991-01-01
As a training tool, Accelerated Learning techniques have been in use since 1956. Trainers from a variety of applications and disciplines have found success in using Accelerated Learning approaches, such as training aids, positive affirmations, memory aids, room arrangement, color patterns, and music. Some have thought that maintenance training and Accelerated Learning have nothing in common. Recent training applications by industry and education of Accelerated Learning are proving very successful by several standards. This paper cites available resource examples and challenges maintenance trainers to adopt new ideas and concepts to accelerate learning in all training setting. 7 refs.
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…
Aperiodicity in one-dimensional cellular automata
Jen, E.
1990-01-01
Cellular automata are a class of mathematical systems characterized by discreteness (in space, time, and state values), determinism, and local interaction. A certain class of one-dimensional, binary site-valued, nearest-neighbor automata is shown to generate infinitely many aperiodic temporal sequences from arbitrary finite initial conditions on an infinite lattice. The class of automaton rules that generate aperiodic temporal sequences are characterized by a particular form of injectivity in their interaction rules. Included are the nontrivial linear'' automaton rules (that is, rules for which the superposition principle holds); certain nonlinear automata that retain injectivity properties similar to those of linear automata; and a wider subset of nonlinear automata whose interaction rules satisfy a weaker form of injectivity together with certain symmetry conditions. A technique is outlined here that maps this last set of automata onto a linear automaton, and thereby establishes the aperiodicity of their temporal sequences. 12 refs., 3 figs.
Approaches to Learning in the Workplace
ERIC Educational Resources Information Center
Geertshuis, Susan A.; Fazey, John A.
2006-01-01
Purpose: The aim of this study is to explore approaches to learning in the workplace. Design/methodology/approach: Computer based questionnaires are used with a sample of over 300 employees. Findings: Using a version of the Revised Approaches to Study Inventory (RASI) adapted to workforce development, the factor structure of deep, surface and…
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)
Xtoys: Cellular automata on xwindows
Creutz, M.
1995-08-15
Xtoys is a collection of xwindow programs for demonstrating simulations of various statistical models. Included are xising, for the two dimensional Ising model, xpotts, for the q-state Potts model, xautomalab, for a fairly general class of totalistic cellular automata, xsand, for the Bak-Tang-Wiesenfield model of self organized criticality, and xfires, a simple forest fire simulation. The programs should compile on any machine supporting xwindows.
An approach to elemental task learning
Belmans, P
1990-01-01
In this article we deal with the automated learning of tasks by a robotic system through observation of a human operator. Particularly, we explain what is meant by a learning ability in autonomous robots and in teleoperation systems, where several operators and several machines may work in cooperation to perform tasks. We discuss different approaches to learning in these systems and outline the features of the models they are based upon. This leads us to choose an analytical model suited for tasks analysis. We then present the software architecture for our proposed approach and show the first results obtained on sample tests. 5 refs., 9 figs.
A Cognitive Approach to e-Learning
Greitzer, Frank L.; Rice, Douglas M.; Eaton, Sharon L.; Perkins, Michael C.; Scott, Ryan T.; Burnette, John R.; Robertson, Sarah R.
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. The 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 computer
Concept Learning for Achieving Personalized Ontologies: An Active Learning Approach
NASA Astrophysics Data System (ADS)
Şensoy, Murat; Yolum, Pinar
In many multiagent approaches, it is usual to assume the existence of a common ontology among agents. However, in dynamic systems, the existence of such an ontology is unrealistic and its maintenance is cumbersome. Burden of maintaining a common ontology can be alleviated by enabling agents to evolve their ontologies personally. However, with different ontologies, agents are likely to run into communication problems since their vocabularies are different from each other. Therefore, to achieve personalized ontologies, agents must have a means to understand the concepts used by others. Consequently, this paper proposes an approach that enables agents to teach each other concepts from their ontologies using examples. Unlike other concept learning approaches, our approach enables the learner to elicit most informative examples interactively from the teacher. Hence, the learner participates to the learning process actively. We empirically compare the proposed approach with the previous concept learning approaches. Our experiments show that using the proposed approach, agents can learn new concepts successfully and with fewer examples.
Personality, Approaches to Learning and Achievement
ERIC Educational Resources Information Center
Swanberg, Anne Berit; Martinsen, Oyvind Lund
2010-01-01
The present study investigated the relationships between the five-factor model of personality, approaches to learning and academic achievement. Based on the previous research, we expected approaches to have a mediating effect between personality and academic achievement. Six hundred and eighty-seven business students participated in a survey; 56%…
Heutagogy: An alternative practice based learning approach.
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. PMID:20554249
Generalized information-lossless automata. I
Speranskii, D.V.
1995-01-01
Huffman and Even introduced classes of abstract automata, which they called respectively information-lossless automata (ILL) and information-lossless automata of finite order (ILLFO). The underlying property of these automata is the ability to reconstruct unknown input sequences from observations of the output response, assuming that the true initial state of the automaton is known. Similar classes of automata introduced in are called essentially information-lossless automata, and they are capable of reconstructing the unknown input word without knowledge of the initial state of the automaton. It is only assumed that the set of possible initial states of the automaton is the set of all automaton states. In this paper we analyze a structural analog of an abstract ILL-automaton whose set of initial states may be of arbitrary cardinality. This class of automata is thus a generalization of the classical ILL-automata, which allows not only for the structure of the input and output alphabets, but also for the configuration of the set of possible initial states.
Understanding Observational Learning: An Interbehavioral Approach
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
On the secure obfuscation of deterministic finite automata.
Anderson, William Erik
2008-06-01
In this paper, we show how to construct secure obfuscation for Deterministic Finite Automata, assuming non-uniformly strong one-way functions exist. We revisit the software protection approaches originally proposed by [5, 10, 12, 17] and revise them to the current obfuscation setting of Barak et al. [2]. Under this model, we introduce an efficient oracle that retains some 'small' secret about the original program. Using this secret, we can construct an obfuscator and two-party protocol that securely obfuscates Deterministic Finite Automata against malicious adversaries. The security of this model retains the strong 'virtual black box' property originally proposed in [2] while incorporating the stronger condition of dependent auxiliary inputs in [15]. Additionally, we show that our techniques remain secure under concurrent self-composition with adaptive inputs and that Turing machines are obfuscatable under this model.
Extended Self Organised Criticality in Asynchronously Tuned Cellular Automata
NASA Astrophysics Data System (ADS)
Gunji, Yukio-Pegio
2014-12-01
Systems at a critical point in phase transitions can be regarded as being relevant to biological complex behaviour. Such a perspective can only result, in a mathematical consistent manner, from a recursive structure. We implement a recursive structure based on updating by asynchronously tuned elementary cellular automata (AT ECA), and show that a large class of elementary cellular automata (ECA) can reveal critical behavior due to the asynchronous updating and tuning.We show that the obtained criticality coincides with the criticality in phase transitions of asynchronous ECA with respect to density decay, and that multiple distributed ECAs, synchronously updated, can emulate critical behavior in AT ECA. Our approach draws on concepts and tools from category and set theory, in particular on "adjunction dualities" of pairs of adjoint functors.
Relational String Verification Using Multi-track Automata
NASA Astrophysics Data System (ADS)
Yu, Fang; Bultan, Tevfik; Ibarra, Oscar H.
Verification of string manipulation operations is a crucial problem in computer security. In this paper, we present a new relational string verification technique based on multi-track automata. Our approach is capable of verifying properties that depend on relations among string variables. This enables us to prove that vulnerabilities that result from improper string manipulation do not exist in a given program. Our main contributions in this paper can be summarized as follows: (1) We formally characterize the string verification problem as the reachability analysis of string systems and show decidability/undecidability results for several string analysis problems. (2) We develop a sound symbolic analysis technique for string verification that over-approximates the reachable states of a given string system using multi-track automata and summarization. (3) We evaluate the presented techniques with respect to several string analysis benchmarks extracted from real web applications.
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.
Symmetry analysis of cellular automata
NASA Astrophysics Data System (ADS)
García-Morales, V.
2013-01-01
By means of B-calculus [V. García-Morales, Phys. Lett. A 376 (2012) 2645] a universal map for deterministic cellular automata (CAs) has been derived. The latter is shown here to be invariant upon certain transformations (global complementation, reflection and shift). When constructing CA rules in terms of rules of lower range a new symmetry, “invariance under construction” is uncovered. Modular arithmetic is also reformulated within B-calculus and a new symmetry of certain totalistic CA rules, which calculate the Pascal simplices modulo an integer number p, is then also uncovered.
Stochastic computing with biomolecular automata
NASA Astrophysics Data System (ADS)
Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud
2004-07-01
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.
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 approach"…
Transformative Learning Approaches for Public Relations Pedagogy
ERIC Educational Resources Information Center
Motion, Judy; Burgess, Lois
2014-01-01
Public relations educators are frequently challenged by students' flawed perceptions of public relations. Two contrasting case studies are presented in this paper to illustrate how socially-oriented paradigms may be applied to a real-client project to deliver a transformative learning experience. A discourse-analytic approach is applied…
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…
A Mixed Learning Approach in Mechatronics Education
ERIC Educational Resources Information Center
Yilmaz, O.; Tuncalp, K.
2011-01-01
This study aims to investigate the effect of a Web-based mixed learning approach model on mechatronics education. The model combines different perception methods such as reading, listening, and speaking and practice methods developed in accordance with the vocational background of students enrolled in the course Electromechanical Systems in…
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…
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.
Rasmussen, S. |; Smith, J.R. |
1995-05-01
We present a new style of molecular dynamics and self-assembly simulation, the Lattice Polymer Automaton (LPA). In the LPA all interactions, including electromagnetic forces, are decomposed and communicated via propagating particles, {open_quotes}photons.{close_quotes} The monomer-monomer bondforces, the molecular excluded volume forces, the longer range intermolecular forces, and the polymer-solvent interactions may all be modeled with propagating particles. The LPA approach differs significantly from both of the standard approaches, Monte Carlo lattice methods and Molecular Dynamics simulations. On the one hand, the LPA provides more realism than Monte Carlo methods, because it produces a time series of configurations of a single molecule, rather than a set of causally unrelated samples from a distribution of configurations. The LPA can therefore be used directly to study dynamical properties; one can in fact watch polymers move in real time. On the other hand, the LPA is fully discrete, and therefore much simpler than traditional Molecular Dynamics models, which are continuous and operate on much shorter time scales. Due to this simplicity it is possible to simulate longer real time periods, which should enable the study of molecular self-organization on workstations supercomputers are not needed.
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.
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…
Quantum features of natural cellular automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2016-03-01
Cellular automata can show well known features of quantum mechanics, such as a linear rule according to which they evolve and which resembles a discretized version of the Schrödinger equation. This includes corresponding conservation laws. The class of “natural” Hamiltonian cellular automata is based exclusively on integer-valued variables and couplings and their dynamics derives from an Action Principle. They can be mapped reversibly to continuum models by applying Sampling Theory. Thus, “deformed” quantum mechanical models with a finite discreteness scale l are obtained, which for l → 0 reproduce familiar continuum results. We have recently demonstrated that such automata can form “multipartite” systems consistently with the tensor product structures of nonrelativistic many-body quantum mechanics, while interacting and maintaining the linear evolution. Consequently, the Superposition Principle fully applies for such primitive discrete deterministic automata and their composites and can produce the essential quantum effects of interference and entanglement.
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)
Cellular automata to describe seismicity: A review
NASA Astrophysics Data System (ADS)
Jiménez, Abigail
2013-12-01
Cellular Automata have been used in the literature to describe seismicity. We first historically introduce Cellular Automata and provide some important definitions. Then we proceed to review the most important models, most of them being variations of the spring-block model proposed by Burridge and Knopoff, and describe the most important results obtained from them. We discuss the relation with criticality and also describe some models that try to reproduce real data.
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…
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…
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.
Distinguishing Asthma Phenotypes Using Machine Learning Approaches.
Howard, Rebecca; Rattray, Magnus; Prosperi, Mattia; Custovic, Adnan
2015-07-01
Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as 'asthma endotypes'. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies. PMID:26143394
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.
Generic framework for mining cellular automata models on protein-folding simulations.
Diaz, N; Tischer, I
2016-01-01
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. PMID:27323045
Modeling Pseudorandom Sequence Generators using Cellular Automata: The Alternating Step Generator
NASA Astrophysics Data System (ADS)
Pazo-Robles, María Eugenia; Fúster-Sabater, Amparo
2007-12-01
Stream ciphers are pseudorandom bit generators whose output sequences are combined with the sensitive information by means of a mathematical function currently an addition module 2. The Alternating Step Generator is a pseudorandom sequence generator with good cryptographic properties and non-linear structure. In this work, we propose two different ways to model such a generator by using linear and discrete mathematical functions e.g. Cellular Automata. One of these ways deals with the realization of a linear model from a pair of basic automata provided by the Catell and Muzio algorithm. The other way is a new approach based on automata's addition consisting in the realization of a new automaton with non-primitive polynomial and short length. Both methods provide linear models able to generate the output sequence of the Alternating Step Generator.
Cellular automata modelling of biomolecular networks dynamics.
Bonchev, D; Thomas, S; Apte, A; Kier, L B
2010-01-01
The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215
ERIC Educational Resources Information Center
Ozkal, Kudret; Tekkaya, Ceren; Cakiroglu, Jale; Sungur, Semra
2009-01-01
This study proposed a conceptual model of relationships among constructivist learning environment perception variables (Personal Relevance, Uncertainty, Critical Voice, Shared Control, and Student Negotiation), scientific epistemological belief variables (fixed and tentative), and learning approach. It was proposed that learning environment…
Maximizing Exposure Therapy: An Inhibitory Learning Approach
Craske, Michelle G.; Treanor, Michael; Conway, Chris; Zbozinek, Tomislav; Vervliet, Bram
2014-01-01
Exposure therapy is an effective approach for treating anxiety disorders, although a substantial number of individuals fail to benefit or experience a return of fear after treatment. Research suggests that anxious individuals show deficits in the mechanisms believed to underlie exposure therapy, such as inhibitory learning. Targeting these processes may help improve the efficacy of exposure-based procedures. Although evidence supports an inhibitory learning model of extinction, there has been little discussion of how to implement this model in clinical practice. The primary aim of this paper is to provide examples to clinicians for how to apply this model to optimize exposure therapy with anxious clients, in ways that distinguish it from a ‘fear habituation’ approach and ‘belief disconfirmation’ approach within standard cognitive-behavior therapy. Exposure optimization strategies include 1) expectancy violation, 2) deepened extinction, 3) occasional reinforced extinction, 4) removal of safety signals, 5) variability, 6) retrieval cues, 7) multiple contexts, and 8) affect labeling. Case studies illustrate methods of applying these techniques with a variety of anxiety disorders, including obsessive-compulsive disorder, posttraumatic stress disorder, social phobia, specific phobia, and panic disorder. PMID:24864005
Lattice gas automata for flow and transport in geochemical systems
Janecky, D.R.; Chen, S.; Dawson, S.; Eggert, K.C.; Travis, B.J.
1992-01-01
Lattice gas automata models are described, which couple solute transport with chemical reactions at mineral surfaces within pore networks. Diffusion in a box calculations are illustrated, which compare directly with Fickian diffusion. Chemical reactions at solid surfaces, including precipitation/dissolution, sorption, and catalytic reaction, can be examined with the model because hydrodynamic transport, solute diffusion and mineral surface processes are all treated explicitly. The simplicity and flexibility of the approach provides the ability to study the interrelationship between fluid flow and chemical reactions in porous materials, at a level of complexity that has not previously been computationally possible.
Social learning in Models and Cases - an Interdisciplinary Approach
NASA Astrophysics Data System (ADS)
Buhl, Johannes; De Cian, Enrica; Carrara, Samuel; Monetti, Silvia; Berg, Holger
2016-04-01
Our paper follows an interdisciplinary understanding of social learning. We contribute to the literature on social learning in transition research by bridging case-oriented research and modelling-oriented transition research. We start by describing selected theories on social learning in innovation, diffusion and transition research. We present theoretical understandings of social learning in techno-economic and agent-based modelling. Then we elaborate on empirical research on social learning in transition case studies. We identify and synthetize key dimensions of social learning in transition case studies. In the following we bridge between more formal and generalising modelling approaches towards social learning processes and more descriptive, individualising case study approaches by interpreting the case study analysis into a visual guide on functional forms of social learning typically identified in the cases. We then try to exemplarily vary functional forms of social learning in integrated assessment models. We conclude by drawing the lessons learned from the interdisciplinary approach - methodologically and empirically.
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…
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…
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…
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…
Course Management Systems and Blended Learning: An Innovative Learning Approach
ERIC Educational Resources Information Center
Chou, Amy Y.; Chou, David C.
2011-01-01
This article utilizes Rogers' innovation-decision process model (2003) and Beckman and Berry's innovation process model (2007) to create an innovative learning map that illustrates three learning methods (i.e., face-to-face learning, online learning, and blended learning) in two types of innovation (i.e., incremental innovation and radical…
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…
The Learning Center Approach to Physical Education Instruction.
ERIC Educational Resources Information Center
Espiritu, Joyce K.; Loughrey, Thomas J.
1985-01-01
A learning center approach to physical education is recommended and presented. This approach can resolve the problem of large class sizes by freeing the teacher to work with individual students. Both psychomotor and cognitive learning experiences can be incorporated into learning centers. (MT)
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…
A Conceptual Analysis on the Approaches to Learning
ERIC Educational Resources Information Center
Ak, Serife
2008-01-01
The concept of approach to learning was first identified by Marton and Saljo in 1976. Numerous researchers have conducted studies on students' approaches to learning since 1976. There appears considerable confusion in the literature concerning the terms cognitive styles and learning styles. Therefore, there is a remarkable ambiguity about the…
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…
A Bayesian Approach to Learning Scoring Systems.
Ertekin, Şeyda; Rudin, Cynthia
2015-12-01
We present a Bayesian method for building scoring systems, which are linear models with coefficients that have very few significant digits. Usually the construction of scoring systems involve manual effort-humans invent the full scoring system without using data, or they choose how logistic regression coefficients should be scaled and rounded to produce a scoring system. These kinds of heuristics lead to suboptimal solutions. Our approach is different in that humans need only specify the prior over what the coefficients should look like, and the scoring system is learned from data. For this approach, we provide a Metropolis-Hastings sampler that tends to pull the coefficient values toward their "natural scale." Empirically, the proposed method achieves a high degree of interpretability of the models while maintaining competitive generalization performances. PMID:27441407
Computational approaches to motor learning by imitation.
Schaal, Stefan; Ijspeert, Auke; Billard, Aude
2003-01-01
Movement imitation requires a complex set of mechanisms that map an observed movement of a teacher onto one's own movement apparatus. Relevant problems include movement recognition, pose estimation, pose tracking, body correspondence, coordinate transformation from external to egocentric space, matching of observed against previously learned movement, resolution of redundant degrees-of-freedom that are unconstrained by the observation, suitable movement representations for imitation, modularization of motor control, etc. All of these topics by themselves are active research problems in computational and neurobiological sciences, such that their combination into a complete imitation system remains a daunting undertaking-indeed, one could argue that we need to understand the complete perception-action loop. As a strategy to untangle the complexity of imitation, this paper will examine imitation purely from a computational point of view, i.e. we will review statistical and mathematical approaches that have been suggested for tackling parts of the imitation problem, and discuss their merits, disadvantages and underlying principles. Given the focus on action recognition of other contributions in this special issue, this paper will primarily emphasize the motor side of imitation, assuming that a perceptual system has already identified important features of a demonstrated movement and created their corresponding spatial information. Based on the formalization of motor control in terms of control policies and their associated performance criteria, useful taxonomies of imitation learning can be generated that clarify different approaches and future research directions. PMID:12689379
Benchmark study between FIDAP and a cellular automata code
Akau, R.L.; Stockman, H.W.
1991-01-01
A fluid flow benchmark exercise was conducted to compare results between a cellular automata code and FIDAP. Cellular automata codes are free from gridding constraints, and are generally used to model slow (Reynolds number {approx} 1) flows around complex solid obstacles. However, the accuracy of cellular automata codes at higher Reynolds numbers, where inertial terms are significant, is not well-documented. In order to validate the cellular automata code, two fluids problems were investigated. For both problems, flow was assumed to be laminar, two-dimensional, isothermal, incompressible and periodic. Results showed that the cellular automata code simulated the overall behavior of the flow field. 7 refs., 12 figs.
Automata in random environments with application to machine intelligence
Wegman, E.J.; Gould, J.
1982-09-01
Computers and brains are modeled by finite and probabilistic automata, respectively. Probabilistic automata are known to be strictly more powerful than finite automata. The observation that the environment affects behavior of both computer and brain is made. Automata are then modeled in an environment. Theorem 1 shows that useful environmental models are those which are infinite sets. A probabilistic structure is placed on the environment set. Theorem 2 compares the behavior of finite (deterministic) and probabilistic automata in random environments. Several interpretations of theorem 2 are discussed which offer some insight into some mathematical limits of machine intelligence. 15 references.
Cellular automata modeling of weld solidification structure
Dress, W.B.; Zacharia, T.; Radhakrishnan, B.
1993-12-31
The authors explore the use of cellular automata in modeling arc-welding processes. A brief discussion of cellular automata and their previous use in micro-scale solidification simulations is presented. Macro-scale thermal calculations for arc-welding at a thin plate are shown to give good quantitative and qualitative results. Combining the two calculations in a single cellular array provides a realistic simulation of grain growth in a welding process. Results of simulating solidification in a moving melt pool in a poly-crystalline alloy sheet are presented.
Modelling and synthesis of automata in HDLs
NASA Astrophysics Data System (ADS)
Chmielewski, Sławomir; Węgrzyn, Marek
2006-10-01
In the paper digital modelling and synthesis of automata in Hardware Description Languages is described. There is presented different kinds of automata and methods of realization using languages like VHDL and Verilog. Basic models for control units are: Finite State Machine (FSM), Algorithmic State Machine (ASM) and Linked State Machine (LSM). FSM, ASM and LSM can be represented graphically, which would help a designer to visualize and design in a more efficient way. On the other hand, a designer needs a fast and direct way to convert the considered designs into Hardware Description Language (HDL) codes for simulation and analysis it for synthesis and implementation.
Towards modeling DNA sequences as automata
NASA Astrophysics Data System (ADS)
Burks, Christian; Farmer, Doyne
1984-01-01
We seek to describe a starting point for modeling the evolution and role of DNA sequences within the framework of cellular automata by discussing the current understanding of genetic information storage in DNA sequences. This includes alternately viewing the role of DNA in living organisms as a simple scheme and as a complex scheme; a brief review of strategies for identifying and classifying patterns in DNA sequences; and finally, notes towards establishing DNA-like automata models, including a discussion of the extent of experimentally determined DNA sequence data present in the database at Los Alamos.
Automata theory. 1964-May 1983 (Citations from the NTIS Data Base)
Not Available
1983-06-01
Research reports are cited on pushdown automata, tessellation automata, web automata, and finite state automata. Studies on finite state machines, turing machines, and sequential machines are included. Research on Boolean functions, recursive functions, the Moore model, and the Mealey model, as applied to automata theory, are also covered. (This updated bibliography contains 298 citations, 41 of which are new entries to the previous edition.)
