A novel time series link prediction method: Learning automata approach
NASA Astrophysics Data System (ADS)
Moradabadi, Behnaz; Meybodi, Mohammad Reza
2017-09-01
Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.
Image Segmentation Based on Learning Cellular Automata Using Soft Computing Approach
NASA Astrophysics Data System (ADS)
Das, Debasis; Ray, Abhishek
2010-10-01
Image Segmentation refers to the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify and change the representation of an image into something that is more meaningful and easier to analyze. A Cellular Automata (CA) is a computing model of complex system using simple rule. It divides the problem space into number of cells and each cell can be in one or several final states. Cells are affected by its neighbor's to the simple rule. Learning Cellular Automata (LCA) is a variant of automata that interact with random environment having as goal to improve its behavior. This paper proposes an image segmentation technique based on LCA using soft computing approach. This proposed method works in two steps, the first step is called as soft segmentation where the input image(s) is/are analyzed through LCA and the second step is called as soft computing approach where the analyzed image is segmented through fuzzy C-means algorithm.
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.
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.
Genetic learning automata for function optimization.
Howell, M N; Gordon, T J; Brandao, F V
2002-01-01
Stochastic learning automata and genetic algorithms (GAs) have previously been shown to have valuable global optimization properties. Learning automata have, however, been criticized for having a relatively slow rate of convergence. In this paper, these two techniques are combined to provide an increase in the rate of convergence for the learning automata and also to improve the chances of escaping local optima. The technique separates the genotype and phenotype properties of the GA and has the advantage that the degree of convergence can be quickly ascertained. It also provides the GA with a stopping rule. If the technique is applied to real-valued function optimization problems, then bounds on the range of the values within which the global optima is expected can be determined throughout the search process. The technique is demonstrated through a number of bit-based and real-valued function optimization examples.
Decentralized indirect methods for learning automata games.
Tilak, Omkar; Martin, Ryan; Mukhopadhyay, Snehasis
2011-10-01
We discuss the application of indirect learning methods in zero-sum and identical payoff learning automata games. We propose a novel decentralized version of the well-known pursuit learning algorithm. Such a decentralized algorithm has significant computational advantages over its centralized counterpart. The theoretical study of such a decentralized algorithm requires the analysis to be carried out in a nonstationary environment. We use a novel bootstrapping argument to prove the convergence of the algorithm. To our knowledge, this is the first time that such analysis has been carried out for zero-sum and identical payoff games. Extensive simulation studies are reported, which demonstrate the proposed algorithm's fast and accurate convergence in a variety of game scenarios. We also introduce the framework of partial communication in the context of identical payoff games of learning automata. In such games, the automata may not communicate with each other or may communicate selectively. This comprehensive framework has the capability to model both centralized and decentralized games discussed in this paper.
Automata Learning with Automated Alphabet Abstraction Refinement
NASA Astrophysics Data System (ADS)
Howar, Falk; Steffen, Bernhard; Merten, Maik
on is the key when learning behavioral models of realistic systems, but also the cause of a major problem: the introduction of non-determinism. In this paper, we introduce a method for refining a given abstraction to automatically regain a deterministic behavior on-the-fly during the learning process. Thus the control over abstraction becomes part of the learning process, with the effect that detected non-determinism does not lead to failure, but to a dynamic alphabet abstraction refinement. Like automata learning itself, this method in general is neither sound nor complete, but it also enjoys similar convergence properties even for infinite systems as long as the concrete system itself behaves deterministically, as illustrated along a concrete example.
An evolving algebra approach to formal description of a class of automata networks
NASA Astrophysics Data System (ADS)
Severyanov, V. M.
2003-04-01
The Automata Networks considered here and called Hyperbolic Cellular Automata are based on Iterated Function Systems and can be considered as a generalization of Cellular Automata. The Evolving Algebras have been proposed by Yuri Gurevich to be the models for arbitrary computational processes. They provide a formal method for executable specifications. In the paper, an evolving algebra approach to formal description of Hyperbolic Cellular Automata is presented.
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 novel cellular automata based approach to storm sewer design
NASA Astrophysics Data System (ADS)
Guo, Y.; Walters, G. A.; Khu, S. T.; Keedwell, E.