Particle learning for probabilistic deterministic finite automata
2011-09-01
The plpdfa software is a product of an LDRD project at LLNL entitked "Adaptive Sampling for Very High Throughput Data Streams" (tracking number 11-ERD-035). This software was developed by a graduate student summer intern, Chris Challis, who worked under project PI Dan Merl furing the summer of 2011. The software the source code is implementing is a statistical analysis technique for clustering and classification of text-valued data. The method had been previously published by themore » PI in the open literature.« less
Particle learning for probabilistic deterministic finite automata
2011-09-01
The plpdfa software is a product of an LDRD project at LLNL entitked "Adaptive Sampling for Very High Throughput Data Streams" (tracking number 11-ERD-035). This software was developed by a graduate student summer intern, Chris Challis, who worked under project PI Dan Merl furing the summer of 2011. The software the source code is implementing is a statistical analysis technique for clustering and classification of text-valued data. The method had been previously published by the PI in the open literature.
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…
The Relationship between Intelligence, Approaches to Learning and Academic Achievement.
ERIC Educational Resources Information Center
Diseth, Age
2002-01-01
Administered three tests of intelligence and the Approaches and Study Skills Inventory for Students (Entwhistle, 1997) to 89 Norwegian undergraduates to study the relationships among intelligence, approaches of learning, and academic achievement. Findings support the construct validity of approaches to learning because of its independence from…
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…
Stochastic Games for Verification of Probabilistic Timed Automata
NASA Astrophysics Data System (ADS)
Kwiatkowska, Marta; Norman, Gethin; Parker, David
Probabilistic timed automata (PTAs) are used for formal modelling and verification of systems with probabilistic, nondeterministic and real-time behaviour. For non-probabilistic timed automata, forwards reachability is the analysis method of choice, since it can be implemented extremely efficiently. However, for PTAs, such techniques are only able to compute upper bounds on maximum reachability probabilities. In this paper, we propose a new approach to the analysis of PTAs using abstraction and stochastic games. We show how efficient forwards reachability techniques can be extended to yield both lower and upper bounds on maximum (and minimum) reachability probabilities. We also present abstraction-refinement techniques that are guaranteed to improve the precision of these probability bounds, providing a fully automatic method for computing the exact values. We have implemented these techniques and applied them to a set of large case studies. We show that, in comparison to alternative approaches to verifying PTAs, such as backwards reachability and digital clocks, our techniques exhibit superior performance and scalability.
Fuzzy cellular automata models in immunology
NASA Astrophysics Data System (ADS)
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.
Dynamical Systems Perspective of Wolfram's Cellular Automata
NASA Astrophysics Data System (ADS)
Courbage, M.; Kamiński, B.
2013-01-01
Leon Chua, following Wolfram, devoted a big effort to understand deeply the wealth of complexity of the rules of all elementary one-dimensional cellular automata from the point of view of the nonlinear dynamicist. Here we complete this point of view by a dynamical system perspective, extending them to the limit of infinite number of sites.
Self-reproduction in small cellular automata
NASA Astrophysics Data System (ADS)
Byl, John
1989-01-01
Self-reproduction in cellular automata is discussed with reference to Langton's criteria as to what constitutes genuine self-reproduction. It is found that it is possible to construct self-reproducing structures that are substantially less complex than that presented by Langton.
Partial Derivative Automata Formalized in Coq
NASA Astrophysics Data System (ADS)
Almeida, José Bacelar; Moreira, Nelma; Pereira, David; de Sousa, Simão Melo
In this paper we present a computer assisted proof of the correctness of a partial derivative automata construction from a regular expression within the Coq proof assistant. This proof is part of a formalization of Kleene algebra and regular languages in Coq towards their usage in program certification.
Additive Cellular Automata and Volume Growth
NASA Astrophysics Data System (ADS)
Ward, Thomas B.
2000-09-01
A class of dynamical systems associated to rings of S-integers in rational function fields is described. General results about these systems give a rather complete description of the well-known dynamics in one-dimensional additive cellular automata with prime alphabet, including simple formulæ for the topological entropy and the number of periodic configurations. For these systems the periodic points are uniformly distributed along some subsequence with respect to the maximal measure, and in particular are dense. Periodic points may be constructed arbitrarily close to a given configuration, and rationality of the dynamical zeta function is characterized. Throughout the emphasis is to place this particular family of cellular automata into the wider context of S-integer dynamical systems, and to show how the arithmetic of rational function fields determines their behaviour. Using a covering space the dynamics of additive cellular automata are related to a form of hyperbolicity in completions of rational function fields. This expresses the topological entropy of the automata directly in terms of volume growth in the covering space.
ERIC Educational Resources Information Center
Phan, Huy P.
2008-01-01
Introduction: Recent research in educational psychology has explored student approaches to learning (SAL) and epistemological beliefs within the theoretical framework of self-regulated learning. The focus of this research study seeks to explore the predictiveness of learning approaches and epistemological beliefs on students' self-regulatory…
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…
ERIC Educational Resources Information Center
Baeten, Marlies; Dochy, Filip; Struyven, Katrien
2013-01-01
Previous research has shown the difficulty of enhancing students' approaches to learning, in particular the deep approach, through student-centred teaching methods such as problem- and case-based learning. This study investigates whether mixed instructional methods combining case-based learning and lectures have the power to enhance students'…
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…
Supervised nuclear track detection of CR-39 detectors by cellular automata
NASA Astrophysics Data System (ADS)
Chahkandi Nejad, Hadi; Khayat, Omid; Mohammadi, Kheirollah; Tavakoli, Saeed
2014-05-01
In this paper, cellular automata are used to detect the nuclear tracks in the track images captured from the surface of CR-39 detectors. Parameters of the automaton as the states, neighborhood, rules and quality parameters are defined optimally for the track image data set under analysis. The presented method is a supervised computational algorithm which comprises a rule definition phase as the learning procedure. Parameter optimization is also performed to adapt the algorithm to the data set used.
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…
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…
(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…
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…
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…
Assessing the Learning Organization: Part 2--Exploring Practical Assessment Approaches.
ERIC Educational Resources Information Center
Tosey, Paul; Smith, Peter A. C.
1999-01-01
Presents two approaches to assessing learning organizations: (1) Focus, Will, Capability, Performance System and (2) organizations as energies. Describes ways in which behavior change is measured in each approach. (SK)
Encoding nondeterministic fuzzy tree automata into recursive neural networks.
Gori, Marco; Petrosino, Alfredo
2004-11-01
Fuzzy neural systems have been a subject of great interest in the last few years, due to their abilities to facilitate the exchange of information between symbolic and subsymbolic domains. However, the models in the literature are not able to deal with structured organization of information, that is typically required by symbolic processing. In many application domains, the patterns are not only structured, but a fuzziness degree is attached to each subsymbolic pattern primitive. The purpose of this paper is to show how recursive neural networks, properly conceived for dealing with structured information, can represent nondeterministic fuzzy frontier-to-root tree automata. Whereas available prior knowledge expressed in terms of fuzzy state transition rules are injected into a recursive network, unknown rules are supposed to be filled in by data-driven learning. We also prove the stability of the encoding algorithm, extending previous results on the injection of fuzzy finite-state dynamics in high-order recurrent networks. PMID:15565771
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.
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…
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…
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…
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…
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…
Hong Kong Students' Approaches to Learning: Cross-Cultural Comparisons
ERIC Educational Resources Information Center
Dasari, Bhoomiah
2009-01-01
Anecdotal evidence abounds in Hong Kong to the effect that students entering tertiary education are predisposed to a "rote" learning approach. With the internalisation of higher education in many countries, there is still insufficient understanding of how Chinese students approach their learning. Except few studies were conducted locally, there…
Conceptions of and Approaches to Learning through Online Peer Assessment
ERIC Educational Resources Information Center
Yang, Yu-Fang; Tsai, Chin-Chung
2010-01-01
The present study investigated junior college students' conceptions of and approaches to learning via online peer assessment (PA) using a phenomenographic approach. Participants were 163 college students. Students were asked to accomplish a given learning task via an online PA system. Of the participants, 62 were interviewed after the activity.…
Students' Approaches to Learning a New Mathematical Model
ERIC Educational Resources Information Center
Flegg, Jennifer A.; Mallet, Daniel G.; Lupton, Mandy
2013-01-01
In this article, we report on the findings of an exploratory study into the experience of undergraduate students as they learn new mathematical models. Qualitative and quantitative data based around the students' approaches to learning new mathematical models were collected. The data revealed that students actively adopt three approaches to…
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…
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…
Argumentation Based Joint Learning: A Novel Ensemble Learning Approach
Xu, Junyi; Yao, Li; Li, Le
2015-01-01
Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification. PMID:25966359
Learning Based Approach for Optimal Clustering of Distributed Program's Call Flow Graph
NASA Astrophysics Data System (ADS)
Abofathi, Yousef; Zarei, Bager; Parsa, Saeed
Optimal clustering of call flow graph for reaching maximum concurrency in execution of distributable components is one of the NP-Complete problems. Learning automatas (LAs) are search tools which are used for solving many NP-Complete problems. In this paper a learning based algorithm is proposed to optimal clustering of call flow graph and appropriate distributing of programs in network level. The algorithm uses learning feature of LAs to search in state space. It has been shown that the speed of reaching to solution increases remarkably using LA in search process, and it also prevents algorithm from being trapped in local minimums. Experimental results show the superiority of proposed algorithm over others.
Lifelong Learning in Architectural Design Studio: The Learning Contract Approach
ERIC Educational Resources Information Center
Hassanpour, B.; Che-Ani, A. I.; Usman, I. M. S.; Johar, S.; Tawil, N. M.
2015-01-01
Avant-garde educational systems are striving to find lifelong learning methods. Different fields and majors have tested a variety of proposed models and found varying difficulties and strengths. Architecture is one of the most critical areas of education because of its special characteristics, such as learning by doing and complicated evaluation…
Problem Finding in Professional Learning Communities: A Learning Study Approach
ERIC Educational Resources Information Center
Tan, Yuen Sze Michelle; Caleon, Imelda Santos
2016-01-01
This study marries collaborative problem solving and learning study in understanding the onset of a cycle of teacher professional development process within school-based professional learning communities (PLCs). It aimed to explore how a PLC carried out collaborative problem finding--a key process involved in collaborative problem solving--that…
Nonsynchronous updating in the multiverse of cellular automata.
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. PMID:25974442
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.
Generational diversity: teaching and learning approaches.
Johnson, Susan A; Romanello, Mary L
2005-01-01
Nursing students represent multiple generations--Baby Boomers, Generation X, and now the Millennials. Each generation has its own set of values, ideas, ethics, beliefs, and learning styles. The authors describe the context, characteristics, and learning styles of each generation and provide suggestions for enhanced teaching and learning across multiple generations. Using generational diversity as a teaching tool in the classroom is also discussed. PMID:16170263
GARDENS OF EDEN OF ELEMENTARY CELLULAR AUTOMATA.
Barrett, C. L.; Chen, W. Y. C.; Reidys, C. M.
2001-01-01
Using de Bruijn graphs, we give a characterization of elementary cellular automata on the linear lattice that do not have any Gardens of Eden. It turns out that one can easily recoginze a CA that does not have any Gardens of Eden by looking at its de Bruijn graph. We also present a sufficient condition for the set of words accepted by a CA not to constitute a finite-complement language.
Cellular automata model for citrus variegated chlorosis.
Martins, M L; Ceotto, G; Alves, S G; Bufon, C C; Silva, J M; Laranjeira, F F
2000-11-01
A cellular automata model is proposed to analyze the progress of citrus variegated chlorosis epidemics in São Paulo orange plantations. In this model epidemiological and environmental features, such as motility of sharpshooter vectors that perform Lévy flights, level of plant hydric and nutritional stress, and seasonal climatic effects, are included. The observed epidemic data were quantitatively reproduced by the proposed model on varying the parameters controlling vector motility, plant stress, and initial population of diseased plants. PMID:11102058
Child Development: An Active Learning Approach
ERIC Educational Resources Information Center
Levine, Laura E.; Munsch, Joyce
2010-01-01
Within each chapter of this innovative topical text, the authors engage students by demonstrating the wide range of real-world applications of psychological research connected to child development. In particular, the distinctive Active Learning features incorporated throughout the book foster a dynamic and personal learning process for students.…
Design Approaches in Technology-Enhanced Learning
ERIC Educational Resources Information Center
Mor, Yishay; Winters, Niall
2007-01-01
Design is critical to the successful development of any interactive learning environment (ILE). Moreover, in technology-enhanced learning (TEL) the design process requires input from many diverse areas of expertise. As such, anyone undertaking tool development is required to directly address the design challenge from multiple perspectives. We…
A New Approach to Group Learning
ERIC Educational Resources Information Center
Parsons, Jerry
1976-01-01
To help teachers plan strategy for working with a learning group, 12 factors affecting a learning group are discussed and a series of check points are identified as criteria for evaluation. Concepts and principles of group dynamics are drawn from sociology and the work of Carl Rogers. (Author/AJ)
Understanding Observational Learning: An Interbehavioral Approach
ERIC Educational Resources Information Center
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…
Individualistic and Collectivistic Approaches to Language Learning
ERIC Educational Resources Information Center
Pena, Elizabeth D.; Mendez-Perez, Anita
2006-01-01
Mediated learning describes what parents and teachers do to teach and includes four components: (1) intent to teach; (2) competence; (3) transcendence to promote high level thinking; and (4) mediation of meaning, helping children to focus on the importance of what is being focused on. Mediated learning is assumed to be universal for all cultural…
Holistic Approaches to E-Learning Accessibility
ERIC Educational Resources Information Center
Phipps, Lawrie; Kelly, Brian
2006-01-01
The importance of accessibility to digital e-learning resources is widely acknowledged. The World Wide Web Consortium Web Accessibility Initiative has played a leading role in promoting the importance of accessibility and developing guidelines that can help when developing accessible web resources. The accessibility of e-learning resources…
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…
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…
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…
A Team Approach to Successful Learning: Peer Learning Coaches in Chemistry
ERIC Educational Resources Information Center
Popejoy, Kate; Asala, Kathryn S.
2013-01-01
High failure rates in introductory large lecture chemistry courses for STEM majors have been of concern for years. Through our weekly Team Approach to Successful Learning (TASL) workshops, students learn and apply problem-solving strategies, coached by specially trained peer learning coaches (LCs). These coaches concurrently enroll in Chemistry…
ERIC Educational Resources Information Center
Struyven, Katrien; Dochy, Filip; Janssens, Steven; Gielen, Sarah
2006-01-01
This study investigates the effects of the learning/teaching environment on students' approaches to learning (i.e. combination of intention and learning strategies) and compares a lecture based to a student-activating setting within the first year of elementary teacher education. Data collection (N = 790) was carried out using a pre-test/post-test…
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…
ERIC Educational Resources Information Center
Zandi, Hamed; Kaivanpanah, Shiva; Alavi, Sayyed Mohammad
2015-01-01
Contract learning as an approach to individualizing education in the context of assessment for learning is relatively underexplored in English as a Foreign Language instruction. The present study used a mixed-methods design to investigate its efficacy to provide feedback to students and improve self-directed learning. Furthermore, it studied…
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…
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.
A Goal-Based Approach for Learning in Business Processes
NASA Astrophysics Data System (ADS)
Soffer, Pnina; Ghattas, Johny; Peleg, Mor
Organizations constantly strive to improve their business performance; hence they make business process redesign efforts. So far, redesign has mainly been a human task, which relies on human reasoning and creativity, although various analysis tools can support it by identifying improvement opportunities. This chapter proposes an automated approach for learning from accumulated experience and improving business processes over time. The approach ties together three aspects of business processes: goals, context, and actual paths. It proposes a learning cycle, including a learning phase, where the relevant context is identified and used for making improvements in the process model, and a runtime application phase, where the improved process model is applied at runtime and actual results are stored for the next learning cycle. According to our approach, a goal-oriented process model is essential for learning to improve process outcomes.
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.
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.
Cellular automata simulation of traffic including cars and bicycles
NASA Astrophysics Data System (ADS)
Vasic, Jelena; Ruskin, Heather J.
2012-04-01
As 'greening' of all aspects of human activity becomes mainstream, transportation science is also increasingly focused around sustainability. Modal co-existence between motorised and non-motorised traffic on urban networks is, in this context, of particular interest for traffic flow modelling. The main modelling problems here are posed by the heterogeneity of vehicles, including size and dynamics, and by the complex interactions at intersections. Herein we address these with a novel technique, based on one-dimensional cellular automata components, for modelling network infrastructure and its occupancy by vehicles. We use this modelling approach, together with a corresponding vehicle behaviour model, to simulate combined car and bicycle traffic for two elemental scenarios-examples of components that would be used in the building of an arbitrary network. Results of simulations performed on these scenarios, (i) a stretch of road and (ii) an intersection causing conflict between cars and bicycles sharing a lane, are presented and analysed.
Learning from project experiences using a legacy-based approach
NASA Technical Reports Server (NTRS)
Cooper, Lynne P.; Majchrzak, Ann; Faraj, Samer
2005-01-01
As project teams become used more widely, the question of how to capitalize on the knowledge learned in project teams remains an open issue. Using previous research on shared cognition in groups, an approach to promoting post-project learning was developed. This Legacy Review concept was tested on four in tact project teams. The results from those test sessions were used to develop a model of team learning via group cognitive processes. The model and supporting propositions are presented.
Learning Approach and Learning Strengths: A Case Study in an Ultraorthodox Community
ERIC Educational Resources Information Center
Aflalo, Ester
2012-01-01
This study furthers the understanding of the connections between learning approaches and learning strengths. The research population embraced 65 males from the Jewish ultraorthodox community, who abide by distinct methods of study. One group follows the very didactic, linear and structured approach with performance orientation, while the second…
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,…
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…
Learning Styles and Approaches to Learning in Excellent and Average First-Year University Students
ERIC Educational Resources Information Center
Gargallo López, Bernardo; Almerich Cerveró, Gonzalo; Suárez Rodríguez, Jesús M.; García Félix, Eloïna; Garfella Esteban, Pedro R.
2013-01-01
We assessed the learning approaches and learning styles of a sample of 148 excellent students selected from 11 degrees from nine centers of the Polytechnic University of Valencia (Spain), and we compared the results with those of a sample of 133 average students from the same centers. We found that excellent students took deeper approach than…
Situated Poetry Learning Using Multimedia Resource Sharing Approach
ERIC Educational Resources Information Center
Yang, Che-Ching; Tseng, Shian-Shyong; Liao, Anthony Y. H.; Liang, Tyne
2013-01-01
Educators have emphasized the importance of situating students in an authentic learning environment. By using such approach, teachers can encourage students to learn Chinese poems by browsing content resources and relevant online multimedia resources by using handheld devices. Nevertheless, students in heterogeneous network environments may have…
University Students' Achievement Goals and Approaches to Learning in Mathematics
ERIC Educational Resources Information Center
Cano, Francisco; Berben, A. B. G.
2009-01-01
Background: Achievement goals (AG) and students' approaches to learning (SAL) are two research perspectives on student motivation and learning in higher education that have until now been pursued quite independently. Aims: This study sets out: (a) to explore the relationship between the most representative variables of SAL and AG; (b) to identify…
Blended Learning in Higher Education: Three Different Design Approaches
ERIC Educational Resources Information Center
Alammary, Ali; Sheard, Judy; Carbone, Angela
2014-01-01
Blended learning has been growing in popularity as it has proved to be an effective approach for accommodating an increasingly diverse student population whilst adding value to the learning environment through incorporation of online teaching resources. Despite this growing interest, there is ongoing debate about the definition of the concept of…
Developing a Competency-Based Assessment Approach for Student Learning
ERIC Educational Resources Information Center
Dunning, Pamela T.
2014-01-01
Higher education accrediting bodies are increasing the emphasis on assessing student learning outcomes as opposed to teaching methodology. The purpose of this article is to describe the process used by Troy University's Master of Public Administration program to change their assessment approach from a course learning objective perspective to a…
A Challenge-Feedback Learning Approach to Teaching International Business
ERIC Educational Resources Information Center
Sternad, Dietmar
2015-01-01
This article introduces a challenge-feedback learning (CFL) approach based on the goal-setting theory of human motivation, the deliberate practice theory of expert performance, and findings from the research on active and collaborative learning. The core of the teaching concept is the CFL cycle in which students repeatedly progress through four…
Students' Studying and Approaches to Learning in Introductory Biology
ERIC Educational Resources Information Center
Tomanek, Debra; Montplaisir, Lisa
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…
Contextualized Teaching & Learning: A Promising Approach for Basic Skills Instruction
ERIC Educational Resources Information Center
Baker, Elaine DeLott; Hope, Laura; Karandjeff, Kelley
2009-01-01
Contextualized teaching and learning (CTL), or the concept of relating subject matter content to meaningful situations that are relevant to students' lives, offers one promising approach to helping students learn more effectively. This brief offers instructors, college leaders, policy makers and funders a high-level summary of the CTL…
Learning Objects Update: Review and Critical Approach to Content Aggregation
ERIC Educational Resources Information Center
Balatsoukas, Panos; Morris, Anne; O'Brien, Ann
2008-01-01
The structure and composite nature of a learning object is still open to interpretation. Although several theoretical studies advocate integrated approaches to the structure and aggregation level of learning objects, in practice, many content specifications, such as SCORM, IMS Content Packaging, and course authoring tools, do not explicitly state…
Teaching Math in the Primary Grades: The Learning Trajectories Approach
ERIC Educational Resources Information Center
Sarama, Julie; Clements, Douglas
2009-01-01
Children's thinking follows natural developmental paths in learning math. When teachers understand those paths and offer activities based on children's progress along them, they build developmentally appropriate math environments. The authors explain math learning trajectories and why teaching math using the trajectories approach is effective. A…
Sound Foundations: Organic Approaches to Learning Notation in Beginning Band
ERIC Educational Resources Information Center
West, Chad
2016-01-01
By starting with a foundation of sound before sight, we can help our students learn notation organically in a way that honors the natural process. This article describes five organic approaches to learning notation in beginning band: (1) iconic notation, (2) point and play, (3) student lead-sheet, (4) modeling, and (5) kid dictation. While…
Afterschool Programs: Inspiring Students with a Connected Learning Approach
ERIC Educational Resources Information Center
Afterschool Alliance, 2015
2015-01-01
Afterschool programs have been among the pioneers in applying a connected learning approach-creating a learning environment for students that builds on their interests; introduces them to new passions; provides mentors and a supportive peer network; and links this engagement to academics, careers and civic participation. This report, discusses the…
Practical Approaches to Using Learning Styles in Higher Education.
ERIC Educational Resources Information Center
Dunn, Rita, Ed.; Griggs, Shirley A., Ed.
The focus of this collection of essays is on new approaches to teaching in higher education. Selections are organized in five sections; the first section focuses on learning styles, while the remaining sections focus on applications in various academic disciplines. The chapters include: (1) "Capitalizing on College Students' Learning Styles:…
Approaches to Learning: Supporting Brain Development for School Success
ERIC Educational Resources Information Center
Petersen, Sandra
2012-01-01
Prenatally and in infants and toddlers, the brain is being constructed as a foundation for all later learning. Positive early experiences contribute to the formation of a brain that is capable, early in infancy, of utilizing and strengthening the basic processes of learning. Throughout a lifetime, a person will repeatedly use these approaches to…
Exploring the Behavioural Patterns of Entrepreneurial Learning: A Competency Approach
ERIC Educational Resources Information Center
Man, Thomas Wing Yan
2006-01-01
Purpose: The purpose of this study is to empirically explore the behavioural patterns involved in entrepreneurial learning through a conceptualization of entrepreneurial learning as a "competency". Design/methodology/approach: Semi-structured interviews to 12 entrepreneurs were conducted with a focus on the critical incidents in which significant…
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…
A Hybrid Approach to University Subject Learning Activities
ERIC Educational Resources Information Center
Osorio Gomez, Luz Adriana; Duart, Josep M.
2012-01-01
In order to get a better understanding of subject design and delivery using a hybrid approach, we have studied a hybrid learning postgraduate programme offered by the University of the Andes, Bogota, Colombia. The study analyses students' perceptions of subject design and delivery, with particular reference to learning activities and the roles of…
Mini Anchors: A Universal Design for Learning Approach
ERIC Educational Resources Information Center
Zydney, Janet Mannheimer; Hasselbring, Ted S.
2014-01-01
Teachers are challenged to create flexible learning environments that prepare students with diverse learning needs for adaptable thinking in a fast-paced and changing society. To address this need, we used a design-based research approach to develop a technology-based solution to individualize mathematical problem solving instruction to students…
Group Experiential Learning with Undergraduate Nursing Students: An Interdisciplinary Approach
ERIC Educational Resources Information Center
Pistole, M. Carole; Kinyon, Jane; Keith, Cynthia Bozich
2008-01-01
This research examined an interdisciplinary, collaborative experiential group learning approach, in which undergraduate nursing students met in small groups led by counseling doctoral student co-leaders. Statistical analysis suggests that the teaching method lead to learning of group concepts. Discussion addresses anecdotal observations,…
Students' Evaluation of Teaching, Approaches to Learning, and Academic Achievement
ERIC Educational Resources Information Center
Diseth, Age
2007-01-01
Students' evaluation and perception of the learning environment are considered to be important predictors of students' approaches to learning. These variables may also account for variance in academic outcome, such as in examination grades, but previous research has rarely included a comparison between all of these variables. This article…
An active learning approach with uncertainty, representativeness, and diversity.
He, Tianxu; Zhang, Shukui; Xin, Jie; Zhao, Pengpeng; Wu, Jian; Xian, Xuefeng; Li, Chunhua; Cui, Zhiming
2014-01-01
Big data from the Internet of Things may create big challenge for data classification. Most active learning approaches select either uncertain or representative unlabeled instances to query their labels. Although several active learning algorithms have been proposed to combine the two criteria for query selection, they are usually ad hoc in finding unlabeled instances that are both informative and representative and fail to take the diversity of instances into account. We address this challenge by presenting a new active learning framework which considers uncertainty, representativeness, and diversity creation. The proposed approach provides a systematic way for measuring and combining the uncertainty, representativeness, and diversity of an instance. Firstly, use instances' uncertainty and representativeness to constitute the most informative set. Then, use the kernel k-means clustering algorithm to filter the redundant samples and the resulting samples are queried for labels. Extensive experimental results show that the proposed approach outperforms several state-of-the-art active learning approaches. PMID:25180208
An Active Learning Approach with Uncertainty, Representativeness, and Diversity
He, Tianxu; Zhang, Shukui; Xin, Jie; Xian, Xuefeng; Li, Chunhua; Cui, Zhiming
2014-01-01
Big data from the Internet of Things may create big challenge for data classification. Most active learning approaches select either uncertain or representative unlabeled instances to query their labels. Although several active learning algorithms have been proposed to combine the two criteria for query selection, they are usually ad hoc in finding unlabeled instances that are both informative and representative and fail to take the diversity of instances into account. We address this challenge by presenting a new active learning framework which considers uncertainty, representativeness, and diversity creation. The proposed approach provides a systematic way for measuring and combining the uncertainty, representativeness, and diversity of an instance. Firstly, use instances' uncertainty and representativeness to constitute the most informative set. Then, use the kernel k-means clustering algorithm to filter the redundant samples and the resulting samples are queried for labels. Extensive experimental results show that the proposed approach outperforms several state-of-the-art active learning approaches. PMID:25180208
Exploiting the features of the finite state automata for biomolecular computing.
Martínez-Pérez, Israel Marck; Ignatova, Zoya; Zimmermann, Karl-Heinz
2009-01-01
Here, we review patents that have emerged in the field of DNA-based computing focusing thereby on the discoveries using the concept of molecular finite state automata. A finite state automaton, operating on a finite sequence of symbols and converting information from one to another, provides a basis for developing molecular-scale autonomous programmable models of biomolecular computation at cellular level. We also provide a brief overview on inventions which methodologically support the DNA-based computational approach. PMID:19519583
Service-Learning Pedagogy: Benefits of a Learning Community Approach
ERIC Educational Resources Information Center
Flinders, Brooke A.
2013-01-01
Service-learning is, by nature, continually evolving. Seifer (1996) stressed the importance of partnerships between communities and schools, and stated that reflection should facilitate the connection between practice and theory, and lead to critical thinking. Before these reflective activities occur, however, much can be done to maximize…
Promoting Hybrid Learning through a Sharable eLearning Approach
ERIC Educational Resources Information Center
Bai, Xin; Smith, Michael B.
2010-01-01
Educational technology is developing rapidly, making education more accessible, affordable, adaptable, and equitable. Students now have the option to choose a campus that can provide an excellent blended learning curriculum with minimal geographical restraints. We explored ways to maximize the power of educational technologies to improve teaching…
Self-structuring data learning approach
NASA Astrophysics Data System (ADS)
Ternovskiy, Igor; Graham, James; Carson, Daniel
2016-05-01
In this paper, we propose a hierarchical self-structuring learning algorithm based around the general principles of the Stanovich/Evans framework and "Quest" group definition of unexpected query. One of the main goals of our algorithm is for it to be capable of patterns learning and extrapolating more complex patterns from less complex ones. This pattern learning, influenced by goals, either learned or predetermined, should be able to detect and reconcile anomalous behaviors. One example of a proposed application of this algorithm would be traffic analysis. We choose this example, because it is conceptually easy to follow. Despite the fact that we are unlikely to develop superior traffic tracking techniques using our algorithm, a traffic based scenario remains a good starting point if only do to the easy availability of data and the number of other known techniques. In any case, in this scenario, the algorithm would observe and track all vehicular traffic in a particular area. After some initial time passes, it would begin detecting and learning the traffic's patters. Eventually the patterns would stabilize. At that point, "new" patterns could be considered anomalies, flagged, and handled accordingly. This is only one, particular application of our proposed algorithm. Ideally, we want to make it as general as possible, such that it can be applies to numerous different problems with varying types of sensory input and data types, such as IR, RF, visual, census data, meta data, etc.
Larvae, Ladies and Learning: The Project Approach.
ERIC Educational Resources Information Center
Whitham, Laurel; Killoran, Isabel
2003-01-01
Describes the Project Approach and how it was used in a Grade 1 exploration of Painted Lady butterflies in Ontario, Canada. Outlines the students' experience with the project and examines the compatibility of the Project Approach with the Ontario Science and Technology Curriculum document. Maintains that the Project Approach supports and…
Learning topological maps: An alternative approach
Buecken, A.; Thrun, S.
1996-12-31
Our goal is autonomous real-time control of a mobile robot. In this paper we want to show a possibility to learn topological maps of a large-scale indoor environment autonomously. In the literature there are two paradigms how to store information on the environment of a robot: as a grid-based (geometric) or as a topological map. While grid-based maps are considerably easy to learn and maintain, topological maps are quite compact and facilitate fast motion-planning.
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…
A Cognitive Approach to Student-Centered e-Learning
Greitzer, Frank L.
2002-09-30
Like traditional classroom instruction, distance/electronic learning (e-Learning) derives from largely behaviorist computer-based instruction paradigms that tend to reflect passive training philosophies. Over the past thirty years, more flexible, student-centered classroom teaching methods have been advocated based on the concepts of ''discovery'' learning and ''active'' learning; student-centered approaches are likewise encouraged in the development of e-Learning applications. Nevertheless, many e-Learning applications that employ state-of-the art multimedia technology in which students interact with simulations, animations, video, and sounds still fail to meet their expected training potential. Implementation of multimedia-based training features may give the impression of engaging the student in more active forms of learning, but sophisticated use of multimedia features does not necessarily produce the desired effect. This paper briefly reviews some general guidelines for applying cognitive science principles to development of student-centered e-Learning applications and describes a cognitive approach to e-Learning development that is being undertaken for the US Army.
Newton's First Law: A Learning Cycle Approach
ERIC Educational Resources Information Center
McCarthy, Deborah
2005-01-01
To demonstrate how Newton's first law of motion applies to students' everyday lives, the author developed a learning cycle series of activities on inertia. The discrepant event at the heart of these activities is sure to elicit wide-eyed stares and puzzled looks from students, but also promote critical thinking and help bring an abstract concept…
The Learning Centers Approach to Instruction.
ERIC Educational Resources Information Center
George, Paul S.; And Others
The learning center is a place for using and storing materials that relate to a special interest or curriculum area. It is a place where the students, after consulting with the teacher, may go to work; where ideas, materials, and activities are presented on a variety of levels of difficulty. Teachers, however, must first decide what the role of…
Bangladeshi EFL Learners' Approach towards Learning English
ERIC Educational Resources Information Center
Fathema, Fawzia
2015-01-01
Bangladesh is a poverty stricken country with a huge population "unemployed' in respect of the definition of Economics including both male and female. Government is striving hard to make the people well-equipped with necessary skills and learning in order that they can prove themselves fit for the upcoming challenges of the global economy and…
Integrated Learning Systems--An 'Open' Approach.
ERIC Educational Resources Information Center
Rogers, Laurence; Newton, Leonard
2001-01-01
Evaluates a new version of software explicitly designed to make links with several external factors, in particular with another software application for supporting investigative work in practical science. Explores the contributions to the learning process made by the teacher, the student, and the software itself. (Author/SAH)
Flipped Approach to Mobile Assisted Language Learning
ERIC Educational Resources Information Center
Yamamoto, Junko
2013-01-01
There are abundant possibilities for using smart phones and tablet computers for foreign language learning. However, if there is an emphasis on memorization or on technology, language learners may not develop proficiency in their target language. Therefore, language teachers should be familiar with strategies for facilitating creative…
A Belgian Approach to Learning Disabilities.
ERIC Educational Resources Information Center
Hayes, Cheryl W.
The paper reviews Belgian philosophy toward the education of learning disabled students and cites the differences between American behaviorally-oriented theory and Belgian emphasis on identifying the underlying causes of the disability. Academic methods observed in Belgium (including psychodrama and perceptual motor training) are discussed and are…
Teaching and Learning Forgiveness: A Multidimensional Approach
ERIC Educational Resources Information Center
Malcolm, Lois; Ramsey, Janet
2006-01-01
This essay seeks to illumine the teaching and learning of the practice of forgiveness by relating a range of theoretical perspectives (theological, psychological, and socio-cultural) to the process of cultivating the practical wisdom needed for forgiveness. We discuss how a Trinitarian "epistemology of the cross" might lead one to a new way of…
Approaches to the Validation of Learning Hierarchies.
ERIC Educational Resources Information Center
Resnick, Lauren B.; Wang, Margaret C.
This paper describes a program of research in the application of scalogram analysis to the validation of learning hierarchies, together with the development of an alternative method for assessing hierarchical relationships among tests of instructional objectives. The relationship between scalability of tests and positive transfer between…
Enterprise Approaches to Information and Learning Technology
ERIC Educational Resources Information Center
Ferrell, Gill
2007-01-01
Like it or not, an institution's IT infrastructure is a matter with which institutional strategic planners must concern themselves. Information systems represent a significant investment, they perform mission-critical functions, and the appropriate use of information and learning technologies can have a critical part to play in delivering against…
An Active Learning Approach to Teaching Statistics.
ERIC Educational Resources Information Center
Dolinsky, Beverly
2001-01-01
Provides suggestions for using active learning as the primary means to teaching statistics in order to create a collaborative environment. Addresses such strategies as using SPSS Base 7.5 for Windows and course periods centered on answering student-generated questions. Discusses various writing intensive assignments. (CMK)
The Cognitive Vocabulary Approach to Word Learning
ERIC Educational Resources Information Center
Harmon, Janis M.; Buckelew-Martin, Elizabeth; Wood, Karen D.
2010-01-01
English teachers face myriad demands every day that include not only helping students read literature in interesting and engaging ways but also attending to the needs of students challenged by the demands of more complex and sophisticated texts. Vocabulary learning is at the heart of this struggle for many students, especially for English language…
Walks: An Effective Approach to Learning.
ERIC Educational Resources Information Center
Wineberg, Lenore Peachin
1997-01-01
Whether planned or spontaneous, walks offer young children unexpected pleasures and discoveries about their environment. This article describes five strategies for using walks in early childhood programs (plan, gather information, develop safety rules, integrate with the curriculum, assess what has been learned), as well as specific indoor,…
Learning by imitation: a hierarchical approach.
Byrne, R W; Russon, A E
1998-10-01
To explain social learning without invoking the cognitively complex concept of imitation, many learning mechanisms have been proposed. Borrowing an idea used routinely in cognitive psychology, we argue that most of these alternatives can be subsumed under a single process, priming, in which input increases the activation of stored internal representations. Imitation itself has generally been seen as a "special faculty." This has diverted much research towards the all-or-none question of whether an animal can imitate, with disappointingly inconclusive results. In the great apes, however, voluntary, learned behaviour is organized hierarchically. This means that imitation can occur at various levels, of which we single out two clearly distinct ones: the "action level," a rather detailed and linear specification of sequential acts, and the "program level," a broader description of subroutine structure and the hierarchical layout of a behavioural "program." Program level imitation is a high-level, constructive mechanism, adapted for the efficient learning of complex skills and thus not evident in the simple manipulations used to test for imitation in the laboratory. As examples, we describe the food-preparation techniques of wild mountain gorillas and the imitative behaviour of orangutans undergoing "rehabilitation" to the wild. Representing and manipulating relations between objects seems to be one basic building block in their hierarchical programs. There is evidence that great apes suffer from a stricter capacity limit than humans in the hierarchical depth of planning. We re-interpret some chimpanzee behaviour previously described as "emulation" and suggest that all great apes may be able to imitate at the program level. Action level imitation is seldom observed in great ape skill learning, and may have a largely social role, even in humans. PMID:10097023
Phase transitions in coupled map lattices and in associated probabilistic cellular automata.
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. PMID:17155155
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…
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…
Modeling dynamical geometry with lattice gas automata
Hasslacher, B.; Meyer, D.A.
1998-06-27
Conventional lattice gas automata consist of particles moving discretely on a fixed lattice. While such models have been quite successful for a variety of fluid flow problems, there are other systems, e.g., flow in a flexible membrane or chemical self-assembly, in which the geometry is dynamical and coupled to the particle flow. Systems of this type seem to call for lattice gas models with dynamical geometry. The authors construct such a model on one dimensional (periodic) lattices and describe some simulations illustrating its nonequilibrium dynamics.
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%).
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…
Student Approaches to Learning in Relation to Online Course Completion
ERIC Educational Resources Information Center
Balter, Olle; Cleveland-Innes, Martha; Pettersson, Kerstin; Scheja, Max; Svedin, Maria
2013-01-01
This study investigates the relationship between approaches to studying and course completion in two online preparatory university courses in mathematics and computer programming. The students participating in the two courses are alike in age, gender, and approaches to learning. Four hundred and ninety-three students participating in these courses…
3 Colleges' Different Approaches Shape Learning in Econ 101
ERIC Educational Resources Information Center
Berrett, Dan
2012-01-01
No matter the college, a class in the principles of microeconomics is likely to cover the discipline's greatest hits. The author attends three economics courses at three colleges, and finds three very different approaches. In this article, the author discusses three colleges' different approaches that shape learning in Econ 101.
The Teaching-Learning Environment, an Information-Dynamic Approach
ERIC Educational Resources Information Center
De Blasio, Cataldo; Järvinen, Mika
2014-01-01
In the present study a generalized approach is given for the description of acquisition procedures with a particular focus on the knowledge acquisition process. The learning progression is given as an example here letting the theory to be applied to different situations. An analytical approach is performed starting from the generalized fundamental…
Work Transitions as Told: A Narrative Approach to Biographical Learning
ERIC Educational Resources Information Center
Hallqvist, Anders; Hyden, Lars-Christer
2013-01-01
In this article, we introduce a narrative approach to biographical learning; that is, an approach that considers autobiographical storytelling as a practice through which claims about life history are performed and negotiated. Using insights from narrative theory, we highlight evaluations in those narratives and suggest their crucial role in…
Theory Based Approaches to Learning. Implications for Adult Educators.
ERIC Educational Resources Information Center
Bolton, Elizabeth B.; Jones, Edward V.
This paper presents a codification of theory-based approaches that are applicable to adult learning situations. It also lists some general guidelines that can be used when selecting a particular approach or theory as a basis for planning instruction. Adult education's emphasis on practicality and the relationship between theory and practice is…
Vocation, Motivation and Approaches to Learning: A Comparative Study
ERIC Educational Resources Information Center
Arquero, Jose Luis; Fernández-Polvillo, Carmen; Hassall, Trevor; Joyce, John
2015-01-01
Purpose: The individual characteristics of students can have a strong influence on the success of the adopted innovations in terms of their transferability and sustainability. The purpose of this paper is to compare the motivations and approaches to learning on degrees with differing vocational components. Design/methodology/approach:…
ERIC Educational Resources Information Center
Butler, Deborah L.
1998-01-01
Reports findings from three studies investigating the efficacy of an instructional model designed to promote self-regulation, the Strategic Content Learning (SCL) approach. Each study comprised multiple in-depth case studies involving postsecondary students with learning disabilities who ranged in age from 19 to 48 years. Implications for theory,…
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…
Evoked Prior Learning Experience and Approach to Learning as Predictors of Academic Achievement
ERIC Educational Resources Information Center
Trigwell, Keith; Ashwin, Paul; Millan, Elena S.
2013-01-01
Background: 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…
To Learn More about Learning: The Value-Added Role of Qualitative Approaches to Assessment
ERIC Educational Resources Information Center
Newhart, Daniel W.
2015-01-01
As we face increasing accountability in higher education, how we measure student learning should exceed the calls for an account of learning that places students at the center. Qualitative approaches to assessment and theoretical underpinnings gleaned from the qualitative research tradition may provide a way that we can support a more holistic…
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…
The Relationship between Students' Approaches to Learning and the Assessment of Learning Outcomes
ERIC Educational Resources Information Center
Gijbels, David; Van de Watering, Gerard; Dochy, Filip; Van den Bossche, Piet
2005-01-01
The purpose of the present study is to gain more insight into the relationship between students' approaches to learning and students' quantitative learning outcomes, as a function of the different components of problem-solving that are measured within the assessment. Data were obtained from two sources: the revised two factor study process…
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…
ERIC Educational Resources Information Center
Cavanagh, Rob
2012-01-01
This report is about one of two phases in an investigation into associations between student engagement in classroom learning and the classroom learning environment. Both phases applied the same instrumentation to the same sample. The difference between the phases was in the measurement approach applied. This report is about application of the…
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…
The Effects of Computer Supported Problem Based Learning on Students' Approaches to Learning
ERIC Educational Resources Information Center
Ak, Serife
2011-01-01
The purpose of this paper is to investigate the effects of computer supported problem based learning on students' approaches to learning. The research was conducted as a pre-test and posttest one-grouped design used to achieve the objectives of the study. The experimental process of study lasted 5 weeks and was carried out on 78 university…
A Game-Based Learning Approach to Improving Students' Learning Achievements in a Nutrition Course
ERIC Educational Resources Information Center
Yien, Jui-Mei; Hung, Chun-Ming; Hwang, Gwo-Jen; Lin, Yueh-Chiao
2011-01-01
The aim of this study was to explore the influence of applying a game-based learning approach to nutrition education. The quasi-experimental nonequivalent-control group design was adopted in a four-week learning activity. The participants included sixty-six third graders in two classes of an elementary school. One of the classes was assigned to be…
ERIC Educational Resources Information Center
Chun, Eul Jung; Hertzog, Nancy B.; Gaffney, Janet S.; Dymond, Stacy K.
2012-01-01
The researchers described in this case study how Service Learning was incorporated within the context of an early childhood program where the teachers used the Project Approach. The Service Learning project was embedded in an investigation about water and was designed to help tsunami victims in Asia. Participants included two teachers and 12…
Weyl, Dirac and Maxwell Quantum Cellular Automata
NASA Astrophysics Data System (ADS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro
2015-10-01
Recent advances on quantum foundations achieved the derivation of free quantum field theory from general principles, without referring to mechanical notions and relativistic invariance. From the aforementioned principles a quantum cellular automata (QCA) theory follows, whose relativistic limit of small wave-vector provides the free dynamics of quantum field theory. The QCA theory can be regarded as an extended quantum field theory that describes in a unified way all scales ranging from an hypothetical discrete Planck scale up to the usual Fermi scale. The present paper reviews the automaton theory for the Weyl field, and the composite automata for Dirac and Maxwell fields. We then give a simple analysis of the dynamics in the momentum space in terms of a dispersive differential equation for narrowband wave-packets. We then review the phenomenology of the free-field automaton and consider possible visible effects arising from the discreteness of the framework. We conclude introducing the consequences of the automaton dispersion relation, leading to a deformed Lorentz covariance and to possible effects on the thermodynamics of ideal gases.
Students awareness of learning styles and their perceptions to a mixed method approach for learning
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
Galaxy morphology - An unsupervised machine learning approach
NASA Astrophysics Data System (ADS)
Schutter, A.; Shamir, L.
2015-09-01
Structural properties poses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a network of similarities between galaxy morphological types, and automatically deduce a morphological sequence of galaxies. Application of the method to the EFIGI catalog show that the morphological scheme produced by the algorithm is largely in agreement with the De Vaucouleurs system, demonstrating the ability of computer vision and machine learning methods to automatically profile galaxy morphological sequences. The unsupervised analysis method is based on comprehensive computer vision techniques that compute the visual similarities between the different morphological types. Rather than relying on human cognition, the proposed system deduces the similarities between sets of galaxy images in an automatic manner, and is therefore not limited by the number of galaxies being analyzed. The source code of the method is publicly available, and the protocol of the experiment is included in the paper so that the experiment can be replicated, and the method can be used to analyze user-defined datasets of galaxy images.
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'…
ERIC Educational Resources Information Center
Phan, Huy P.
2006-01-01
Introduction: The work of reflective thinking (Mezirow, 1991, 1998) and epistemological beliefs (Schommer, 1990, 1993; Schommer-Aikins, Duell & Hutter, 2005) is increasingly recognized as playing an important role in students' academic learning. Furthermore, students' approaches to their learning are also considered as contributing factors in…
Students' Studying and Approaches to Learning in Introductory Biology
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
A Digital Approach to Learning Petrology
NASA Astrophysics Data System (ADS)
Reid, M. R.