2007-04-01
Optimal storm sewer design aims at minimizing capital investment on infrastructure whilst ensuring good system performance under specified design criteria. An innovative sewer design approach based on cellular automata (CA) principles is introduced in this paper. Cellular automata have been applied as computational simulation devices in various scientific fields. However, some recent research has indicated that CA can also be a viable and efficient optimization engine. This engine is heuristic and largely relies on the key properties of CA: locality, homogeneity, and parallelism. In the proposed approach, the CA-based optimizer is combined with a sewer hydraulic simulator, the EPA Storm Water Management Model (SWMM). At each optimization step, according to a set of transition rules, the optimizer updates all decision variables simultaneously based on the hydraulic situation within each neighbourhood. Two sewer networks (one small artificial network and one large real network) have been tested in this study. The CA optimizer demonstrated its ability to obtain near-optimal solutions in a remarkably small number of computational steps in a comparison of its performance with that of a genetic algorithm.
NASA Astrophysics Data System (ADS)
Hellouin de Menibus, Benjamin; Sablik, Mathieu
2017-06-01
This article introduces new tools to study self-organisation in a family of simple cellular automata which contain some particle-like objects with good collision properties (coalescence) in their time evolution. We draw an initial configuration at random according to some initial shift-ergodic measure, and use the limit measure to describe the asymptotic behaviour of the automata. We first take a qualitative approach, i.e. we obtain information on the limit measure(s). We prove that only particles moving in one particular direction can persist asymptotically. This provides some previously unknown information on the limit measures of various deterministic and probabilistic cellular automata: 3 and 4-cyclic cellular automata [introduced by Fisch (J Theor Probab 3(2):311-338, 1990; Phys D 45(1-3):19-25, 1990)], one-sided captive cellular automata [introduced by Theyssier (Captive Cellular Automata, 2004)], the majority-traffic cellular automaton, a self stabilisation process towards a discrete line [introduced by Regnault and Rémila (in: Mathematical Foundations of Computer Science 2015—40th International Symposium, MFCS 2015, Milan, Italy, Proceedings, Part I, 2015)]. In a second time we restrict our study to a subclass, the gliders cellular automata. For this class we show quantitative results, consisting in the asymptotic law of some parameters: the entry times [generalising K ůrka et al. (in: Proceedings of AUTOMATA, 2011)], the density of particles and the rate of convergence to the limit measure.
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
Perceptions of teaching and learning automata theory in a college-level computer science course
NASA Astrophysics Data System (ADS)
Weidmann, Phoebe Kay
This dissertation identifies and describes student and instructor perceptions that contribute to effective teaching and learning of Automata Theory in a competitive college-level Computer Science program. Effective teaching is the ability to create an appropriate learning environment in order to provide effective learning. We define effective learning as the ability of a student to meet instructor set learning objectives, demonstrating this by passing the course, while reporting a good learning experience. We conducted our investigation through a detailed qualitative case study of two sections (118 students) of Automata Theory (CS 341) at The University of Texas at Austin taught by Dr. Lily Quilt. Because Automata Theory has a fixed curriculum in the sense that many curricula and textbooks agree on what Automata Theory contains, differences being depth and amount of material to cover in a single course, a case study would allow for generalizable findings. Automata Theory is especially problematic in a Computer Science curriculum since students are not experienced in abstract thinking before taking this course, fail to understand the relevance of the theory, and prefer classes with more concrete activities such as programming. This creates a special challenge for any instructor of Automata Theory as motivation becomes critical for student learning. Through the use of student surveys, instructor interviews, classroom observation, material and course grade analysis we sought to understand what students perceived, what instructors expected of students, and how those perceptions played out in the classroom in terms of structure and instruction. Our goal was to create suggestions that would lead to a better designed course and thus a higher student success rate in Automata Theory. We created a unique theoretical basis, pedagogical positivism, on which to study college-level courses. Pedagogical positivism states that through examining instructor and student perceptions
Link prediction based on temporal similarity metrics using continuous action set learning automata
NASA Astrophysics Data System (ADS)
Moradabadi, Behnaz; Meybodi, Mohammad Reza
2016-10-01
Link prediction is a social network research area that tries to predict future links using network structure. The main approaches in this area are based on predicting future links using network structure at a specific period, without considering the links behavior through different periods. For example, a common traditional approach in link prediction calculates a chosen similarity metric for each non-connected link and outputs the links with higher similarity scores as the prediction result. In this paper, we propose a new link prediction method based on temporal similarity metrics and Continuous Action set Learning Automata (CALA). The proposed method takes advantage of using different similarity metrics as well as different time periods. In the proposed algorithm, we try to model the link prediction problem as a noisy optimization problem and use a team of CALAs to solve the noisy optimization problem. CALA is a reinforcement based optimization tool which tries to learn the optimal behavior from the environment feedbacks. To determine the importance of different periods and similarity metrics on the prediction result, we define a coefficient for each of different periods and similarity metrics and use a CALA for each coefficient. Each CALA tries to learn the true value of the corresponding coefficient. Final link prediction is obtained from a combination of different similarity metrics in different times based on the obtained coefficients. The link prediction results reported here show satisfactory of the proposed method for some social network data sets.