2011-12-01
In the undergraduate igneous and metamorphic petrology course at Northern Arizona University, we are employing petrographic microscopes equipped with relatively inexpensive ( $200) digital cameras that are linked to pen-tablet computers. The camera-tablet systems can assist student learning in a variety of ways. Images provided by the tablet computers can be used for helping students filter the visually complex specimens they examine. Instructors and students can simultaneously view the same petrographic features captured by the cameras and exchange information about them by pointing to salient features using the tablet pen. These images can become part of a virtual mineral/rock/texture portfolio tailored to individual student's needs. Captured digital illustrations can be annotated with digital ink or computer graphics tools; this activity emulates essential features of more traditional line drawings (visualizing an appropriate feature and selecting a representative image of it, internalizing the feature through studying and annotating it) while minimizing the frustration that many students feel about drawing. In these ways, we aim to help a student progress more efficiently from novice to expert. A number of our petrology laboratory exercises involve use of the camera-tablet systems for collaborative learning. Observational responsibilities are distributed among individual members of teams in order to increase interdependence and accountability, and to encourage efficiency. Annotated digital images are used to share students' findings and arrive at an understanding of an entire rock suite. This interdependence increases the individual's sense of responsibility for their work, and reporting out encourages students to practice use of technical vocabulary and to defend their observations. Pre- and post-course student interest in the camera-tablet systems has been assessed. In a post-course survey, the majority of students reported that, if available, they would use
A Variance Based Active Learning Approach for Named Entity Recognition
NASA Astrophysics Data System (ADS)
Hassanzadeh, Hamed; Keyvanpour, Mohammadreza
The cost of manually annotating corpora is one of the significant issues in many text based tasks such as text mining, semantic annotation and generally information extraction. Active Learning is an approach that deals with reduction of labeling costs. In this paper we proposed an effective active learning approach based on minimal variance that reduces manual annotation cost by using a small number of manually labeled examples. In our approach we use a confidence measure based on the model's variance that reaches a considerable accuracy for annotating entities. Conditional Random Field (CRF) is chosen as the underlying learning model due to its promising performance in many sequence labeling tasks. The experiments show that the proposed method needs considerably fewer manual labeled samples to produce a desirable result.
The use of hybrid automata for fault-tolerant vibration control for parametric failures
NASA Astrophysics Data System (ADS)
Byreddy, Chakradhar; Frampton, Kenneth D.; Yongmin, Kim
2006-03-01
The purpose of this work is to make use of hybrid automata for vibration control reconfiguration under system failures. Fault detection and isolation (FDI) filters are used to monitor an active vibration control system. When system failures occur (specifically parametric faults) the FDI filters detect and identify the specific failure. In this work we are specifically interested in parametric faults such as changes in system physical parameters; however this approach works equally well with additive faults such as sensor or actuator failures. The FDI filter output is used to drive a hybrid automaton, which selects the appropriate controller and FDI filter from a library. The hybrid automata also implements switching between controllers and filters in order to maintain optimal performance under faulty operating conditions. The biggest challenge in developing this system is managing the switching and in maintaining stability during the discontinuous switches. Therefore, in addition to vibration control, the stability associated with switching compensators and FDI filters is studied. Furthermore, the performance of two types of FDI filters is compared: filters based on parameter estimation methods and so called "Beard-Jones" filters. Finally, these simulations help in understanding the use of hybrid automata for fault-tolerant control.
The Capability Approach: Enabling Musical Learning
ERIC Educational Resources Information Center
Cameron, Kate
2012-01-01
Amartya Sen's capability approach offers a new perspective for educators throughout the curriculum. This new insight has the potential to promote a music education that is inherently tailored to the individual. In essence it asks the question: What is music education going to offer to this student? This article represents an initial enquiry into…
Cellular automata based byte error correcting codes over finite fields
NASA Astrophysics Data System (ADS)
Köroğlu, Mehmet E.; Şiap, İrfan; Akın, Hasan
2012-08-01
Reed-Solomon codes are very convenient for burst error correction which occurs frequently in applications, but as the number of errors increase, the circuit structure of implementing Reed-Solomon codes becomes very complex. An alternative solution to this problem is the modular and regular structure of cellular automata which can be constructed with VLSI economically. Therefore, in recent years, cellular automata have became an important tool for error correcting codes. For the first time, cellular automata based byte error correcting codes analogous to extended Reed-Solomon codes over binary fields was studied by Chowdhury et al. [1] and Bhaumik et al. [2] improved the coding-decoding scheme. In this study cellular automata based double-byte error correcting codes are generalized from binary fields to primitive finite fields Zp.
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.
A developmental approach to learning causal models for cyber security
NASA Astrophysics Data System (ADS)
Mugan, Jonathan
2013-05-01
To keep pace with our adversaries, we must expand the scope of machine learning and reasoning to address the breadth of possible attacks. One approach is to employ an algorithm to learn a set of causal models that describes the entire cyber network and each host end node. Such a learning algorithm would run continuously on the system and monitor activity in real time. With a set of causal models, the algorithm could anticipate novel attacks, take actions to thwart them, and predict the second-order effects flood of information, and the algorithm would have to determine which streams of that flood were relevant in which situations. This paper will present the results of efforts toward the application of a developmental learning algorithm to the problem of cyber security. The algorithm is modeled on the principles of human developmental learning and is designed to allow an agent to learn about the computer system in which it resides through active exploration. Children are flexible learners who acquire knowledge by actively exploring their environment and making predictions about what they will find,1, 2 and our algorithm is inspired by the work of the developmental psychologist Jean Piaget.3 Piaget described how children construct knowledge in stages and learn new concepts on top of those they already know. Developmental learning allows our algorithm to focus on subsets of the environment that are most helpful for learning given its current knowledge. In experiments, the algorithm was able to learn the conditions for file exfiltration and use that knowledge to protect sensitive files.
Learning strategies and study approaches of postsecondary students with dyslexia.
Kirby, John R; Silvestri, Robert; Allingham, Beth H; Parrila, Rauno; La Fave, Chantal B
2008-01-01
The present study describes the self-reported learning strategies and study approaches of college and university students with and without dyslexia and examines the relationship of those characteristics with reading ability. Students with (n = 36) and without (n = 66) dyslexia completed tests measuring reading rate, reading comprehension, reading history, learning strategies, and learning approaches. The results indicated that students without dyslexia obtained significantly higher scores than students with dyslexia in their reported use of selecting main ideas and test taking strategies. Students with dyslexia reported significantly greater use of study aids and time management strategies in comparison to students without dyslexia. Moreover, university students with dyslexia were significantly more likely to report a deep approach to learning in comparison to university students without dyslexia. Reading ability correlated positively with selecting main ideas and test taking strategies and negatively with use of study aids. The authors interpret the learning strategy results as consequences of and compensations for the difficulties that students with dyslexia have in word reading. PMID:18274505
ERIC Educational Resources Information Center
Washington, Michael H.
A systems approach was used to assess, remediate, and/or develop compensatory strategies in learning disabled college students. The approach consisted of four components: an analysis of the educational task, preparation of criterion measures, preparation of behavioral objectives, and preparation of instructional sequences. A task analysis was…
Factors Contributing to Changes in a Deep Approach to Learning in Different Learning Environments
ERIC Educational Resources Information Center
Postareff, Liisa; Parpala, Anna; Lindblom-Ylänne, Sari
2015-01-01
The study explored factors explaining changes in a deep approach to learning. The data consisted of interviews with 12 students from four Bachelor-level courses representing different disciplines. We analysed and compared descriptions of students whose deep approach either increased, decreased or remained relatively unchanged during their courses.…
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.…
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 implementation of…
Does Instructional Approach Matter? How Elaboration Plays a Crucial Role in Multimedia Learning
ERIC Educational Resources Information Center
Eysink, Tessa H. S.; de Jong, Ton
2012-01-01
This study compared the affordances of 4 multimedia learning environments for specific learning processes. The environments covered the same domain but used different instructional approaches: (a) hypermedia learning, (b) observational learning, (c) self-explanation-based learning, and (d) inquiry learning. Although they all promote an active…
An Information-Based Learning Approach to Dual Control.
Alpcan, Tansu; Shames, Iman
2015-11-01
Dual control aims to concurrently learn and control an unknown system. However, actively learning the system conflicts directly with any given control objective for it will disturb the system during exploration. This paper presents a receding horizon approach to dual control, where a multiobjective optimization problem is solved repeatedly and subject to constraints representing system dynamics. Balancing a standard finite-horizon control objective, a knowledge gain objective is defined to explicitly quantify the information acquired when learning the system dynamics. Measures from information theory, such as entropy-based uncertainty, Fisher information, and relative entropy, are studied and used to quantify the knowledge gained as a result of the control actions. The resulting iterative framework is applied to Markov decision processes and discrete-time nonlinear systems. Thus, the broad applicability and usefulness of the presented approach is demonstrated in diverse problem settings. The framework is illustrated with multiple numerical examples. PMID:25730828
Particles and Patterns in Cellular Automata
Jen, E.; Das, R.; Beasley, C.E.
1999-06-03
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Our objective has been to develop tools for studying particle interactions in a class of dynamical systems characterized by discreteness, determinism, local interaction, and an inherently parallel form of evolution. These systems can be described by cellular automata (CA) and the behavior we studied has improved our understanding of the nature of patterns generated by CAs, their ability to perform global computations, and their relationship to continuous dynamical systems. We have also developed a rule-table mathematics that enables one to custom-design CA rule tables to generate patterns of specified types, or to perform specified computational tasks.
Complex dynamics of cellular automata rule 119
NASA Astrophysics Data System (ADS)
Chen, Fang-Fang; Chen, Fang-Yue
2009-03-01
In this paper, the dynamical behaviors of cellular automata rule 119 are studied from the viewpoint of symbolic dynamics in the bi-infinite symbolic sequence space Σ2. It is shown that there exists one Bernoulli-measure global attractor of rule 119, which is also the nonwandering set of the rule. Moreover, it is demonstrated that rule 119 is topologically mixing on the global attractor and possesses the positive topological entropy. Therefore, rule 119 is chaotic in the sense of both Li-Yorke and Devaney on the global attractor. It is interesting that rule 119, a member of Wolfram’s class II which was said to be simple as periodic before, actually possesses a chaotic global attractor in Σ2. Finally, it is noted that the method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules therein.
SELF-ORGANIZED CRITICALITY AND CELLULAR AUTOMATA
CREUTZ,M.
2007-01-01
Cellular automata provide a fascinating class of dynamical systems based on very simple rules of evolution yet capable of displaying highly complex behavior. These include simplified models for many phenomena seen in nature. Among other things, they provide insight into self-organized criticality, wherein dissipative systems naturally drive themselves to a critical state with important phenomena occurring over a wide range of length and the scales. This article begins with an overview of self-organized criticality. This is followed by a discussion of a few examples of simple cellular automaton systems, some of which may exhibit critical behavior. Finally, some of the fascinating exact mathematical properties of the Bak-Tang-Wiesenfeld sand-pile model [1] are discussed.
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.
Traffic jam dynamics in stochastic cellular automata
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) and in NRW (Germany) for large scale microsimulations of network traffic.
A Child-Centred Approach to Learning about Healthy Eating
ERIC Educational Resources Information Center
Telford, Francesca
2013-01-01
Science involves children in exploring and gaining understanding about the world they live in. Use of a creative and imaginative approach to science can enhance this learning in many ways (Coates and Wilson, 2003). When presented with the challenge of teaching a series of science lessons on food and nutrition to a mixed class of years 4 and 5…
Study Process Questionnaire Manual. Student Approaches to Learning and Studying.
ERIC Educational Resources Information Center
Biggs, John B.
This manual describes the theory behind the Study Process Questionnaire (SPQ) and explains what the subscale and scale scores mean. The SPQ is a 42-item self-report questionnaire used in Australia to assess the extent to which a tertiary student at a college or university endorses different approaches to learning and the motives and strategies…
The Law Review Approach: What the Humanities Can Learn
ERIC Educational Resources Information Center
Mendenhall, Allen
2013-01-01
Readers of this journal probably know how the peer review process works in the humanities disciplines and at various journals. Therefore the author explains how the law review process generally works and then what the humanities can learn and borrow from the law review process. He ends by advocating for a hybrid law review/peer review approach to…
Approaches to Teaching Plant Nutrition. Children's Learning in Science Project.
ERIC Educational Resources Information Center
Leeds Univ. (England). Centre for Studies in Science and Mathematics Education.
During the period 1984-1986, over 30 teachers from the Yorkshire (England) region have worked in collaboration with the Children's Learning in Science Project (CLIS) developing and testing teaching schemes in the areas of energy, particle theory, and plant nutrition. The project is based upon the constructivist approach to teaching. This document…
Approaches and Strategies in Next Generation Science Learning
ERIC Educational Resources Information Center
Khine, Myint Swe, Ed.; Saleh, Issa M., Ed.
2013-01-01
"Approaches and Strategies in Next Generation Science Learning" examines the challenges involved in the development of modern curriculum models, teaching strategies, and assessments in science education in order to prepare future students in the 21st century economies. This comprehensive collection of research brings together science educators,…
A Home Learning Center Approach to Early Stimulation. Final Report.
ERIC Educational Resources Information Center
Gordon, Ira J.; Guinagh, Barry J.
The Home Learning Center (HLC) Project, a combination of research and demonstration containing phases of basic research, material development and field testing of materials and delivery system, began in 1968 as a longitudinal investigation of a home-oriented approach to intervention in the lives of very young children which might enhance their…
Three Approaches to Cooperative Learning in Higher Education.
ERIC Educational Resources Information Center
Kaufman, David; Sutow, Elliott; Dunn, Ken
1997-01-01
Offers a rationale for using cooperative learning in higher education, identifying six elements essential to its success: positive interdependence; face-to-face verbal interaction; individual accountability; social skills; group processing; appropriate grouping. Describes and compares three distinct approaches in medicine, dentistry, and…
A Narrative Approach to Supporting Students Diagnosed with Learning Disabilities
ERIC Educational Resources Information Center
Lambie, Glenn W.; Milsom, Amy
2010-01-01
Students diagnosed with learning disabilities experience many challenges that school counselors may address through narrative therapy. Narrative therapy is a postmodern, social constructionist approach based on the theoretical construct that individuals create their notions of truth and meaning of life through interpretive stories. This article…
The Learning Tree Montessori Child Care: An Approach to Diversity
ERIC Educational Resources Information Center
Wick, Laurie
2006-01-01
In this article the author describes how she and her partners started The Learning Tree Montessori Child Care, a Montessori program with a different approach in Seattle in 1979. The author also relates that the other area Montessori schools then offered half-day programs, and as a result the children who attended were, for the most part,…
Activity-Centred Approaches to Second Language Learning.
ERIC Educational Resources Information Center
Stevens, Florence
Recent research in psycholinguistics shows that experience with language in its communicative function is essential for learning to speak a second language. A suitable linguistic environment provides for the development of strategies for aural comprehension and for the acquisition of means of expression. A different approach to curriculum is…
Instructional Approaches to Slow Learning. Practical Suggestions for Teaching Series.
ERIC Educational Resources Information Center
Younie, William J.
Designed for teachers, the text distinguishes types of slow learners and suggests practical approaches for their educational problems. Slow learning and its types are defined; the slow learner is characterized; stages of educational evaluation and aspects of administration are outlined. Curriculum considerations for different levels are described,…
Approaches to Learning Information Literacy: A Phenomenographic Study
ERIC Educational Resources Information Center
Diehm, Rae-Anne; Lupton, Mandy
2012-01-01
This paper reports on an empirical study that explores the ways students approach learning to find and use information. Based on interviews with 15 education students in an Australian university, this study uses phenomenography as its methodological and theoretical basis. The study reveals that students use three main strategies for learning…
Challenges to a Learning Approach through a Global Network.
ERIC Educational Resources Information Center
Lee, In-Sook
Computer networking is a new educational approach that can well serve the educational needs in a society of dynamic and constant changes. This paper examines effective ways of establishing a computer network-based learning system in the Korean educational system. The Korean Educational Development Institute (KEDI) conducted a one-year research…
Learning Outcomes of Two Approaches to Multicultural Music Education
ERIC Educational Resources Information Center
Abril, Carlos R.
2006-01-01
The purpose of this study was to examine the effect of multicultural music instruction on classroom learning outcomes. Fifth-grade children (10-11 years of age; N = 170) from four schools were randomly assigned to one of two instructional treatments: music concept and sociocultural context. The former approach used formal elements of music as a…
Evaluating Action Learning: A Critical Realist Complex Network Theory Approach
ERIC Educational Resources Information Center
Burgoyne, John G.
2010-01-01
This largely theoretical paper will argue the case for the usefulness of applying network and complex adaptive systems theory to an understanding of action learning and the challenge it is evaluating. This approach, it will be argued, is particularly helpful in the context of improving capability in dealing with wicked problems spread around…
Understanding the Science-Learning Environment: A Genetically Sensitive Approach
ERIC Educational Resources Information Center
Haworth, Claire M. A.; Davis, Oliver S. P.; Hanscombe, Ken B.; Kovas, Yulia; Dale, Philip S.; Plomin, Robert
2013-01-01
Previous studies have shown that environmental influences on school science performance increase in importance from primary to secondary school. Here we assess for the first time the relationship between the science-learning environment and science performance using a genetically sensitive approach to investigate the aetiology of this link. 3000…
A Multiple Cross-Cultural Comparison of Approaches to Learning
ERIC Educational Resources Information Center
Bowden, Mark P.; Abhayawansa, Subhash; Manzin, Gregoria
2015-01-01
This study compares learning approaches of local English-speaking students and students from Asian countries studying at an Australian metropolitan university. The sample consists of students across 13 different countries. Unlike previous studies, students from Asian countries are subdivided into two categories: students from Confucian Heritage…
Students Approach to Learning and Their Use of Lecture Capture
ERIC Educational Resources Information Center
Vajoczki, Susan; Watt, Susan; Marquis, Nick; Liao, Rose; Vine, Michelle
2011-01-01
This study examined lecture capture as a way of enhancing university education, and explored how students with different learning approaches used lecture capturing (i.e., podcasts and vodcasts). Results indicate that both deep and surface learners report increased course satisfaction and better retention of knowledge in courses with traditional…
Cognitive Ability, Learning Approaches and Personality Correlates of General Knowledge
ERIC Educational Resources Information Center
Furnham, Adrian; Swami, Viren; Arteche, Adriane; Chamorro-Premuzic, Tomas
2008-01-01
The relationship between general knowledge (GK) and cognitive ability (IQ and abstract reasoning), learning approaches, and personality ("big five" traits and typical intellectual engagement) was investigated in a sample of 101 British undergraduates. As predicted, GK was positively correlated with cognitive ability (more so with IQ than with…
Ahkwesahsne Science & Math Pilot Project: A Native Approach to Learning.
ERIC Educational Resources Information Center
Wendt, Kim, Comp.
1995-01-01
Describes a science and math pilot project developed for Mohawk junior high school students in Ahkwesahsne (Canada) that integrates Iroquois culture with Western approaches to learning science. Curriculum units are based on the Mohawk Thanksgiving Address that acknowledges all aspects of life. Includes a passage examining differences between…
Learning Strategies and Study Approaches of Postsecondary Students with Dyslexia
ERIC Educational Resources Information Center
Kirby, John R.; Silvestri, Robert; Allingham, Beth H.; Parrila, Rauno; La Fave, Chantal B.
2008-01-01
The present study describes the self-reported learning strategies and study approaches of college and university students with and without dyslexia and examines the relationship of those characteristics with reading ability. Students with (n = 36) and without (n = 66) dyslexia completed tests measuring reading rate, reading comprehension, reading…
Evaluation Theory in Problem-Based Learning Approach.
ERIC Educational Resources Information Center
Hsu, Yu-chen
The purpose of this paper is to review evaluation theories and techniques in both the medical and educational fields and to propose an evaluation theory to explain the condition variables, the method variables, and the outcome variables of student assessment in a problem-based learning (PBL) approach. The PBL definition and process are presented,…
Enhancing the Scholarship of Teaching and Learning: An Organic Approach
ERIC Educational Resources Information Center
Adcroft, Andy; Lockwood, Andrew
2010-01-01
The aim of this paper is to report on an experiment in the School of Management at the University of Surrey whereby the Scholarship of Teaching and Learning is being promoted through an approach which is organic in nature. The paper argues that the nature of such scholarship means that its promotion is more likely to be successful when the…
Can Virtual Museums Motivate Students? Toward a Constructivist Learning Approach
ERIC Educational Resources Information Center
Katz, James E.; Halpern, Daniel
2015-01-01
This study aims to assess the effectiveness of immersive environments that have been implemented by museums to attract new visitors. Based on the frameworks introduced by telepresence and media richness theories, and following a constructivist-based learning approach, we argue that the greater the similarity of an online museum experience is to…
Re"modeling" College Algebra: An Active Learning Approach
ERIC Educational Resources Information Center
Pinzon, D.; Pinzon, K.; Stackpole, M.
2016-01-01
In this paper, we discuss active learning in College Algebra at Georgia Gwinnett College. This approach has been used in more than 20 sections of College Algebra taught by the authors in the past four semesters. Students work in small, structured groups on guided inquiry activities after watching 15-20 minutes of videos before class. We discuss a…
A Problem-Based Learning Approach to Entrepreneurship Education
ERIC Educational Resources Information Center
Tan, Siok San; Ng, C. K. Frank
2006-01-01
Purpose: While it is generally acknowledged that entrepreneurship can be taught, many differ in their opinions about the appropriate methodologies to teach and equip students with the requisite entrepreneurial skills. This paper presents a case to suggest that a problem-based learning (PBL) approach practised at the Republic Polytechnic in…
Human Resource Building--An Approach to Service Learning
ERIC Educational Resources Information Center
Rajan, Sonika
2009-01-01
Background: Isabella Thoburn College at Lucknow, Uttar Pradesh, India has initiated Service Learning Program for its students through 4 issue based centers. One of the centers AIDS Awareness Center for Counseling, Education, and Training (AACCET) is in the field of HIV/AIDS. It follows 6 pronged approach to achieve its objectives and one of the…
Developing a Student-Centered Approach to Reflective Learning.
ERIC Educational Resources Information Center
Stefani, Lorraine A. J.; Clarke, Joe; Littlejohn, Allison H.
2000-01-01
Presents a student-centered approach to reflective learning through a partnership between disciplinary-based academic staff and educational development staff members in a postgraduate Environmental Engineering Postgraduate Diploma/MSc program at the University of Strathclyde. Students were encouraged to maintain project management logbooks to…
Using an Active-Learning Approach to Teach Epigenetics
ERIC Educational Resources Information Center
Colon-Berlingeri, Migdalisel
2010-01-01
Epigenetics involves heritable changes in gene expression that do not involve alterations in the DNA sequence. I developed an active-learning approach to convey this topic to students in a college genetics course. I posted a brief summary of the topic before class to stimulate exchange in cooperative groups. During class, we discussed the…
Blended University Teaching Using Virtual Learning Environments: Conceptions and Approaches
ERIC Educational Resources Information Center
Lameras, Petros; Levy, Philippa; Paraskakis, Iraklis; Webber, Sheila
2012-01-01
This paper reports findings from a phenomenographic investigation into blended university teaching using virtual learning environments (VLEs). Interviews with 25 Computer Science teachers in Greek universities illuminated a spectrum of teachers' conceptions and approaches from "teacher-focused and content-oriented", through "student-focused and…
Mathematical Critical Thinking Ability through Contextual Teaching and Learning Approach
ERIC Educational Resources Information Center
Kurniati; Kusumah, Yaya S.; Sabandar, Jozua; Herman, Tatang
2015-01-01
This research aimed to examine the effect of the application of contextual teaching and learning (CTL) approach to the enhance of mathematical critical thinking ability (MCTA) of Primary School Teacher Students (PSTS). This research is an experimental study with the population of all students PSTS who took algebra subject matter of one university…
Transferring Knowledge across Cultures: A Learning Competencies Approach
ERIC Educational Resources Information Center
Kayes, Anna B.; Kayes, D. Christopher; Yamazaki, Yoshitaka
2005-01-01
At the heart of any successful cross-cultural knowledge transfer effort lies an individual or group of individuals with the skills to manage a complex, ambiguous and often stressful process. The ability to manage the knowledge transfer process depends as much on learning in real time as it does on rational planning. Yet, few approaches to…
Teacher Training Resource Handbook: Innovative Approach to Teaching and Learning.
ERIC Educational Resources Information Center
Namathaka, Lester; Kalulu, Master; Malisawa, Andrew; Mhoni, Sophie; Kabuwe, Enock; Kasitomu, Helix; Mhura, Hastings; Namachapa, Arton
This manual provides a tool for training community-based primary school teachers with a focus on a child-centered approach. There are 34 sections: (1) "Who an Affective Teacher Is"; (2) "How Children Learn"; (3) "Schemes of Work" and "Records of Work"; (4) "The Lesson"; (5) "Lesson Plan"; (6) "Effective Methods of Teaching"; (7) "Effective…
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
Modeling Second-Order Chemical Reactions using Cellular Automata
NASA Astrophysics Data System (ADS)
Hunter, N. E.; Barton, C. C.; Seybold, P. G.; Rizki, M. M.
2012-12-01
Cellular automata (CA) are discrete, agent-based, dynamic, iterated, mathematical computational models used to describe complex physical, biological, and chemical systems. Unlike the more computationally demanding molecular dynamics and Monte Carlo approaches, which use "force fields" to model molecular interactions, CA models employ a set of local rules. The traditional approach for modeling chemical reactions is to solve a set of simultaneous differential rate equations to give deterministic outcomes. CA models yield statistical outcomes for a finite number of ingredients. The deterministic solutions appear as limiting cases for conditions such as a large number of ingredients or a finite number of ingredients and many trials. Here we present a 2-dimensional, probabilistic CA model of a second-order gas phase reaction A + B → C, using a MATLAB basis. Beginning with a random distribution of ingredients A and B, formation of C emerges as the system evolves. The reaction rate can be varied based on the probability of favorable collisions of the reagents A and B. The model permits visualization of the conversion of reagents to products, and allows one to plot concentration vs. time for A, B and C. We test hypothetical reaction conditions such as: limiting reagents, the effects of reaction probabilities, and reagent concentrations on the reaction kinetics. The deterministic solutions of the reactions emerge as statistical averages in the limit of the large number of cells in the array. Modeling results for dynamic processes in the atmosphere will be presented.
Learning about knowledge: A complex network approach
NASA Astrophysics Data System (ADS)
da Fontoura Costa, Luciano
2006-08-01
An approach to modeling knowledge acquisition in terms of walks along complex networks is described. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchical networks—i.e., networks composed of successive interconnected layers—are related to compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks—i.e., unreachable nodes—the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barabási-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaus of knowledge stagnation in the case of the preferential movement strategy in the presence of conditional edges.
A hybrid learning approach for better recognition of visual objects
Imam, I.F.; Gutta, S.
1996-12-31
Real world images often contain similar objects but with different rotations, noise, or other visual alterations. Vision systems should be able to recognize objects regardless of these visual alterations. This paper presents a novel approach for learning optimized structures of classifiers for recognizing visual objects regardless of certain types of visual alterations. The approach consists of two phases. The first phase is concerned with learning classifications of a set of standard and altered objects. The second phase is concerned with discovering an optimized structure of classifiers for recognizing objects from unseen images. This paper presents an application of this approach to a domain of 15 classes of hand gestures. The experimental results show significant improvement in the recognition rate rather than using a single classifier or multiple classifiers with thresholds.
Explanatory approach for evaluation of machine learning-induced knowledge.
Zorman, Milan; Verlic, M
2009-01-01
Progress in biomedical research has resulted in an explosive growth of data. Use of the world wide web for sharing data has opened up possibilities for exhaustive data mining analysis. Symbolic machine learning approaches used in data mining, especially ensemble approaches, produce large sets of patterns that need to be evaluated. Manual evaluation of all patterns by a human expert is almost impossible. We propose a new approach to the evaluation of machine learning-induced knowledge by introducing a pre-evaluation step. Pre-evaluation is the automatic evaluation of patterns obtained from the data mining phase, using text mining techniques and sentiment analysis. It is used as a filter for patterns according to the support found in online resources, such as publicly-available repositories of scientific papers and reports related to the problem. The domain expert can then more easily distinguish between patterns or rules that are potential candidates for new knowledge. PMID:19930862
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…
An Approach for Learning Expressive Ontologies in Medical Domain.
Rios-Alvarado, Ana B; Lopez-Arevalo, Ivan; Tello-Leal, Edgar; Sosa-Sosa, Victor J
2015-08-01
The access to medical information (journals, blogs, web-pages, dictionaries, and texts) has been increased due to availability of many digital media. In particular, finding an appropriate structure that represents the information contained in texts is not a trivial task. One of the structures for modeling the knowledge are ontologies. An ontology refers to a conceptualization of a specific domain of knowledge. Ontologies are especially useful because they support the exchange and sharing of information as well as reasoning tasks. The usage of ontologies in medicine is mainly focussed in the representation and organization of medical terminologies. Ontology learning techniques have emerged as a set of techniques to get ontologies from unstructured information. This paper describes a new ontology learning approach that consists of a method for the acquisition of concepts and its corresponding taxonomic relations, where also axioms disjointWith and equivalentClass are learned from text without human intervention. The source of knowledge involves files about medical domain. Our approach is divided into two stages, the first part corresponds to discover hierarchical relations and the second part to the axiom extraction. Our automatic ontology learning approach shows better results compared against previous work, giving rise to more expressive ontologies. PMID:26077127
Theoretical description of teaching-learning processes: a multidisciplinary approach.
Bordogna, C M; Albano, E V
2001-09-10
A multidisciplinary approach based on concepts from sociology, educational psychology, statistical physics, and computational science is developed for the theoretical description of teaching-learning processes that take place in the classroom. The emerging model is consistent with well-established empirical results, such as the higher achievements reached working in collaborative groups and the influence of the structure of the group on the achievements of the individuals. Furthermore, another social learning process that takes place in massive interactions among individuals via the Internet is also investigated. PMID:11531550
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.
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…
Machine learning approach for objective inpainting quality assessment
NASA Astrophysics Data System (ADS)
Frantc, V. A.; Voronin, V. V.; Marchuk, V. I.; Sherstobitov, A. I.; Agaian, S.; Egiazarian, K.
2014-05-01
This paper focuses on a machine learning approach for objective inpainting quality assessment. Inpainting has received a lot of attention in recent years and quality assessment is an important task to evaluate different image reconstruction approaches. Quantitative metrics for successful image inpainting currently do not exist; researchers instead are relying upon qualitative human comparisons in order to evaluate their methodologies and techniques. We present an approach for objective inpainting quality assessment based on natural image statistics and machine learning techniques. Our method is based on observation that when images are properly normalized or transferred to a transform domain, local descriptors can be modeled by some parametric distributions. The shapes of these distributions are different for noninpainted and inpainted images. Approach permits to obtain a feature vector strongly correlated with a subjective image perception by a human visual system. Next, we use a support vector regression learned on assessed by human images to predict perceived quality of inpainted images. We demonstrate how our predicted quality value repeatably correlates with a qualitative opinion in a human observer study.
Using Cellular Automata for Parking Recommendations in Smart Environments
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
Epileptic spike recognition in electroencephalogram using deterministic finite automata.
Keshri, Anup Kumar; Sinha, Rakesh Kumar; Hatwal, Rajesh; Das, Barda Nand
2009-06-01
This Paper presents an automated method of Epileptic Spike detection in Electroencephalogram (EEG) using Deterministic Finite Automata (DFA). It takes prerecorded single channel EEG data file as input and finds the occurrences of Epileptic Spikes data in it. The EEG signal was recorded at 256 Hz in two minutes separate data files using the Visual Lab-M software (ADLink Technology Inc., Taiwan). It was preprocessed for removal of baseline shift and band pass filtered using an infinite impulse response (IIR) Butterworth filter. A system, whose functionality was modeled with DFA, was designed. The system was tested with 10 EEG signal data files. The recognition rate of Epileptic Spike as on average was 95.68%. This system does not require any human intrusion. Also it does not need any short of training. The result shows that the application of DFA can be useful in detection of different characteristics present in EEG signals. This approach could be extended to a continuous data processing system. PMID:19408450
Using cellular automata for parking recommendations in smart environments.
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
Some properties of the floor field cellular automata evacuation model
NASA Astrophysics Data System (ADS)
Gwizdałła, Tomasz M.
2015-02-01
We study the process of evacuation of pedestrians from the room with the given arrangement of doors and obstacles by using the cellular automata technique. The technique which became quite popular is characterized by the discretization of time as well as space. For such a discretized space we use so-called floor field model which generally corresponds to the description of every cell by some monotonic function of distance between this cell and the closest exit. We study several types of effects. We start from some general features of model like the kind of a neighborhood or the factors disrupting the motion. Then we analyze the influence of asymmetry and size on the evacuation time. Finally we show characteristics concerning different arrangements of exits and include a particular approach to the proxemics effects. The scaling analyses help us to distinguish these cases which just reflect the geometry of the system and those which depend also on the simulation properties. All calculations are performed for a wide range of initial densities corresponding to different occupation rates as described by the typical crowd counting techniques.
Revising a design course from a lecture approach to a project-based learning approach
NASA Astrophysics Data System (ADS)
Kunberger, Tanya
2013-06-01
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 focuses on the process rather than the result and underscores not only the theoretical but also the practical constraints of a problem. The shift in course emphasis, to skills over concepts, results in reduced content coverage but increased student ability to independently acquire a breadth of knowledge.
The Epistemological Beliefs, Learning Approaches and Study Orchestrations of University Students
ERIC Educational Resources Information Center
Rodriguez, Lourdes; Cano, Francisco
2006-01-01
This study examined the learning experience (learning approaches, study orchestrations and epistemological beliefs) of 388 university students. Data analysis revealed two main results. First, the different aspects of students' learning experience were related: learning approaches and epistemological beliefs (two pairs of canonical variates…
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…
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…
A reinforcement learning approach to gait training improves retention
Hasson, Christopher J.; Manczurowsky, Julia; Yen, Sheng-Che
2015-01-01
Many gait training programs are based on supervised learning principles: an individual is guided towards a desired gait pattern with directional error feedback. While this results in rapid adaptation, improvements quickly disappear. This study tested the hypothesis that a reinforcement learning approach improves retention and transfer of a new gait pattern. The results of a pilot study and larger experiment are presented. Healthy subjects were randomly assigned to either a supervised group, who received explicit instructions and directional error feedback while they learned a new gait pattern on a treadmill, or a reinforcement group, who was only shown whether they were close to or far from the desired gait. Subjects practiced for 10 min, followed by immediate and overnight retention and over-ground transfer tests. The pilot study showed that subjects could learn a new gait pattern under a reinforcement learning paradigm. The larger experiment, which had twice as many subjects (16 in each group) showed that the reinforcement group had better overnight retention than the supervised group (a 32% vs. 120% error increase, respectively), but there were no differences for over-ground transfer. These results suggest that encouraging participants to find rewarding actions through self-guided exploration is beneficial for retention. PMID:26379524
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
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.
ERIC Educational Resources Information Center
Çolak, Esma
2015-01-01
Problem Statement: For this study, a cooperative learning process was designed in which students with different learning styles could help each other in heterogeneous groups to perform teamwork-based activities. One aspect deemed important in this context was whether the instructional environment designed to reach students with different learning…
Computing cellular automata spectra under fixed boundary conditions via limit graphs
NASA Astrophysics Data System (ADS)
Ruivo, Eurico L. P.; de Oliveira, Pedro P. B.
2016-01-01
Cellular automata are fully discrete complex systems with parallel and homogeneous behavior studied both from the theoretical and modeling viewpoints. The limit behaviors of such systems are of particular interest, as they give insight into their emerging properties. One possible approach to investigate such limit behaviors is the analysis of the growth of graphs describing the finite time behavior of a rule in order to infer its limit behavior. Another possibility is to study the Fourier spectrum describing the average limit configurations obtained by a rule. While the former approach gives the characterization of the limit configurations of a rule, the latter yields a qualitative and quantitative characterisation of how often particular blocks of states are present in these limit configurations. Since both approaches are closely related, it is tempting to use one to obtain information about the other. Here, limit graphs are automatically adjusted by configurations directly generated by their respective rules, and use the graphs to compute the spectra of their rules. We rely on a set of elementary cellular automata rules, on lattices with fixed boundary condition, and show that our approach is a more reliable alternative to a previously described method from the literature.
A Self-Regulated Learning Approach for Children with Learning/Behavior Disorders
ERIC Educational Resources Information Center
Benevento, Joan A.
2004-01-01
This book is designed to be an intervention model based on the concepts of Piaget's study of constructivism. The application of this approach will help children with learning/ behavioral disorders actively participate in a fuller integration of their own psychomotor, affective, and cognitive information processing skills and adaptation. The work…
ERIC Educational Resources Information Center
McKay-Jackson, Cassandra
2014-01-01
The traditional teaching of reading, writing, and arithmetic alone will not fully prepare students to lead with integrity, govern fairly, analyze problems, and work collectively with people different from themselves. Social emotional learning (SEL) has been described as one of the missing links in academic education, but a restrictive approach to…
ERIC Educational Resources Information Center
Park, Jiyeon; Jeon, Dongryul
2015-01-01
The systemizing and empathizing brain type represent two contrasted students' characteristics. The present study investigated differences in the conceptions and approaches to learning science between the systemizing and empathizing brain type students. The instruments are questionnaires on the systematizing and empathizing, questionnaires on the…
Relations between Students' Approaches to Learning, Experienced Emotions and Outcomes of Learning
ERIC Educational Resources Information Center
Trigwell, Keith; Ellis, Robert A.; Han, Feifei
2012-01-01
Quantitative analyses conducted on the self-reports of first year university students suggest that there is a relationship between the ways they emotionally experience their course and the approach they take to the learning of that course. Students who more strongly experience positive emotions, such as hope and pride, and more weakly experience…
ERIC Educational Resources Information Center
Baeten, Marlies; Dochy, Filip; Struyven, Katrien
2008-01-01
This study focused on the relationships between experiences with portfolio assessment, students' approaches to learning and their assessment preferences by means of a pre- and post-test design in an authentic class setting. The participants were 138 first-year professional bachelor's degree students in office management. They were assessed by…
ERIC Educational Resources Information Center
Micari, Marina; Light, Gregory
2009-01-01
The phenomenographic "approach to learning" literature holds that students' approaches to learning can change depending on the learning context. This implies that, by modifying the learning context, teachers can change the way students approach learning, and this can ultimately lead to a change in learning outcomes. The study presented here…
Unstable vicinal crystal growth from cellular automata
NASA Astrophysics Data System (ADS)
Krasteva, A.; Popova, H.; KrzyŻewski, F.; Załuska-Kotur, M.; Tonchev, V.
2016-03-01
In order to study the unstable step motion on vicinal crystal surfaces we devise vicinal Cellular Automata. Each cell from the colony has value equal to its height in the vicinal, initially the steps are regularly distributed. Another array keeps the adatoms, initially distributed randomly over the surface. The growth rule defines that each adatom at right nearest neighbor position to a (multi-) step attaches to it. The update of whole colony is performed at once and then time increases. This execution of the growth rule is followed by compensation of the consumed particles and by diffusional update(s) of the adatom population. Two principal sources of instability are employed - biased diffusion and infinite inverse Ehrlich-Schwoebel barrier (iiSE). Since these factors are not opposed by step-step repulsion the formation of multi-steps is observed but in general the step bunches preserve a finite width. We monitor the developing surface patterns and quantify the observations by scaling laws with focus on the eventual transition from diffusion-limited to kinetics-limited phenomenon. The time-scaling exponent of the bunch size N is 1/2 for the case of biased diffusion and 1/3 for the case of iiSE. Additional distinction is possible based on the time-scaling exponents of the sizes of multi-step Nmulti, these are 0.36÷0.4 (for biased diffusion) and 1/4 (iiSE).
Quantum Features of Natural Cellular Automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
We review the properties of discrete and integer-valued, hence "natural", cellular automata (CA), a particular class of which comprises "Hamiltonian CA" with equations of motion that bear strong similarities to Hamilton's equations, despite presenting discrete updating rules. The resulting dynamics is linear in the same sense as unitary evolution described by the Schrödinger equation. Employing Shannon's Sampling Theorem, we construct an invertible map between such CA and continuous quantum mechanical models which incorporate a fundamental discreteness scale. This leads to one-to-one correspondence of quantum mechanical and CA conservation laws. In order to illuminate the all-important issue of linearity, we presently introduce an extension of the class of CA incorporating nonlinearities. We argue that these imply non-local effects in the continuous quantum mechanical description of intrinsically local discrete CA, enforcing locality entails linearity. We recall the construction of admissible CA observables and the existence of solutions of the modified dispersion relation for stationary states, besides discussing next steps of the deconstruction of quantum mechanical models in terms of deterministic CA.
ERIC Educational Resources Information Center
Beausaert, Simon A. J.; Segers, M. S. R; Wiltink, Danique P. A.
2013-01-01
Background: Research on the relation between teaching and learning approaches has been mainly conducted in higher education and it is not yet clear to what extent the results can be generalised when it comes to secondary education. Purpose: The purpose of this study was to research how students in secondary education perceive their teachers'…
Evaluation of students' perception of their learning environment and approaches to learning
NASA Astrophysics Data System (ADS)
Valyrakis, Manousos; Cheng, Ming
2015-04-01
This work presents the results of two case studies designed to assess the various approaches undergraduate and postgraduate students undertake for their education. The first study describes the results and evaluation of an undergraduate course in Water Engineering which aims to develop the fundamental background knowledge of students on introductory practical applications relevant to the practice of water and hydraulic engineering. The study assesses the effectiveness of the course design and learning environment from the perception of students using a questionnaire addressing several aspects that may affect student learning, performance and satisfaction, such as students' motivation, factors to effective learning, and methods of communication and assessment. The second study investigates the effectiveness of supervisory arrangements based on the perceptions of engineering undergraduate and postgraduate students. Effective supervision requires leadership skills that are not taught in the University, yet there is rarely a chance to get feedback, evaluate this process and reflect. Even though the results are very encouraging there are significant lessons to learn in improving ones practice and develop an effective learning environment to student support and guidance. The findings from these studies suggest that students with high level of intrinsic motivation are deep learners and are also top performers in a student-centered learning environment. A supportive teaching environment with a plethora of resources and feedback made available over different platforms that address students need for direct communication and feedback has the potential to improve student satisfaction and their learning experience. Finally, incorporating a multitude of assessment methods is also important in promoting deep learning. These results have deep implications about student learning and can be used to further improve course design and delivery in the future.
Dynamic behavior of multirobot systems using lattice gas automata
NASA Astrophysics Data System (ADS)
Stantz, Keith M.; Cameron, Stewart M.; Robinett, Rush D., III; Trahan, Michael W.; Wagner, John S.
1999-07-01
Recent attention has been given to the deployment of an adaptable sensor array realized by multi-robotic systems (or swarms). Our group has been studying the collective, autonomous behavior of these such systems and their applications in the area of remote-sensing and emerging threats. To accomplish such tasks, an interdisciplinary research effort at Sandia National Laboratories are conducting tests in the fields of sensor technology, robotics, and multi- agents architectures. Our goal is to coordinate a constellation of point sensors using unmanned robotic vehicles (e.g., RATLERs, Robotic All-Terrain Lunar Exploration Rover- class vehicles) that optimizes spatial coverage and multivariate signal analysis. An overall design methodology evolves complex collective behaviors realized through local interaction (kinetic) physics and artificial intelligence. Learning objectives incorporate real-time operational responses to environmental changes. This paper focuses on our recent work understanding the dynamics of many-body systems according to the physics-based hydrodynamic model of lattice gas automata. Three design features are investigated. One, for single-speed robots, a hexagonal nearest-neighbor interaction topology is necessary to preserve standard hydrodynamic flow. Two, adaptability, defined by the swarm's rate of deformation, can be controlled through the hydrodynamic viscosity term, which, in turn, is defined by the local robotic interaction rules. Three, due to the inherent nonlinearity of the dynamical equations describing large ensembles, stability criteria ensuring convergence to equilibrium states is developed by scaling information flow rates relative to a swarm's hydrodynamic flow rate. An initial test case simulates a swarm of twenty-five robots maneuvering past an obstacle while following a moving target. A genetic algorithm optimizes applied nearest-neighbor forces in each of five spatial regions distributed over the simulation domain. Armed with
Lempel-Ziv complexity analysis of one dimensional cellular automata.
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. PMID:26723145
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.
Icing detection from geostationary satellite data using machine learning approaches
NASA Astrophysics Data System (ADS)
Lee, J.; Ha, S.; Sim, S.; Im, J.
2015-12-01
Icing can cause a significant structural damage to aircraft during flight, resulting in various aviation accidents. Icing studies have been typically performed using two approaches: one is a numerical model-based approach and the other is a remote sensing-based approach. The model based approach diagnoses aircraft icing using numerical atmospheric parameters such as temperature, relative humidity, and vertical thermodynamic structure. This approach tends to over-estimate icing according to the literature. The remote sensing-based approach typically uses meteorological satellite/ground sensor data such as Geostationary Operational Environmental Satellite (GOES) and Dual-Polarization radar data. This approach detects icing areas by applying thresholds to parameters such as liquid water path and cloud optical thickness derived from remote sensing data. In this study, we propose an aircraft icing detection approach which optimizes thresholds for L1B bands and/or Cloud Optical Thickness (COT) from Communication, Ocean and Meteorological Satellite-Meteorological Imager (COMS MI) and newly launched Himawari-8 Advanced Himawari Imager (AHI) over East Asia. The proposed approach uses machine learning algorithms including decision trees (DT) and random forest (RF) for optimizing thresholds of L1B data and/or COT. Pilot Reports (PIREPs) from South Korea and Japan were used as icing reference data. Results show that RF produced a lower false alarm rate (1.5%) and a higher overall accuracy (98.8%) than DT (8.5% and 75.3%), respectively. The RF-based approach was also compared with the existing COMS MI and GOES-R icing mask algorithms. The agreements of the proposed approach with the existing two algorithms were 89.2% and 45.5%, respectively. The lower agreement with the GOES-R algorithm was possibly due to the high uncertainty of the cloud phase product from COMS MI.
A Blended Learning Approach to Course Design and Implementation
ERIC Educational Resources Information Center
Hoic-Bozic, N.; Mornar, V.; Boticki, I.