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.
Apostolico, A; Bejerano, G
2000-01-01
Statistical modeling of sequences is a central paradigm of machine learning that finds multiple uses in computational molecular biology and many other domains. The probabilistic automata typically built in these contexts are subtended by uniform, fixed-memory Markov models. In practice, such automata tend to be unnecessarily bulky and computationally imposing both during their synthesis and use. Recently, D. Ron, Y. Singer, and N. Tishby built much more compact, tree-shaped variants of probabilistic automata under the assumption of an underlying Markov process of variable memory length. These variants, called Probabilistic Suffix Trees (PSTs) were subsequently adapted by G. Bejerano and G. Yona and applied successfully to learning and prediction of protein families. The process of learning the automaton from a given training set S of sequences requires theta(Ln2) worst-case time, where n is the total length of the sequences in S and L is the length of a longest substring of S to be considered for a candidate state in the automaton. Once the automaton is built, predicting the likelihood of a query sequence of m characters may cost time theta(m2) in the worst case. The main contribution of this paper is to introduce automata equivalent to PSTs but having the following properties: Learning the automaton, for any L, takes O (n) time. Prediction of a string of m symbols by the automaton takes O (m) time. Along the way, the paper presents an evolving learning scheme and addresses notions of empirical probability and related efficient computation, which is a by-product possibly of more general interest.
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.
MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali
2017-01-01
Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms.
MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali
2017-01-01
Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms. PMID:28979308
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.
Li, Ming; Miao, Chunyan; Leung, Cyril
2015-12-04
Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches.
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
Modeling a student-classroom interaction in a tutorial-like system using learning automata.
Oommen, B John; Hashem, M Khaled
2010-02-01
Almost all of the learning paradigms used in machine learning, learning automata (LA), and learning theory, in general, use the philosophy of a Student (learning mechanism) attempting to learn from a teacher. This paradigm has been generalized in a myriad of ways, including the scenario when there are multiple teachers or a hierarchy of mechanisms that collectively achieve the learning. In this paper, we consider a departure from this paradigm by allowing the Student to be a member of a classroom of Students, where, for the most part, we permit each member of the classroom not only to learn from the teacher(s) but also to "extract" information from any of his fellow Students. This paper deals with issues concerning the modeling, decision-making process, and testing of such a scenario within the LA context. The main result that we show is that a weak learner can actually benefit from this capability of utilizing the information that he gets from a superior colleague-if this information transfer is done appropriately. As far as we know, the whole concept of Students learning from both a teacher and from a classroom of Students is novel and unreported in the literature. The proposed Student-classroom interaction has been tested for numerous strategies and for different environments, including the established benchmarks, and the results show that Students can improve their learning by interacting with each other. For example, for some interaction strategies, a weak Student can improve his learning by up to 73% when interacting with a classroom of Students, which includes Students of various capabilities. In these interactions, the Student does not have a priori knowledge of the identity or characteristics of the Students who offer their assistance.
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 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.