2009-01-01
Blended learning has become an increasingly popular form of e-learning, and is particularly suitable to the process of transitioning towards e-learning from traditional forms of learning and teaching. This paper describes the use of the blended e-learning model, which is based on a mixture of collaborative learning, problem-based learning (PBL)…
Podlesnik, Christopher A.; Sanabria, Federico
2016-01-01
We assessed the effects of repeated extinction and reversals of two conditional stimuli (CS+/CS−) on an appetitive conditioned approach response in rats. Three results were observed that could not be accounted for by a simple linear operator model such as the one proposed by Rescorla and Wagner (1972): (1) responding to a CS− declined faster when a CS+ was simultaneously extinguished; (2) reacquisition of pre-extinction performance recovered rapidly within one session; and (3) reversal of CS+/CS− contingencies resulted in a more rapid recovery to the current CS− (former CS+) than the current CS+, accompanied by a slower acquisition of performance to the current CS+. An arousal parameter that mediates learning was introduced to a linear operator model to account for these effects. The arousal-mediated learning model adequately fit the data and predicted data from a second experiment with different rats in which only repeated reversals of CS+/CS− were assessed. According to this arousal-mediated learning model, learning is accelerated by US-elicited arousal and it slows down in the absence of US. Because arousal varies faster than conditioning, the model accounts for the decline in responding during extinction mainly through a reduction in arousal, not a change in learning. By preserving learning during extinction, the model is able to account for relapse effects like rapid reacquisition, renewal, and reinstatement. PMID:21172410
Podlesnik, Christopher A; Sanabria, Federico
2011-05-01
We assessed the effects of repeated extinction and reversals of two conditional stimuli (CS+/CS-) on an appetitive conditioned approach response in rats. Three results were observed that could not be accounted for by a simple linear operator model such as the one proposed by Rescorla and Wagner (1972): (1) responding to a CS- declined faster when a CS+ was simultaneously extinguished; (2) reacquisition of pre-extinction performance recovered rapidly within one session; and (3) reversal of CS+/CS- contingencies resulted in a more rapid recovery to the current CS- (former CS+) than the current CS+, accompanied by a slower acquisition of performance to the current CS+. An arousal parameter that mediates learning was introduced to a linear operator model to account for these effects. The arousal-mediated learning model adequately fit the data and predicted data from a second experiment with different rats in which only repeated reversals of CS+/CS- were assessed. According to this arousal-mediated learning model, learning is accelerated by US-elicited arousal and it slows down in the absence of US. Because arousal varies faster than conditioning, the model accounts for the decline in responding during extinction mainly through a reduction in arousal, not a change in learning. By preserving learning during extinction, the model is able to account for relapse effects like rapid reacquisition, renewal, and reinstatement. PMID:21172410
Controversial approaches to treating learning disabilities and attention deficit disorder.
Silver, L B
1986-10-01
It is estimated that between 3% and 7% of children and adolescents in this country--up to 4 million--are learning disabled. Of this group, about 20% also have attention deficit disorder. Many professionals in multiple disciplines have proposed treatment approaches. When research has been done to support the approach, the reports and data may be published in journals not normally read by the practicing physician. When research data are not available, the information may be in a popular book, newspapers, or lay magazines or on television. Thus, parents may know of ideas and suggestions before the professional in clinical practice. These acceptable and controversial approaches to treatment are reviewed. It is understandable that a parent would seek out improved ways of helping his or her child. I reviewed the significant literature in an effort to assist the practicing physician in providing appropriate parental guidance and clinical interventions. PMID:2875647
Learning the Task Management Space of an Aircraft Approach Model
NASA Technical Reports Server (NTRS)
Krall, Joseph; Menzies, Tim; Davies, Misty
2014-01-01
Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.
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.
Robust Orbit Determination and Classification: A Learning Theoretic Approach
NASA Astrophysics Data System (ADS)
Sharma, S.; Cutler, J. W.
2015-11-01
Orbit determination involves estimation of a non-linear mapping from feature vectors associated with the position of the spacecraft to its orbital parameters. The de facto standard in orbit determination in real-world scenarios for spacecraft has been linearized estimators such as the extended Kalman filter. Such an estimator, while very accurate and convergent over its linear region, is hard to generalize over arbitrary gravitational potentials and diverse sets of measurements. It is also challenging to perform exact mathematical characterizations of the Kalman filter performance over such general systems. Here we present a new approach to orbit determination as a learning problem involving distribution regression and, also, for the multiple-spacecraft scenario, a transfer learning system for classification of feature vectors associated with spacecraft, and provide some associated analysis of such systems.
Ensemble Learning Approaches to Predicting Complications of Blood Transfusion
Murphree, Dennis; Ngufor, Che; Upadhyaya, Sudhindra; Madde, Nagesh; Clifford, Leanne; Kor, Daryl J.; Pathak, Jyotishman
2016-01-01
Of the 21 million blood components transfused in the United States during 2011, approximately 1 in 414 resulted in complication [1]. Two complications in particular, transfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO), are especially concerning. These two alone accounted for 62% of reported transfusion-related fatalities in 2013 [2]. We have previously developed a set of machine learning base models for predicting the likelihood of these adverse reactions, with a goal towards better informing the clinician prior to a transfusion decision. Here we describe recent work incorporating ensemble learning approaches to predicting TACO/TRALI. In particular we describe combining base models via majority voting, stacking of model sets with varying diversity, as well as a resampling/boosting combination algorithm called RUSBoost. We find that while the performance of many models is very good, the ensemble models do not yield significantly better performance in terms of AUC. PMID:26737958
Ensemble learning approaches to predicting complications of blood transfusion.
Murphree, Dennis; Ngufor, Che; Upadhyaya, Sudhindra; Madde, Nagesh; Clifford, Leanne; Kor, Daryl J; Pathak, Jyotishman
2015-08-01
Of the 21 million blood components transfused in the United States during 2011, approximately 1 in 414 resulted in complication [1]. Two complications in particular, transfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO), are especially concerning. These two alone accounted for 62% of reported transfusion-related fatalities in 2013 [2]. We have previously developed a set of machine learning base models for predicting the likelihood of these adverse reactions, with a goal towards better informing the clinician prior to a transfusion decision. Here we describe recent work incorporating ensemble learning approaches to predicting TACO/TRALI. In particular we describe combining base models via majority voting, stacking of model sets with varying diversity, as well as a resampling/boosting combination algorithm called RUSBoost. We find that while the performance of many models is very good, the ensemble models do not yield significantly better performance in terms of AUC. PMID:26737958
A verification strategy for web services composition using enhanced stacked automata model.
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
ERIC Educational Resources Information Center
Baeten, Marlies; Kyndt, Eva; Struyven, Katrien; Dochy, Filip
2010-01-01
This review outlines encouraging and discouraging factors in stimulating the adoption of deep approaches to learning in student-centred learning environments. Both encouraging and discouraging factors can be situated in the context of the learning environment, in students' perceptions of that context and in characteristics of the students…
ERIC Educational Resources Information Center
She, Hsiao-Ching
2005-01-01
This study investigates the potential of enhancing students' learning of difficult science concepts by exploring the interaction between teachers' four different instructional approaches and students' four different learning preference styles. Students' immediate performance and their retention for learning of buoyancy concepts serve to examine…
ERIC Educational Resources Information Center
Seddon, Frederick; Biasutti, Michele
2009-01-01
This study investigated the viability of learning to play an improvised 12-bar blues on keyboard with both hands together in an asynchronous e-learning environment. The study also sought to reveal participant approaches to and reflections on this learning experience. Participants were video-taped as they engaged with six "Blues Activities",…
ERIC Educational Resources Information Center
So, Hyo-Jeong; Bonk, Curtis J.
2010-01-01
In this study, a Delphi method was used to identify and predict the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments. The Delphi panel consisted of experts in online learning from different geographic regions of the world. This study discusses findings related to (a) pros and cons of blended…
ERIC Educational Resources Information Center
Chiou, Guo-Li; Lee, Min-Hsien; Tsai, Chin-Chung
2013-01-01
Background and purpose: Knowing how students learn physics is a central goal of physics education. The major purpose of this study is to examine the strength of the predictive power of students' epistemic views and conceptions of learning in terms of their approaches to learning in physics. Sample, design and method: A total of 279 Taiwanese high…
Machine learning: An artificial intelligence approach. Vol. II
Michalski, R.S.; Carbonell, J.G.; Mitchell, T.M.
1986-01-01
This book reflects the expansion of machine learning research through presentation of recent advances in the field. The book provides an account of current research directions. Major topics covered include the following: learning concepts and rules from examples; cognitive aspects of learning; learning by analogy; learning by observation and discovery; and an exploration of general aspects of learning.
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…
Perspective: Codesign for materials science: An optimal learning approach
NASA Astrophysics Data System (ADS)
Lookman, Turab; Alexander, Francis J.; Bishop, Alan R.
2016-05-01
A key element of materials discovery and design is to learn from available data and prior knowledge to guide the next experiments or calculations in order to focus in on materials with targeted properties. We suggest that the tight coupling and feedback between experiments, theory and informatics demands a codesign approach, very reminiscent of computational codesign involving software and hardware in computer science. This requires dealing with a constrained optimization problem in which uncertainties are used to adaptively explore and exploit the predictions of a surrogate model to search the vast high dimensional space where the desired material may be found.
ERIC Educational Resources Information Center
Missouri State Dept. of Elementary and Secondary Education, Jefferson City.
This document is comprised of four publications of the early childhood section of the Missouri Department of Elementary and Secondary Education: (1) prekindergarten standards related to social and emotional development and approaches to learning; (2) a teacher's guide to early social and emotional development and approaches to learning; (3) a…
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…
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…
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…
ERIC Educational Resources Information Center
Kotsopoulos, Donna; Makosz, Samantha; Zambrzycka, Joanna; McCarthy, Katharine
2015-01-01
This research investigated the effects of different pedagogical approaches on the learning of length measurement in kindergarten children. Specifically examined were the pedagogical approaches of guided instruction, center-based learning, and free exploration in the context of a play-based learning environment. This mixed design research was…
ERIC Educational Resources Information Center
Cormas, Peter C.
2016-01-01
Preservice teachers (N = 27) in two sections of a sequenced, methodological and process integrated mathematics/science course solved a levers problem with three similar learning processes and a problem-solving approach, and identified a problem-solving approach through one different learning process. Similar learning processes used included:…
ERIC Educational Resources Information Center
Dorça, Fabiano Azevedo; Lima, Luciano Vieira; Fernandes, Márcia Aparecida; Lopes, Carlos Roberto
2012-01-01
Considering learning and how to improve students' performances, an adaptive educational system must know how an individual learns best. In this context, this work presents an innovative approach for student modeling through probabilistic learning styles combination. Experiments have shown that our approach is able to automatically detect and…
What's Wrong with Learning for the Exam? An Assessment-Based Approach for Student Engagement
ERIC Educational Resources Information Center
Ito, Hiroshi
2014-01-01
It is now widely recognized that assessment and the feedback play key roles in the learning process. However, assessment-based learning approaches are not yet commonly practiced in Japan. This paper provides an example of an assessment-based approach to teaching and learning employed for a course entitled "English as an International…
A Concept Map Approach to Developing Collaborative Mindtools for Context-Aware Ubiquitous Learning
ERIC Educational Resources Information Center
Hwang, Gwo-Jen; Shi, Yen-Ru; Chu, Hui-Chun
2011-01-01
Recent advances in mobile and wireless communication technologies have enabled various new learning approaches which situate students in environments that combine real-world and digital-world learning resources; moreover, students are allowed to share knowledge or experiences with others during the learning process. Although such an approach seems…
Translational Approach to Behavioral Learning: Lessons from Cerebellar Plasticity
Cheron, Guy; Dan, Bernard; Márquez-Ruiz, Javier
2013-01-01
The role of cerebellar plasticity has been increasingly recognized in learning. The privileged relationship between the cerebellum and the inferior olive offers an ideal circuit for attempting to integrate the numerous evidences of neuronal plasticity into a translational perspective. The high learning capacity of the Purkinje cells specifically controlled by the climbing fiber represents a major element within the feed-forward and feedback loops of the cerebellar cortex. Reciprocally connected with the basal ganglia and multimodal cerebral domains, this cerebellar network may realize fundamental functions in a wide range of behaviors. This review will outline the current understanding of three main experimental paradigms largely used for revealing cerebellar functions in behavioral learning: (1) the vestibuloocular reflex and smooth pursuit control, (2) the eyeblink conditioning, and (3) the sensory envelope plasticity. For each of these experimental conditions, we have critically revisited the chain of causalities linking together neural circuits, neural signals, and plasticity mechanisms, giving preference to behaving or alert animal physiology. Namely, recent experimental approaches mixing neural units and local field potentials recordings have demonstrated a spike timing dependent plasticity by which the cerebellum remains at a strategic crossroad for deciphering fundamental and translational mechanisms from cellular to network levels. PMID:24319600
Modeling pedestrian behaviors under attracting incidents using cellular automata
NASA Astrophysics Data System (ADS)
Chen, Yanyan; Chen, Ning; Wang, Yang; Wang, Zhenbao; Feng, Guochen
2015-08-01
Compared to vehicular flow, pedestrian flow is more complicated as it is free from the restriction of the lane and more flexible. Due to the lack of modeling pedestrian behaviors under attracting incidents (incidents which attract pedestrians around to gather), this paper proposes a new cellular automata model aiming to reproduce the behaviors induced by such attracting incidents. When attracting incidents occur, the proposed model will classify pedestrians around the incidents into three groups: the "unaffected" type, the "stopped" type and the "onlooking" type. The "unaffected" type represents the pedestrians who are not interested in the attracting incidents and its dynamics are the same as that under normal circumstances which are the main target in the previous works. The "stopped" type represents the pedestrians are somewhat interested in the attracting incidents, but unwilling to move close to the venues. Its dynamics are determined by "stopped" utility which can make the pedestrians stop for a while. The "onlooking" type represents the pedestrians who show strong interest in the attracting incidents and intend to move close to the venues to gain more information. The "onlooking" pedestrians will take a series of reactions to attracting incidents, such as approaching to the venues, stopping and watching the attracting incidents, leaving the venues, which have all been considered in the proposed model. The simulation results demonstrate that the proposed model can capture the macro-characteristics of pedestrian traffic flow under normal circumstances and possesses the fundamental characteristics of the pedestrian behaviors under attracting incidents around which a torus-shaped crowd is typically formed.
Validating Cellular Automata Lava Flow Emplacement Algorithms with Standard Benchmarks
NASA Astrophysics Data System (ADS)
Richardson, J. A.; Connor, L.; Charbonnier, S. J.; Connor, C.; Gallant, E.
2015-12-01
A major existing need in assessing lava flow simulators is a common set of validation benchmark tests. We propose three levels of benchmarks which test model output against increasingly complex standards. First, imulated lava flows should be morphologically identical, given changes in parameter space that should be inconsequential, such as slope direction. Second, lava flows simulated in simple parameter spaces can be tested against analytical solutions or empirical relationships seen in Bingham fluids. For instance, a lava flow simulated on a flat surface should produce a circular outline. Third, lava flows simulated over real world topography can be compared to recent real world lava flows, such as those at Tolbachik, Russia, and Fogo, Cape Verde. Success or failure of emplacement algorithms in these validation benchmarks can be determined using a Bayesian approach, which directly tests the ability of an emplacement algorithm to correctly forecast lava inundation. Here we focus on two posterior metrics, P(A|B) and P(¬A|¬B), which describe the positive and negative predictive value of flow algorithms. This is an improvement on less direct statistics such as model sensitivity and the Jaccard fitness coefficient. We have performed these validation benchmarks on a new, modular lava flow emplacement simulator that we have developed. This simulator, which we call MOLASSES, follows a Cellular Automata (CA) method. The code is developed in several interchangeable modules, which enables quick modification of the distribution algorithm from cell locations to their neighbors. By assessing several different distribution schemes with the benchmark tests, we have improved the performance of MOLASSES to correctly match early stages of the 2012-3 Tolbachik Flow, Kamchakta Russia, to 80%. We also can evaluate model performance given uncertain input parameters using a Monte Carlo setup. This illuminates sensitivity to model uncertainty.
Is there a sharp phase transition for deterministic cellular automata
Wootters, W.K. Los Alamos National Lab., NM Williams Coll., Williamstown, MA . Dept. of Physics); Langton, C.G. )
1990-01-01
Previous work has suggested that there is a kind of phase transition between deterministic automata exhibiting periodic behavior and those exhibiting chaotic behavior. However, unlike the usual phase transitions of physics, this transition takes place over a range of values of the parameter rather than at a specific value. The present paper asks whether the transition can be made sharp, either by taking the limit of an infinitely large rule table, or by changing the parameter in terms of which the space of automata is explored. We find strong evidence that, for the class of automata we consider, the transition does become sharp in the limit of an infinite number of symbols, the size of the neighborhood being held fixed. Our work also suggests an alternative parameter in terms of which it is likely that the transition will become fairly sharp even if one does not increase the number of symbols. In the course of our analysis, we find that mean field theory, which is our main tool, gives surprisingly good predictions of the statistical properties of the class of automata we consider. 18 refs., 6 figs.
Comprehensive bidding strategies with genetic programming/finite state automata
Richter, C.W. Jr.; Sheble, G.B.; Ashlock, D.
1999-11-01
This research is an extension of the authors' previous work in double auctions aimed at developing bidding strategies for electric utilities which trade electricity competitively. The improvements detailed in this paper come from using data structures which combine genetic programming and finite state automata termed GP-Automata. The strategies developed by the method described here are adaptive--reacting to inputs--whereas the previously developed strategies were only suitable in the particular scenario for which they had been designed. The strategies encoded in the GP-Automata are tested in an auction simulator. The simulator pits them against other distribution companies (distcos) and generation companies (gencos), buying and selling power via double auctions implemented in regional commodity exchanges. The GP-Automata are evolved with a genetic algorithm so that they possess certain characteristics. In addition to designing successful bidding strategies (whose usage would result in higher profits) the resulting strategies can also be designed to imitate certain types of trading behaviors. The resulting strategies can be implemented directly in on-line trading, or can be used as realistic competitors in an off-line trading simulator.
On the Reversibility of 150 Wolfram Cellular Automata
NASA Astrophysics Data System (ADS)
Del Rey, A. Martín; Sánchez, G. Rodríguez
In this paper, the reversibility problem for 150 Wolfram cellular automata is tackled for null boundary conditions. It is explicitly shown that the reversibility depends on the number of cells of the cellular automaton. The inverse cellular automaton for each case is also computed.
Synchronization of One-Dimensional Stochastically Coupled Cellular Automata
NASA Astrophysics Data System (ADS)
Mrowinski, Maciej J.; Kosinski, Robert A.
In this work the authors study synchronization resulting from the asymmetric stochastic coupling between two one-dimensional chaotic cellular automata and provide a simple analytical model to explain this phenomenon. The authors also study synchronization in a more general case, using sets of rules with a different number of states and different values of Langton's parameter λ.
Knot invariants and the thermodynamics of lattice gas automata
Meyer, D.A.
1992-01-01
The goal of this project is to build on the understanding of the connections between knot invariants, exactly solvable statistical mechanics models and discrete dynamical systems that we have gained in earlier work, toward an answer to the question of how early and robust thermodynamic behavior appears in lattice gas automata.
Return of the Quantum Cellular Automata: Episode VI
NASA Astrophysics Data System (ADS)
Carr, Lincoln D.; Hillberry, Logan E.; Rall, Patrick; Halpern, Nicole Yunger; Bao, Ning; Montangero, Simone
2016-05-01
There are now over 150 quantum simulators or analog quantum computers worldwide. Although exploring quantum phase transitions, many-body localization, and the generalized Gibbs ensemble are exciting and worthwhile endeavors, there are totally untapped directions we have not yet pursued. One of these is quantum cellular automata. In the past a principal goal of quantum cellular automata was to reproduce continuum single particle quantum physics such as the Schrodinger or Dirac equation from simple rule sets. Now that we begin to really understand entanglement and many-body quantum physics at a deeper level, quantum cellular automata present new possibilities. We explore several time evolution schemes on simple spin chains leading to high degrees of quantum complexity and nontrivial quantum dynamics. We explain how the 256 known classical elementary cellular automata reduce to just a few exciting quantum cases. Our analysis tools include mutual information based complex networks as well as more familiar quantifiers like sound speed and diffusion rate. Funded by NSF and AFOSR.
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.
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)
An approach towards problem-based learning in virtual space
Freudenberg, Lutz S.; Bockisch, Andreas; Beyer, Thomas
2010-01-01
Problem-based learning (PBL) is an established and efficient approach to sustainable teaching. Here, we describe translation of PBL into the virtual classroom thereby offering novel teaching aspects in the field of Nuclear Medicine. Our teaching approach is implemented on a "moodle" platform and consists of 2 modules: complementary seminar teaching materials and a virtual PBL-classroom, which can be attended via Skype. Over the course of 4 semesters 539 students have accessed our teaching platform. 21 students have participated in the PBL seminar (module 2). After resolving some minor technical difficulties our virtual seminars have evolved into a forum of intense studies, whereby the participating students have learned to become more independent along the workup of the teaching cases. This was reflected in the results of the intra-group presentations and discussions. Quantitative and qualitative evaluation of our moodle-based PBL platform indicates an increasing level of acceptance and enthusiasm by the students. This has initiated discussions about opening our PBL concept to a wider audience within the university and beyond the Nuclear Medicine specialty. PMID:21818218
A learning-based approach for biomedical word sense disambiguation.
Al-Mubaid, Hisham; Gungu, Sandeep
2012-01-01
In the biomedical domain, word sense ambiguity is a widely spread problem with bioinformatics research effort devoted to it being not commensurate and allowing for more development. This paper presents and evaluates a learning-based approach for sense disambiguation within the biomedical domain. The main limitation with supervised methods is the need for a corpus of manually disambiguated instances of the ambiguous words. However, the advances in automatic text annotation and tagging techniques with the help of the plethora of knowledge sources like ontologies and text literature in the biomedical domain will help lessen this limitation. The proposed method utilizes the interaction model (mutual information) between the context words and the senses of the target word to induce reliable learning models for sense disambiguation. The method has been evaluated with the benchmark dataset NLM-WSD with various settings and in biomedical entity species disambiguation. The evaluation results showed that the approach is very competitive and outperforms recently reported results of other published techniques. PMID:22666174
Machine Learning Approaches: From Theory to Application in Schizophrenia
Veronese, Elisa; Castellani, Umberto; Peruzzo, Denis; Bellani, Marcella; Brambilla, Paolo
2013-01-01
In recent years, machine learning approaches have been successfully applied for analysis of neuroimaging data, to help in the context of disease diagnosis. We provide, in this paper, an overview of recent support vector machine-based methods developed and applied in psychiatric neuroimaging for the investigation of schizophrenia. In particular, we focus on the algorithms implemented by our group, which have been applied to classify subjects affected by schizophrenia and healthy controls, comparing them in terms of accuracy results with other recently published studies. First we give a description of the basic terminology used in pattern recognition and machine learning. Then we separately summarize and explain each study, highlighting the main features that characterize each method. Finally, as an outcome of the comparison of the results obtained applying the described different techniques, conclusions are drawn in order to understand how much automatic classification approaches can be considered a useful tool in understanding the biological underpinnings of schizophrenia. We then conclude by discussing the main implications achievable by the application of these methods into clinical practice. PMID:24489603
An active, collaborative approach to learning skills in flow cytometry.
Fuller, Kathryn; Linden, Matthew D; Lee-Pullen, Tracey; Fragall, Clayton; Erber, Wendy N; Röhrig, Kimberley J
2016-06-01
Advances in science education research have the potential to improve the way students learn to perform scientific interpretations and understand science concepts. We developed active, collaborative activities to teach skills in manipulating flow cytometry data using FlowJo software. Undergraduate students were given compensated clinical flow cytometry listmode output (FCS) files and asked to design a gating strategy to diagnose patients with different hematological malignancies on the basis of their immunophenotype. A separate cohort of research trainees was given uncompensated data files on which they performed their own compensation, calculated the antibody staining index, designed a sequential gating strategy, and quantified rare immune cell subsets. Student engagement, confidence, and perceptions of flow cytometry were assessed using a survey. Competency against the learning outcomes was assessed by asking students to undertake tasks that required understanding of flow cytometry dot plot data and gating sequences. The active, collaborative approach allowed students to achieve learning outcomes not previously possible with traditional teaching formats, for example, having students design their own gating strategy, without forgoing essential outcomes such as the interpretation of dot plots. In undergraduate students, favorable perceptions of flow cytometry as a field and as a potential career choice were correlated with student confidence but not the ability to perform flow cytometry data analysis. We demonstrate that this new pedagogical approach to teaching flow cytometry is beneficial for student understanding and interpretation of complex concepts. It should be considered as a useful new method for incorporating complex data analysis tasks such as flow cytometry into curricula. PMID:27068992
SAR imaging via iterative adaptive approach and sparse Bayesian learning
NASA Astrophysics Data System (ADS)
Xue, Ming; Santiago, Enrique; Sedehi, Matteo; Tan, Xing; Li, Jian
2009-05-01
We consider sidelobe reduction and resolution enhancement in synthetic aperture radar (SAR) imaging via an iterative adaptive approach (IAA) and a sparse Bayesian learning (SBL) method. The nonparametric weighted least squares based IAA algorithm is a robust and user parameter-free adaptive approach originally proposed for array processing. We show that it can be used to form enhanced SAR images as well. SBL has been used as a sparse signal recovery algorithm for compressed sensing. It has been shown in the literature that SBL is easy to use and can recover sparse signals more accurately than the l 1 based optimization approaches, which require delicate choice of the user parameter. We consider using a modified expectation maximization (EM) based SBL algorithm, referred to as SBL-1, which is based on a three-stage hierarchical Bayesian model. SBL-1 is not only more accurate than benchmark SBL algorithms, but also converges faster. SBL-1 is used to further enhance the resolution of the SAR images formed by IAA. Both IAA and SBL-1 are shown to be effective, requiring only a limited number of iterations, and have no need for polar-to-Cartesian interpolation of the SAR collected data. This paper characterizes the achievable performance of these two approaches by processing the complex backscatter data from both a sparse case study and a backhoe vehicle in free space with different aperture sizes.
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).
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
Wells, J.T. . Dept. of Geological Sciences); Janecky, D.R.; Travis, B.J. )
1990-01-15
A lattice gas automata (LGA) model is described, which couples solute transport with chemical reactions at mineral surfaces and in pore networks. Chemical reactions and transport are integrated into a FHP-I LGA code as a module so that the approach is readily transportable to other codes. Diffusion in a box calculations are compared to finite element Fickian diffusion results and provide an approach to quantifying space-time ratios of the models. Chemical reactions at solid surfaces, including precipitation/dissolution, sorption, and catalytic reaction, can be examined with the model because solute diffusion and mineral surface processes are all treated explicitly. The simplicity and flexibility of the LGA approach provides the ability to study the interrelationship between fluid flow and chemical reactions in porous materials, at a level of complexity that has not previously been computationally possible. 20 refs., 8 figs.
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.
When Disruptive Approaches Meet Disruptive Technologies: Learning at a Distance.
ERIC Educational Resources Information Center
Gibson, Chere Campbell
2000-01-01
Reviews research on constructivism in learning and selection of learning strategies. Suggests linking constructivism with instructional technologies for continuing medical education in order to "disrupt" reactive, habitual ways of learning and encourage active engagement. (SK)
Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults
NASA Technical Reports Server (NTRS)
Spikovska, Lilly; Iverson, David L.; Poll, Scott; Pryor, anna
2005-01-01
Neural network flight controllers are able to accommodate a variety of aircraft control surface faults without detectable degradation of aircraft handling qualities. Under some faults, however, the effective flight envelope is reduced; this can lead to unexpected behavior if a pilot performs an action that exceeds the remaining control authority of the damaged aircraft. The goal of our work is to increase the pilot s situational awareness by informing him of the type of damage and resulting reduction in flight envelope. Our methodology integrates two inductive learning systems with novel visualization techniques. One learning system, the Inductive Monitoring System (IMS), learns to detect when a simulation includes faulty controls, while two others, Inductive Classification System (INCLASS) and multiple binary decision tree system (utilizing C4.5), determine the type of fault. In off-line training using only non-failure data, IMS constructs a characterization of nominal flight control performance based on control signals issued by the neural net flight controller. This characterization can be used to determine the degree of control augmentation required in the pitch, roll, and yaw command channels to counteract control surface failures. This derived information is typically sufficient to distinguish between the various control surface failures and is used to train both INCLASS and C4.5. Using data from failed control surface flight simulations, INCLASS and C4.5 independently discover and amplify features in IMS results that can be used to differentiate each distinct control surface failure situation. In real-time flight simulations, distinguishing features learned during training are used to classify control surface failures. Knowledge about the type of failure can be used by an additional automated system to alter its approach for planning tactical and strategic maneuvers. The knowledge can also be used directly to increase the pilot s situational awareness and
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.
Examining Learning Approaches of Science Student Teachers According to the Class Level and Gender
ERIC Educational Resources Information Center
Tural Dincer, Guner; Akdeniz, Ali Riza
2008-01-01
There are many factors influence the level of students' achievement in education. Studies show that one of these factors is "learning approach of a student". Research findings generally have identified two approaches of learning: deep and surface. When a student uses the deep approach, he/she has an intrinsic interest in subject matter and is…
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…
The Knowledge Creation Metaphor--An Emergent Epistemological Approach to Learning
ERIC Educational Resources Information Center
Paavola, Sami; Hakkarainen, Kai
2005-01-01
We argue that beyond metaphors, according to which learning is a process of knowledge acquisition by individual learners (a "monological" approach) or participation to social interaction (a "dialogical" approach), one should distinguish a "trialogical" approach, i.e., learning as a process of knowledge creation which concentrates on mediated…
Teaching Systems Biology: An Active-learning Approach
2005-01-01
With genomics well established in modern molecular biology, recent studies have sought to further the discipline by integrating complementary methodologies into a holistic depiction of the molecular mechanisms underpinning cell function. This genomic subdiscipline, loosely termed “systems biology,” presents the biology educator with both opportunities and obstacles: The benefit of exposing students to this cutting-edge scientific methodology is manifest, yet how does one convey the breadth and advantage of systems biology while still engaging the student? Here, I describe an active-learning approach to the presentation of systems biology. In graduate classes at the University of Michigan, Ann Arbor, I divided students into small groups and asked each group to interpret a sample data set (e.g., microarray data, two-hybrid data, homology-search results) describing a hypothetical signaling pathway. Mimicking realistic experimental results, each data set revealed a portion of this pathway; however, students were only able to reconstruct the full pathway by integrating all data sets, thereby exemplifying the utility in a systems biology approach. Student response to this cooperative exercise was extremely positive. In total, this approach provides an effective introduction to systems biology appropriate for students at both the undergraduate and graduate levels. PMID:16341259
A machine learning approach to crater detection from topographic data
NASA Astrophysics Data System (ADS)
Di, Kaichang; Li, Wei; Yue, Zongyu; Sun, Yiwei; Liu, Yiliang
2014-12-01
Craters are distinctive features on the surfaces of most terrestrial planets. Craters reveal the relative ages of surface units and provide information on surface geology. Extracting craters is one of the fundamental tasks in planetary research. Although many automated crater detection algorithms have been developed to exact craters from image or topographic data, most of them are applicable only in particular regions, and only a few can be widely used, especially in complex surface settings. In this study, we present a machine learning approach to crater detection from topographic data. This approach includes two steps: detecting square regions which contain one crater with the use of a boosting algorithm and delineating the rims of the crater in each square region by local terrain analysis and circular Hough transform. A new variant of Haar-like features (scaled Haar-like features) is proposed and combined with traditional Haar-like features and local binary pattern features to enhance the performance of the classifier. Experimental results with the use of Mars topographic data demonstrate that the developed approach can significantly decrease the false positive detection rate while maintaining a relatively high true positive detection rate even in challenging sites.
Drug repositioning: a machine-learning approach through data integration.
Napolitano, Francesco; Zhao, Yan; Moreira, Vânia M; Tagliaferri, Roberto; Kere, Juha; D'Amato, Mauro; Greco, Dario
2013-01-01
: Existing computational methods for drug repositioning either rely only on the gene expression response of cell lines after treatment, or on drug-to-disease relationships, merging several information levels. However, the noisy nature of the gene expression and the scarcity of genomic data for many diseases are important limitations to such approaches. Here we focused on a drug-centered approach by predicting the therapeutic class of FDA-approved compounds, not considering data concerning the diseases. We propose a novel computational approach to predict drug repositioning based on state-of-the-art machine-learning algorithms. We have integrated multiple layers of information: i) on the distances of the drugs based on how similar are their chemical structures, ii) on how close are their targets within the protein-protein interaction network, and iii) on how correlated are the gene expression patterns after treatment. Our classifier reaches high accuracy levels (78%), allowing us to re-interpret the top misclassifications as re-classifications, after rigorous statistical evaluation. Efficient drug repurposing has the potential to significantly impact the whole field of drug development. The results presented here can significantly accelerate the translation into the clinics of known compounds for novel therapeutic uses. PMID:23800010
Drug repositioning: a machine-learning approach through data integration
2013-01-01
Existing computational methods for drug repositioning either rely only on the gene expression response of cell lines after treatment, or on drug-to-disease relationships, merging several information levels. However, the noisy nature of the gene expression and the scarcity of genomic data for many diseases are important limitations to such approaches. Here we focused on a drug-centered approach by predicting the therapeutic class of FDA-approved compounds, not considering data concerning the diseases. We propose a novel computational approach to predict drug repositioning based on state-of-the-art machine-learning algorithms. We have integrated multiple layers of information: i) on the distances of the drugs based on how similar are their chemical structures, ii) on how close are their targets within the protein-protein interaction network, and iii) on how correlated are the gene expression patterns after treatment. Our classifier reaches high accuracy levels (78%), allowing us to re-interpret the top misclassifications as re-classifications, after rigorous statistical evaluation. Efficient drug repurposing has the potential to significantly impact the whole field of drug development. The results presented here can significantly accelerate the translation into the clinics of known compounds for novel therapeutic uses. PMID:23800010
Learning approaches to physiology of undergraduates in an Indian medical school.
Abraham, Reem R; Kamath, Asha; Upadhya, Subramanya; Ramnarayan, Komattil
2006-09-01
Inventories monitoring students' learning approaches are widely used in medical education research. It is important that teaching interventions adopted in medical schools aim to develop a deep approach to learning in medical students. To study the changes in medical students' approaches to learning before and after the incorporation of clinically orientated physiology teaching (COPT) in the undergraduate physiology curriculum, using the Short Inventory of Approaches to Learning (SIAL). Medical students (n = 223) at Melaka Manipal Medical College (Manipal Campus) undertake a 9-week learning block of endocrine, reproductive and renal physiology in Year 1. During this period, COPT was incorporated along with regular didactic lectures with the intention of enhancing the use of the deep approach and decreasing the use of the surface and strategic approaches to learning taken by the students. The SIAL, which focuses on the learning approaches of students to physiology, was distributed both before and after COPT. The implementation of COPT seemed to affect the learning approaches of students as measured by the SIAL. After the introduction of COPT, there was a significant increase in the use of the deep learning approach, while the majority of subscales for the surface approach showed decreased use. Nevertheless, use of the strategic approach was found to have increased after COPT. The SIAL was found to be a fairly reliable tool with which to determine the learning approaches of medical students. Clinically orientated physiology teaching was successful in enhancing use of the deep approach to learning and reducing use of the surface approach among undergraduate medical students. PMID:16925643
Machine Learning Approaches to Rare Events Sampling and Estimation
NASA Astrophysics Data System (ADS)
Elsheikh, A. H.
2014-12-01
Given the severe impacts of rare events, we try to quantitatively answer the following two questions: How can we estimate the probability of a rare event? And what are the factors affecting these probabilities? We utilize machine learning classification methods to define the failure boundary (in the stochastic space) corresponding to a specific threshold of a rare event. The training samples for the classification algorithm are obtained using multilevel splitting and Monte Carlo (MC) simulations. Once the training of the classifier is performed, a full MC simulation can be performed efficiently using the classifier as a reduced order model replacing the full physics simulator.We apply the proposed method on a standard benchmark for CO2 leakage through an abandoned well. In this idealized test case, CO2 is injected into a deep aquifer and then spreads within the aquifer and, upon reaching an abandoned well; it rises to a shallower aquifer. In current study, we try to evaluate the probability of leakage of a pre-defined amount of the injected CO2 given a heavy tailed distribution of the leaky well permeability. We show that machine learning based approaches significantly outperform direct MC and multi-level splitting methods in terms of efficiency and precision. The proposed algorithm's efficiency and reliability enabled us to perform a sensitivity analysis to the different modeling assumptions including the different prior distributions on the probability of CO2 leakage.
Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches
Kim, Jae-Won; Sharma, Vinod
2015-01-01
Background: There are no objective, biological markers that can robustly predict methylphenidate response in attention deficit hyperactivity disorder. This study aimed to examine whether applying machine learning approaches to pretreatment demographic, clinical questionnaire, environmental, neuropsychological, neuroimaging, and genetic information can predict therapeutic response following methylphenidate administration. Methods: The present study included 83 attention deficit hyperactivity disorder youth. At baseline, parents completed the ADHD Rating Scale-IV and Disruptive Behavior Disorder rating scale, and participants undertook the continuous performance test, Stroop color word test, and resting-state functional MRI scans. The dopamine transporter gene, dopamine D4 receptor gene, alpha-2A adrenergic receptor gene (ADRA2A) and norepinephrine transporter gene polymorphisms, and blood lead and urine cotinine levels were also measured. The participants were enrolled in an 8-week, open-label trial of methylphenidate. Four different machine learning algorithms were used for data analysis. Results: Support vector machine classification accuracy was 84.6% (area under receiver operating characteristic curve 0.84) for predicting methylphenidate response. The age, weight, ADRA2A MspI and DraI polymorphisms, lead level, Stroop color word test performance, and oppositional symptoms of Disruptive Behavior Disorder rating scale were identified as the most differentiating subset of features. Conclusions: Our results provide preliminary support to the translational development of support vector machine as an informative method that can assist in predicting treatment response in attention deficit hyperactivity disorder, though further work is required to provide enhanced levels of classification performance. PMID:25964505
A hybrid ensemble learning approach to star-galaxy classification
NASA Astrophysics Data System (ADS)
Kim, Edward J.; Brunner, Robert J.; Carrasco Kind, Matias
2015-10-01
There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template-fitting method. Using data from the CFHTLenS survey (Canada-France-Hawaii Telescope Lensing Survey), we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2 (Deep Extragalactic Evolutionary Probe Phase 2 ), SDSS (Sloan Digital Sky Survey), VIPERS (VIMOS Public Extragalactic Redshift Survey), and VVDS (VIMOS VLT Deep Survey), and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, strategies that combine the predictions of different classifiers may prove to be optimal in currently ongoing and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope.
Approach to Dynamic Assembling of Individualized Learning Paths
ERIC Educational Resources Information Center
Lubchak, Vladimir; Kupenko, Olena; Kuzikov, Borys
2012-01-01
E-learning students are generally heterogeneous and have different capabilities knowledge base and needs. The aim of the Sumy State University (SSU) e-learning system project is to cater to these individual needs by assembling individual learning path. This paper shows current situation with e-learning in Ukraine, state-of-art of development of…
A Systems Approach to the Teaching-Learning Process.
ERIC Educational Resources Information Center
Belgard, Maria R.
This paper introduces the concept of educational systems analysis, shows how it can be applied to the teaching-learning process, and indicates how the teaching-learning process, as a system, can be optimized by using operations research techniques. The teaching-learning process is viewed as a highly complex learning control system with the purpose…
Constructive and problem-based learning using blended learning anchored instruction approaches
NASA Astrophysics Data System (ADS)
Mayer, M.
2012-04-01
Based on an anchored instruction approach, an enriched blended learning lecture course ("Introduction into GNSS positioning") was established in order to enable constructive and problem-based learning. The lecture course "Introduction into GNSS positioning" is a compulsory part of the Bachelor study course "Geodesy and Geoinformatics" and also a supplementary module of the Bachelor study course "Geophysics". Within the lecture course, basic knowledge and basic principles of Global Navigation Satellite Systems, like GPS, are imparted. The presented higher education technique "anchored instruction" uses a real and up-to-date and therefore authentic scientific paper dealing with a recent large-scale geodetic project (Fehmarn Belt Fixed Link) in order to introduce the topic of GNSS-based positioning to the students. In the beginning of the semester, the students have to read the paper individually and carefully. This enables them to realize a lot of not-known GNSS-related facts. Therefore, questions can be formulated focusing on new, unclear or not-understood aspects of the paper. The lecture course deals with these questions, in order to answer them throughout the semester. During the lecture course this paper is referred, e.g., in the middle of the semester, the paper has to be read again in order to check which questions have been answered; in addition, new question arise. At the end of the lecture course, the author of the scientific paper gave a concluding lecture. The framing anchor technique enables the students to anchor their GNSS knowledge. The presented case study uses a teaching resp. learning setting consisting of classroom lectures (given by teachers and learners), practical trainings (e.g., field exercises, students select topics individually), and online lectures (learning management system ILIAS is used as data, result, and asynchronous communication platform). The implementation and the elements of the anchoring technique, which enables student
A full computation-relevant topological dynamics classification of elementary cellular automata
NASA Astrophysics Data System (ADS)
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."
ERIC Educational Resources Information Center
Gijbels, David; Segers, Mien; Struyf, Elke
2008-01-01
Recent research shows that, as students interpret the demands of the assessment tasks, they vary their approaches to learning in order to cope with the assessment tasks. Three research questions are central in the present paper: (1) Do students who participate in a constructivist learning environment change their perception of assessment demands…
ERIC Educational Resources Information Center
Khan, S.
2011-01-01
The purpose of this article is to report on empirical work, related to a techniques module, undertaken with the dental students of the University of the Western Cape, South Africa. I will relate how a range of different active learning techniques (tutorials; question papers and mock tests) assisted students to adopt a deep approach to learning in…
ERIC Educational Resources Information Center
Hsu, Ching-Kun; Hwang, Gwo-Jen
2014-01-01
Personal computer assembly courses have been recognized as being essential in helping students understand computer structure as well as the functionality of each computer component. In this study, a context-aware ubiquitous learning approach is proposed for providing instant assistance to individual students in the learning activity of a…
ERIC Educational Resources Information Center
Arulselvi, Evangelin
2013-01-01
The present study aims at finding out the effectiveness of Mutual learning approach over the conventional method in learning English optional II among B.Ed students. The randomized pre-test, post test, control group and experimental group design was employed. The B.Ed students of the same college formed the control and experimental groups. Each…
ERIC Educational Resources Information Center
Brett, Paul; Nagra, Jas
2005-01-01
Provision of computers in universities for self-study is taken for granted and is seen as a must have educational resource, yet it is very expensive to fund. Students report that they use the Internet as their first stop in approaching research tasks. Learning theorists posit the important role of social interaction in contributing to learning.…
A Machine Learning Approach for Accurate Annotation of Noncoding RNAs
Liu, Chunmei; Wang, Zhi
2016-01-01
Searching genomes to locate noncoding RNA genes with known secondary structure is an important problem in bioinformatics. In general, the secondary structure of a searched noncoding RNA is defined with a structure model constructed from the structural alignment of a set of sequences from its family. Computing the optimal alignment between a sequence and a structure model is the core part of an algorithm that can search genomes for noncoding RNAs. In practice, a single structure model may not be sufficient to capture all crucial features important for a noncoding RNA family. In this paper, we develop a novel machine learning approach that can efficiently search genomes for noncoding RNAs with high accuracy. During the search procedure, a sequence segment in the searched genome sequence is processed and a feature vector is extracted to represent it. Based on the feature vector, a classifier is used to determine whether the sequence segment is the searched ncRNA or not. Our testing results show that this approach is able to efficiently capture crucial features of a noncoding RNA family. Compared with existing search tools, it significantly improves the accuracy of genome annotation. PMID:26357266
Light: an experiments based learning approach with primary school children
NASA Astrophysics Data System (ADS)
Abreu, Cátia; Noversa, Silvana; Varela, Paulo; Costa, Manuel F.
2014-07-01
A pedagogical intervention project was carried out at a primary school in the municipality of Vila Verde, Braga in Portugal. In a class of the 3rd grade, composed of 16 students, a practice of inquiry-based science teaching was implemented, addressing the curricular topic "Light Experiments". Various experimental activities were planned within this topic, including: What is light? How does light travel? Does light travel through every material? How is light reflected by a mirror? This project adopted an action research methodology and had as its main objectives: a) to promote a practical and experimental approach to the science component of the Environmental Studies curricular area; b) to describe the scientific meaning construction process inherent to the topics addressed in the classroom with the children, c) to assess the learning steps and children' achievements. Class diaries were prepared, based on field notes and audio recordings taken in the classroom. Through the analysis of the class diary concerning the topic "materials that let light travel through them" we intend to illustrate the process of construction of scientific meanings promoted in the classroom with our approach.
Machine learning approaches in medical image analysis: From detection to diagnosis.
de Bruijne, Marleen
2016-10-01
Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols, learning from weak labels, and interpretation and evaluation of results. PMID:27481324
Learning in the Liminal Space: A Semiotic Approach to Threshold Concepts
ERIC Educational Resources Information Center
Land, Ray; Rattray, Julie; Vivian, Peter
2014-01-01
The threshold concepts approach to student learning and curriculum design now informs an empirical research base comprising over 170 disciplinary and professional contexts. It draws extensively on the notion of troublesomeness in a "liminal" space of learning. The latter is a transformative state in the process of learning in which there…
ERIC Educational Resources Information Center
Wu, Ji-Wei; Tseng, Judy C. R.; Hwang, Gwo-Jen
2015-01-01
Inquiry-Based Learning (IBL) is an effective approach for promoting active learning. When inquiry-based learning is incorporated into instruction, teachers provide guiding questions for students to actively explore the required knowledge in order to solve the problems. Although the World Wide Web (WWW) is a rich knowledge resource for students to…
ERIC Educational Resources Information Center
Scott, Sophia; Koch, Doug
2010-01-01
This article focuses on how technology educators can challenge students to "think" about technical problems. A key aspect of success in quality problem solving is understanding learning preferences and problem-solving approaches. The Learning Style Inventory (LSI) can be used to assess an individual's ideal way to learn, in essence, a person's…
An Evaluation of Learning Objects in Singapore Primary Education: A Case Study Approach
ERIC Educational Resources Information Center
Grace, Tay Pei Lyn; Suan, Ng Peck; Wanzhen, Liaw
2008-01-01
Purpose: The purpose of this paper is to evaluate the usability and interface design of e-learning portal developed for primary schools in Singapore. Design/methodology/approach: Using Singapore-based learning EDvantage (LEAD) portal as a case study, this paper reviews and analyses the usability and usefulness of embedded learning objects (LOs)…
Learning Biology through Innovative Curricula: A Comparison of Game- and Nongame-Based Approaches
ERIC Educational Resources Information Center
Sadler, Troy D.; Romine, William L.; Menon, Deepika; Ferdig, Richard E.; Annetta, Leonard
2015-01-01
This study explored student learning in the context of innovative biotechnology curricula and the effects of gaming as a central element of the learning experience. The quasi-experimentally designed study compared learning outcomes between two curricular approaches: One built around a computer-based game, and the other built around a narrative…
Effect of Inquiry-Based Learning Approach on Student Resistance in a Science and Technology Course
ERIC Educational Resources Information Center
Sever, Demet; Guven, Meral
2014-01-01
The aim of this study was to identify the resistance behaviors of 7th grade students exhibited during their Science and Technology course teaching-learning processes, and to remove the identified resistance behaviors through teaching-learning processes that were constructed based on the inquiry-based learning approach. In the quasi-experimentally…
Autonomy in Science Education: A Practical Approach in Attitude Shifting towards Science Learning
ERIC Educational Resources Information Center
Jalil, Pasl A.; Abu Sbeih, M. Z.; Boujettif, M.; Barakat, R.