Statistical learning and the challenge of syntax: Beyond finite state automata
NASA Astrophysics Data System (ADS)
Elman, Jeff
2003-10-01
Over the past decade, it has been clear that even very young infants are sensitive to the statistical structure of language input presented to them, and use the distributional regularities to induce simple grammars. But can such statistically-driven learning also explain the acquisition of more complex grammar, particularly when the grammar includes recursion? Recent claims (e.g., Hauser, Chomsky, and Fitch, 2002) have suggested that the answer is no, and that at least recursion must be an innate capacity of the human language acquisition device. In this talk evidence will be presented that indicates that, in fact, statistically-driven learning (embodied in recurrent neural networks) can indeed enable the learning of complex grammatical patterns, including those that involve recursion. When the results are generalized to idealized machines, it is found that the networks are at least equivalent to Push Down Automata. Perhaps more interestingly, with limited and finite resources (such as are presumed to exist in the human brain) these systems demonstrate patterns of performance that resemble those in humans.
Consequences of landscape fragmentation on Lyme disease risk: a cellular automata approach.
Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O
2012-01-01
The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial
Consequences of Landscape Fragmentation on Lyme Disease Risk: A Cellular Automata Approach
Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O.
2012-01-01
The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial
Misra, Sudip; Oommen, B John; Yanamandra, Sreekeerthy; Obaidat, Mohammad S
2010-02-01
In this paper, we present a learning-automata-like The reason why the mechanism is not a pure LA, but rather why it yet mimics one, will be clarified in the body of this paper. (LAL) mechanism for congestion avoidance in wired networks. Our algorithm, named as LAL Random Early Detection (LALRED), is founded on the principles of the operations of existing RED congestion-avoidance mechanisms, augmented with a LAL philosophy. The primary objective of LALRED is to optimize the value of the average size of the queue used for congestion avoidance and to consequently reduce the total loss of packets at the queue. We attempt to achieve this by stationing a LAL algorithm at the gateways and by discretizing the probabilities of the corresponding actions of the congestion-avoidance algorithm. At every time instant, the LAL scheme, in turn, chooses the action that possesses the maximal ratio between the number of times the chosen action is rewarded and the number of times that it has been chosen. In LALRED, we simultaneously increase the likelihood of the scheme converging to the action, which minimizes the number of packet drops at the gateway. Our approach helps to improve the performance of congestion avoidance by adaptively minimizing the queue-loss rate and the average queue size. Simulation results obtained using NS2 establish the improved performance of LALRED over the traditional RED methods which were chosen as the benchmarks for performance comparison purposes.
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.
NASA Astrophysics Data System (ADS)
Pandey, Ras B.
1998-03-01
A stochastic cellular automata (SCA) approach is introduced to study the growth and decay of cellular population in an immune response model relevant to HIV. Four cell types are considered: macrophages (M), helper cells (H), cytotoxic cells (C), and viral infected cells (V). Mobility of the cells is introduced and viral mutation is considered probabilistically. In absence of mutation, the population of the host cells, helper (N_H) and cytotxic (N_C) cells in particular, dominates over the viral population (N_V), i.e., N_H, NC > N_V, the immune system wins over the viral infection. Variation of cellular population with time exhibits oscillations. The amplitude of oscillations in variation of N_H, NC and NV with time decreases at high mobility even at low viral mutation; the rate of viral growth is nonmonotonic with NV > N_H, NC in the long time regime. The viral population is much higher than that of the host cells at higher mutation rate, a possible cause of AIDS.
Design pattern mining using distributed learning automata and DNA sequence alignment.
Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina
2014-01-01
Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.
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
Efficient Algorithms for Handling Nondeterministic Automata
NASA Astrophysics Data System (ADS)
Vojnar, Tomáš
Finite (word, tree, or omega) automata play an important role in different areas of computer science, including, for instance, formal verification. Often, deterministic automata are used for which traditional algorithms for important operations such as minimisation and inclusion checking are available. However, the use of deterministic automata implies a need to determinise nondeterministic automata that often arise during various computations even when the computations start with deterministic automata. Unfortunately, determinisation is a very expensive step since deterministic automata may be exponentially bigger than the original nondeterministic automata. That is why, it appears advantageous to avoid determinisation and work directly with nondeterministic automata. This, however, brings a need to be able to implement operations traditionally done on deterministic automata on nondeterministic automata instead. In particular, this is the case of inclusion checking and minimisation (or rather reduction of the size of automata). In the talk, we review several recently proposed techniques for inclusion checking on nondeterministic finite word and tree automata as well as Büchi automata. These techniques are based on using the so called antichains, possibly combined with a use of suitable simulation relations (and, in the case of Büchi automata, the so called Ramsey-based or rank-based approaches). Further, we discuss techniques for reducing the size of nondeterministic word and tree automata using quotienting based on the recently proposed notion of mediated equivalences. The talk is based on several common works with Parosh Aziz Abdulla, Ahmed Bouajjani, Yu-Fang Chen, Peter Habermehl, Lisa Kaati, Richard Mayr, Tayssir Touili, Lorenzo Clemente, Lukáš Holík, and Chih-Duo Hong.