2009-01-01
This work describes a 2-year study in teaching school science, based on the stimulation of higher thinking levels in learning science using a highly student-centred and constructivist learning approach. We sought to shift and strengthen students' positive attitudes towards science learning, self-efficacy towards invention, and achievement.…
ERIC Educational Resources Information Center
Önen, Emine
2015-01-01
This study aimed to examine connections between modes of thinking and approaches to learning. Participants were 1490 students attending to 9 high schools located in Ankara. The Style of Learning and Thinking-Youth Form and Revised Version of Learning Process Questionnaire were administered to these students. The connections between modes of…
The Development of a Robot-Based Learning Companion: A User-Centered Design Approach
ERIC Educational Resources Information Center
Hsieh, Yi-Zeng; Su, Mu-Chun; Chen, Sherry Y.; Chen, Gow-Dong
2015-01-01
A computer-vision-based method is widely employed to support the development of a variety of applications. In this vein, this study uses a computer-vision-based method to develop a playful learning system, which is a robot-based learning companion named RobotTell. Unlike existing playful learning systems, a user-centered design (UCD) approach is…
Assessment of Reading and Learning Disabilities: A Research-Based Intervention-Oriented Approach.
ERIC Educational Resources Information Center
Fletcher, Jack M.; Foorman, Barbara R.; Boudousquie, Amy
2002-01-01
Reviews implications of the three primary components of the federal definition of learning disabilities (discrepancy, heterogeneity, and exclusion) for the assessment of children with learning disabilities (LD). Also proposes a rationale and procedures for more efficient approaches to the identification of children as learning disabled that are…
ERIC Educational Resources Information Center
Shroff, Ronnie H.; Vogel, Douglas R.
2010-01-01
Research has established that individual student interest has a positive effect on learning and academic achievement. However, little is known about the impact of a blended learning approach on individual student interest and whether combinations of online and face-to-face learning activities significantly enhance student interest. This paper…
An Outcome Evaluation of a Problem-Based Learning Approach with MSW Students
ERIC Educational Resources Information Center
Westhues, Anne; Barsen, Chia; Freymond, Nancy; Train, Patricia
2014-01-01
In this article, we report the findings from a study exploring the effects of a problem-based learning (PBL) approach to teaching and learning on learning outcomes for master's of social work (MSW) students. Students who participated in a PBL pilot project were compared with students who did not participate in 5 outcome areas: social work…
A Cognitive Load Approach to Collaborative Learning: United Brains for Complex Tasks
ERIC Educational Resources Information Center
Kirschner, Femke; Paas, Fred; Kirschner, Paul A.
2009-01-01
This article presents a review of research comparing the effectiveness of individual learning environments with collaborative learning environments. In reviewing the literature, it was determined that there is no clear and unequivocal picture of how, when, and why the effectiveness of these two approaches to learning differ, a result which may be…
ERIC Educational Resources Information Center
Drago-Severson, Eleanor
2016-01-01
"What is happening in education today?" and "What is most needed for the future of teaching, learning and leading?" This article presents a developmental approach to learning, leadership and advancing professional learning--one that takes into account adults' diverse meaning making processes--that can help educators build the…
ERIC Educational Resources Information Center
Linsey, Julie; Talley, Austin; White, Christina; Jensen, Dan; Wood, Kristin
2009-01-01
Active learning enhances engineering education. This paper presents rationale, curriculum supplements, and an approach to active learning that may be seamlessly incorporated into a traditional lecture-based engineering class. A framework of educational theory that structures the active learning experiences and includes consideration of learning…
The Promise of a Community-Based, Participatory Approach to Service-Learning in Teacher Education
ERIC Educational Resources Information Center
Tinkler, Alan; Tinkler, Barri; Gerstl-Pepin, Cynthia; Mugisha, Vincent M.
2014-01-01
This article reports on how one teacher education program utilized a Learn and Serve America grant to embed service-learning experiences into its practices. Included are narrative reflections on how the program faculty developed a community-based, participatory approach to service-learning in order to act as a responsive partner to the needs of…
Learner-Centred Pedagogy for Swim Coaching: A Complex Learning Theory-Informed Approach
ERIC Educational Resources Information Center
Light, Richard
2014-01-01
While constructivist theories of learning have been widely drawn on to understand and explain learning in games when using game-based approaches their use to inform pedagogy beyond games is limited. In particular, there has been little interest in applying constructivist perspectives on learning to sports in which technique is of prime importance.…
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 Comparison of the Learning Approaches of Accounting and Science Students at an Irish University
ERIC Educational Resources Information Center
Byrne, Marann; Finlayson, Odilla; Flood, Barbara; Lyons, Orla; Willis, Pauline
2010-01-01
One of the major challenges facing accounting education is the creation of a learning environment that promotes high-quality learning. Comparative research across disciplines offers educators the opportunity to gain a better understanding of the influence of contextual and personal variables on students' learning approaches. Using the Approaches…
Quantum dot spin cellular automata for realizing a quantum processor
NASA Astrophysics Data System (ADS)
Bayat, Abolfazl; Creffield, Charles E.; Jefferson, John H.; Pepper, Michael; Bose, Sougato
2015-10-01
We show how single quantum dots, each hosting a singlet-triplet qubit, can be placed in arrays to build a spin quantum cellular automaton. A fast (˜10 ns) deterministic coherent singlet-triplet filtering, as opposed to current incoherent tunneling/slow-adiabatic based quantum gates (operation time ˜300 ns), can be employed to produce a two-qubit gate through capacitive (electrostatic) couplings that can operate over significant distances. This is the coherent version of the widely discussed charge and nano-magnet cellular automata, and would increase speed, reduce dissipation, and perform quantum computation while interfacing smoothly with its classical counterpart. This combines the best of two worlds—the coherence of spin pairs known from quantum technologies, and the strength and range of electrostatic couplings from the charge-based classical cellular automata. Significantly our system has zero electric dipole moment during the whole operation process, thereby increasing its charge dephasing time.
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.
From quantum cellular automata to quantum lattice gases
Meyer, D.A.
1996-12-01
A natural architecture for nanoscale quantum computation is that of a quantum cellular automaton. Motivated by this observation, we begin an investigation of exactly unitary cellular automata. After proving that there can be no nontrivial, homogeneous, local, unitary, scalar cellular automaton in one dimension, we weaken the homogeneity condition and show that there are nontrivial, exactly unitary, partitioning cellular automata. We find a one-parameter family of evolution rules which are best interpreted as those for a one-particle quantum automaton. This model is naturally reformulated as a two component cellular automaton which we demonstrate to limit to the Dirac equation. We describe two generalizations of this automaton, the second of which, to multiple interacting particles, is the correct definition of a quantum lattice gas.
Biswas, Ashis Kumer; Zhang, Baoju; Wu, Xiaoyong; Gao, Jean X
2013-10-01
The statistics about the open reading frames, the base compositions and the properties of the predicted secondary structures have potential to address the problem of discriminating coding and noncoding transcripts. Again, the Next Generation Sequencing platform, RNA-seq, provides us bounty of data from which expression profiles of the transcripts can be extracted which urged us adding a new set of dimension in this classification task. In this paper, we proposed CNCTDiscriminator -- a coding and noncoding transcript discriminating system where we applied the integration of these four categories of features about the transcripts. The feature integration was done using both hypothesis learning and feature specific ensemble learning approaches. The CNCTDiscriminator model which was trained with composition and ORF features outperforms (precision 83.86%, recall 82.01%) other three popular methods -- CPC (precision 98.31%, recall 25.95%), CPAT (precision 97.74%, recall 52.50%) and PORTRAIT (precision 84.37%, recall 73.2%) when applied to an independent benchmark dataset. However, the CNCTDiscriminator model that was trained using the ensemble approach shows comparable performance (precision 89.85%, recall 71.08%). PMID:24131051
ERIC Educational Resources Information Center
Fuller, June L.
This study examined teachers' perceptions of changes in student learning and changes in their teaching strategies after implementing the Partners Advancing the Learning of Math and Science (PALMS) approach in an urban Massachusetts school district. PALMS was a cooperative statewide systemic initiative funded by the Massachusetts Department of…
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.
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.
Automata-theoretic models of mutation and alignment
Searls, D.B.; Murphy, K.P.
1995-12-31
Finite-state automata called transducers, which have both input and output, can be used to model simple mechanisms of biological mutation. We present a methodology whereby numerically-weighted versions of such specifications can be mechanically adapted to create string edit machines that are essentially equivalent to recurrence relations of the sort that characterize dynamic programming alignment algorithms. Based on this, we have developed a visual programming system for designing new alignment algorithms in a rapid-prototyping fashion.
Generalized hydrodynamic transport in lattice-gas automata
Luo, L. School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332-0430 ); Chen, H. Department of Physics, Dartmouth College, Hanover, New Hampshire 03755 ); Chen, S. Bartol Research Institute, University of Delaware, Newark, Delaware 19716 ); Doolen, G.D.; Lee, Y. )
1991-06-15
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 {bold k} is obtained analytically. Anisotropy of these coefficients due to the lattice symmetry is studied for the entire range of wave number, {bold k}. Boundary effects due to a finite mean free path (Knudsen layer) are analyzed, and accurate comparisons are made with lattice-gas simulations.
An autonomous DNA model for finite state automata.
Martinez-Perez, Israel M; Zimmermann, Karl-Heinz; Ignatova, Zoya
2009-01-01
In this paper we introduce an autonomous DNA model for finite state automata. This model called sticker automaton model is based on the hybridisation of single stranded DNA molecules (stickers) encoding transition rules and input data. The computation is carried out in an autonomous manner by one enzyme which allows us to determine whether a resulting double-stranded DNA molecule belongs to the automaton's language or not. PMID:19136366
Identifying patterns from one-rule-firing cellular automata.
Shin, Jae Kyun
2011-01-01
A new firing scheme for cellular automata in which only one rule is fired at a time produces myriad patterns. In addition to geometric patterns, natural patterns such as flowers and snow crystals were also generated. This study proposes an efficient method identifying the patterns using a minimal number of digits. Complexity of the generated patterns is discussed in terms of the shapes and colors of the patterns. PMID:21087150
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.
A Wiki Technology-Supported Seamless Learning Approach for Chinese Language Learning
ERIC Educational Resources Information Center
Wong, Lung-Hsiang; Chin, Chee-Kuen; Tay, Boon-Pei
2011-01-01
This paper reports an intervention study on Singapore primary five (fifth Grade) students' ICT (information and communication technology)-mediated Chinese idiom learning. We introduced "seamless learning" to the learning design, that is, the bridging of formal and informal learning, and individual and social learning, conforming to the current…
Effects of Situated Mobile Learning Approach on Learning Motivation and Performance of EFL Students
ERIC Educational Resources Information Center
Huang, Chester S. J.; Yang, Stephen J. H.; Chiang, Tosti H. C.; Su, Addison Y. S.
2016-01-01
This study developed a 5-step vocabulary learning (FSVL) strategy and a mobile learning tool in a situational English vocabulary learning environment and assessed their effects on the learning motivation and performance of English as a foreign language (EFL) students in a situational English vocabulary learning environment. Overall, 80 EFL…
What time is it? Deep learning approaches for circadian rhythms
Agostinelli, Forest; Ceglia, Nicholas; Shahbaba, Babak; Sassone-Corsi, Paolo; Baldi, Pierre
2016-01-01
Motivation: Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken. Results: We first curate several large synthetic and biological time series datasets containing labels for both periodic and aperiodic signals. We then use deep learning methods to develop and train BIO_CYCLE, a system to robustly estimate which signals are periodic in high-throughput circadian experiments, producing estimates of amplitudes, periods, phases, as well as several statistical significance measures. Using the curated data, BIO_CYCLE is compared to other approaches and shown to achieve state-of-the-art performance across multiple metrics. We then use deep learning methods to develop and train BIO_CLOCK to robustly estimate the time at which a particular single-time-point transcriptomic experiment was carried. In most cases, BIO_CLOCK can reliably predict time, within approximately 1 h, using the expression levels of only a small number of core clock genes. BIO_CLOCK is shown to work reasonably well across tissue types, and often with only small degradation across conditions. BIO_CLOCK is used to annotate most mouse experiments found in the GEO database with an inferred time stamp. Availability and Implementation: All data and software are publicly available on the CircadiOmics web portal: circadiomics.igb.uci.edu/. Contacts: fagostin@uci.edu or pfbaldi@uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307647
A Learning-Based Approach for IP Geolocation
NASA Astrophysics Data System (ADS)
Eriksson, Brian; Barford, Paul; Sommers, Joel; Nowak, Robert
The ability to pinpoint the geographic location of IP hosts is compelling for applications such as on-line advertising and network attack diagnosis. While prior methods can accurately identify the location of hosts in some regions of the Internet, they produce erroneous results when the delay or topology measurement on which they are based is limited. The hypothesis of our work is that the accuracy of IP geolocation can be improved through the creation of a flexible analytic framework that accommodates different types of geolocation information. In this paper, we describe a new framework for IP geolocation that reduces to a machine-learning classification problem. Our methodology considers a set of lightweight measurements from a set of known monitors to a target, and then classifies the location of that target based on the most probable geographic region given probability densities learned from a training set. For this study, we employ a Naive Bayes framework that has low computational complexity and enables additional environmental information to be easily added to enhance the classification process. To demonstrate the feasibility and accuracy of our approach, we test IP geolocation on over 16,000 routers given ping measurements from 78 monitors with known geographic placement. Our results show that the simple application of our method improves geolocation accuracy for over 96% of the nodes identified in our data set, with on average accuracy 70 miles closer to the true geographic location versus prior constraint-based geolocation. These results highlight the promise of our method and indicate how future expansion of the classifier can lead to further improvements in geolocation accuracy.
The Use of Cellular Automata in the Learning of Emergence
ERIC Educational Resources Information Center
Faraco, G.; Pantano, P.; Servidio, R.
2006-01-01
In recent years, research efforts on complex systems have contributed to improve our ability in investigating, at different levels of complexity, the emergent behaviour shown by a system in the course of its evolution. The study of emergence, an intrinsic property of a large number of complex systems, can be tackled by making use of Cellular…
Discovering Motifs in Biological Sequences Using the Micron Automata Processor.
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. PMID:26886735
Anticipating the Filtrons of Automata by Complex Discrete Systems Analysis
NASA Astrophysics Data System (ADS)
Siwak, Pawel
2002-09-01
Filtrons of automata are coherent structures (discrete solitons) supported by iterated automata maps (IAMs). They differ from signals of cellular automata. The signals emerge during parallel processing of strings, while IAMs transform strings in serial. We relate the filtron and its supporting automaton with a particular complex discrete system (CDS). This CDS has the form of a processing ring net. Its computation is characterized by four components: instructions of processing nodes (I), inter-processor communication constraints (C), initial data (D), and synchronization (S). We present an analysis of a computation performed within this CDS. It is useful in the problems of searching for any of the mentioned four components assuming that remaining three are known. We give a technique of anticipating the filtrons with a desired parameter C when I, S and D are given. We show how to decide the synchronization S when I, C and D are assumed, and how to determine instructions I when the desired filtron is described by known C, D and S.
An educational approach to problem-based learning.
Chen, Nan-Chieh
2008-03-01
This paper provides an analysis of the educational framework of problem-based learning (PBL). As known and used, PBL finds its root in the Structuralism and Pragmatism schools of philosophy. In this paper, the three main requirements of PBL, namely learning by doing, learning in context, and focusing on the student, are discussed within the context of these two schools of thought. Given these attributes, PBL also seems ideally suited for use in learning bioethics. PMID:18364283
Fostering Faculty Collaboration in Learning Communities: A Developmental Approach
ERIC Educational Resources Information Center
Stevenson, Catherine B.; Duran, Robert L.; Barrett, Karen A.; Colarulli, Guy C.
2005-01-01
Colleges and universities are adopting learning communities to increase student learning and build cohesion. As learning communities grow in popularity, institutions need to invest in faculty development (Oates, 2001) and understand faculty experiences (Mullen, 2001). The University of Hartford created a program that prepared faculty for…
Action Learning for Professionals: A New Approach to Practice
ERIC Educational Resources Information Center
Abbott, Christine; Mayes, Cathy
2014-01-01
Following on from the article "Building Capacity in Social Care: An Evaluation of a National Programme of Action Learning Facilitator Development" (Abbott, C., L. Burtney, and C. Wall. 2013. "Action Learning: Research & Practice" 10 (2): 168--177), this article describes how action learning is being introduced in Cornwall…
An Investigative, Cooperative Learning Approach to the General Microbiology Laboratory
ERIC Educational Resources Information Center
Seifert, Kyle; Fenster, Amy; Dilts, Judith A.; Temple, Louise
2009-01-01
Investigative- and cooperative-based learning strategies have been used effectively in a variety of classrooms to enhance student learning and engagement. In the General Microbiology laboratory for juniors and seniors at James Madison University, these strategies were combined to make a semester-long, investigative, cooperative learning experience…
A Collaborative Action Research Approach to Professional Learning
ERIC Educational Resources Information Center
Bleicher, Robert E.
2014-01-01
The field of professional development is moving towards the notion of professional learning, highlighting the active learning role that teachers play in changing their knowledge bases, beliefs and practice. This article builds on this idea and argues for creating professional learning that is guided by a collaborative action research (CAR)…
A Multidimensional Approach to E-Learning Sustainability
ERIC Educational Resources Information Center
Trentin, Guglielmo, Ed.
2007-01-01
The aim of the article is to outline the possible key elements related to the sustainability of e-learning. After analyzing trends in e-learning diffusion, a multidimensional model for sustainability of e-learning innovations is presented. The proposed model is characterized by eight dimensions that are closely and mutually interrelated:…
A Genetic Algorithm Approach to Recognise Students' Learning Styles
ERIC Educational Resources Information Center
Yannibelli, Virginia; Godoy, Daniela; Amandi, Analia
2006-01-01
Learning styles encapsulate the preferences of the students, regarding how they learn. By including information about the student learning style, computer-based educational systems are able to adapt a course according to the individual characteristics of the students. In accomplishing this goal, educational systems have been mostly based on the…
Designing Science Learning with Game-Based Approaches
ERIC Educational Resources Information Center
Liu, Min; Rosenblum, Jason A.; Horton, Lucas; Kang, Jina
2014-01-01
Given the growing popularity of digital games as a form of entertainment, educators are interested in exploring using digital games as a tool to facilitate learning. In this study, we examine game-based learning by describing a learning environment that combines game elements, play, and authenticity in the real world for the purpose of engaging…
A New Design Approach to Game-Based Learning
ERIC Educational Resources Information Center
Larsen, Lasse Juel
2012-01-01
This paper puts forward a new design perspective for game-based learning. The general idea is to abandon the long sought-after dream of designing a closed learning system, where students in both primary and secondary school could learn--without the interference of teachers--whatever subject they wanted while sitting in front of a computer. This…
ERIC Educational Resources Information Center
Smith, Robert; Peethambaran, Bela; Pontiggia, Laura; Blumberg, Phyllis
2013-01-01
Guided instruction is an approach that fully explains the concepts and procedures that students are required to learn. It seems intuitive that this approach should increase student learning; however, there is evidence in the literature that this may not always be the case. We wanted to assess the effectiveness of our own repeated…
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…
ERIC Educational Resources Information Center
Lieberman, Lauren J.; Lytle, Rebecca K.; Clarcq, Jason A.
2008-01-01
The universal design for learning (UDL) approach to teaching, a method to create access for all students, can be extremely effective when adequate time, energy, and creativity are spent to apply it. The purpose of this article is to encourage the use of the universal design for learning approach to ensure the successful inclusion of all students…
Use of Master Classroom Technology To Implement a Case Study Approach to Learning.
ERIC Educational Resources Information Center
Draude, Barbara J.
This paper describes a case study/client scenario approach used in an advanced medical/surgical nursing course; its methods of interactive learning are facilitated by the computer technology available in a "master classroom." This approach incorporates concepts of adult learning theory and creativity and group interaction. The equipment, such as…
ERIC Educational Resources Information Center
Wallis, Emma
2008-01-01
This article draws upon original qualitative data to present an initial assessment of the significance of learning agreements for the development of socially responsible approaches to professional and human resource development within the workplace. The article suggests that the adoption of a partnership-based approach to learning is more…
ERIC Educational Resources Information Center
Dennehy, Edward
2015-01-01
With the advent of increasingly multinational student cohorts in many higher education institutes, the possible influence of 'national culture' on students' learning approaches has become a focal point of attention. In particular, the claim that Asian (Confucian) students adopt (primarily) surface learning approaches has attracted much debate…
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…
Effects of Students' Approaches to Learning on Performance in Two Pedagogical Environments
ERIC Educational Resources Information Center
Varughese, Varughese Kuzhumannil; Fehring, Heather
2009-01-01
This paper investigates various approaches to learning and their effect on performance of a cohort of international students in two different pedagogical environments. The effect of approaches to learning on performance was determined by using Cohen's "d" with Hedges "g" correction. Coe's spread sheet was used for the purpose.…
ERIC Educational Resources Information Center
Imam, Boulent; Rafiq, M. Imran; Kumar, Prashant
2011-01-01
This article investigates the effectiveness of two distinct formative assessment methods for promoting deep learning and hence improving the performance amongst engineering students. The first method, applied for undergraduate students, employs a lecturer-led approach whereas the second method uses a student-led approach and e-learning for…
A Sampled Literature Review of Design-Based Learning Approaches: A Search for Key Characteristics
ERIC Educational Resources Information Center
Gómez Puente, Sonia M.; van Eijck, Michiel; Jochems, Wim
2013-01-01
Design-based learning (DBL) is an educational approach grounded in the processes of inquiry and reasoning towards generating innovative artifacts, systems and solutions. The approach is well characterized in the context of learning natural sciences in secondary education. Less is known, however, of its characteristics in the context of higher…
Implementing a Problem-Based Learning Approach for Teaching Research Methods in Geography
ERIC Educational Resources Information Center
Spronken-Smith, Rachel
2005-01-01
This paper first describes problem-based learning; second describes how a research methods course in geography is taught using a problem-based learning approach; and finally relates student and staff experiences of this approach. The course is run through regular group meetings, two residential field trips and optional skills-based workshops.…
Investigating the Effect of School Ability on Self-Efficacy, Learning Approaches, and Metacognition
ERIC Educational Resources Information Center
Magno, Carlo
2009-01-01
The relations among school ability, self-efficacy, learning approach, and metacognition were examined in a path model. Questionnaires measuring these constructs were administered to 194 Filipino college students. Path analysis was used to determine the effects of school ability on self-efficacy and learning approaches, and in turn, the effects of…
ERIC Educational Resources Information Center
Kizilgunes, Berna; Tekkaya, Ceren; Sungur, Semra
2009-01-01
The authors proposed a model to explain how epistemological beliefs, achievement motivation, and learning approach related to achievement. The authors assumed that epistemological beliefs influence achievement indirectly through their effect on achievement motivation and learning approach. Participants were 1,041 6th-grade students. Results of the…
ERIC Educational Resources Information Center
Ekowati, Ch. Krisnandari; Darwis, Muhammad; Upa, H. M. D. Pua; Tahmir, Suradi
2015-01-01
This research is an action research which aims to implement contextual teaching and learning (CTL) approach to learn mathematics, focus on the integration subjects. The approach utilizes the use of mathematics manipulative so that students can understand a mathematical concept to construct their own. The method which used in this research are…