Social interactions of eating behaviour among high school students: a cellular automata approach.
Dabbaghian, Vahid; Mago, Vijay K; Wu, Tiankuang; Fritz, Charles; Alimadad, Azadeh
2012-10-09
Overweight and obesity in children and adolescents is a global epidemic posing problems for both developed and developing nations. The prevalence is particularly alarming in developed nations, such as the United States, where approximately one in three school-aged adolescents (ages 12-19) are overweight or obese. Evidence suggests that weight gain in school-aged adolescents is related to energy imbalance exacerbated by the negative aspects of the school food environment, such as presence of unhealthy food choices. While a well-established connection exists between the food environment, presently there is a lack of studies investigating the impact of the social environment and associated interactions of school-age adolescents. This paper uses a mathematical modelling approach to explore how social interactions among high school adolescents can affect their eating behaviour and food choice. In this paper we use a Cellular Automata (CA) modelling approach to explore how social interactions among school-age adolescents can affect eating behaviour, and food choice. Our CA model integrates social influences and transition rules to simulate the way individuals would interact in a social community (e.g., school cafeteria). To replicate these social interactions, we chose the Moore neighbourhood which allows all neighbours (eights cells in a two-dimensional square lattice) to influence the central cell. Our assumption is that individuals belong to any of four states; Bring Healthy, Bring Unhealthy, Purchase Healthy, and Purchase Unhealthy, and will influence each other according to parameter settings and transition rules. Simulations were run to explore how the different states interact under varying parameter settings. This study, through simulations, illustrates that students will change their eating behaviour from unhealthy to healthy as a result of positive social and environmental influences. In general, there is one common characteristic of changes across time
Social interactions of eating behaviour among high school students: a cellular automata approach
2012-01-01
Background Overweight and obesity in children and adolescents is a global epidemic posing problems for both developed and developing nations. The prevalence is particularly alarming in developed nations, such as the United States, where approximately one in three school-aged adolescents (ages 12-19) are overweight or obese. Evidence suggests that weight gain in school-aged adolescents is related to energy imbalance exacerbated by the negative aspects of the school food environment, such as presence of unhealthy food choices. While a well-established connection exists between the food environment, presently there is a lack of studies investigating the impact of the social environment and associated interactions of school-age adolescents. This paper uses a mathematical modelling approach to explore how social interactions among high school adolescents can affect their eating behaviour and food choice. Methods In this paper we use a Cellular Automata (CA) modelling approach to explore how social interactions among school-age adolescents can affect eating behaviour, and food choice. Our CA model integrates social influences and transition rules to simulate the way individuals would interact in a social community (e.g., school cafeteria). To replicate these social interactions, we chose the Moore neighbourhood which allows all neighbours (eights cells in a two-dimensional square lattice) to influence the central cell. Our assumption is that individuals belong to any of four states; Bring Healthy, Bring Unhealthy, Purchase Healthy, and Purchase Unhealthy, and will influence each other according to parameter settings and transition rules. Simulations were run to explore how the different states interact under varying parameter settings. Results This study, through simulations, illustrates that students will change their eating behaviour from unhealthy to healthy as a result of positive social and environmental influences. In general, there is one common characteristic of
López, Leonardo; Burguerner, Germán; Giovanini, Leonardo
2014-04-12
The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the
Ship interaction in narrow water channels: A two-lane cellular automata approach
NASA Astrophysics Data System (ADS)
Sun, Zhuo; Chen, Zhonglong; Hu, Hongtao; Zheng, Jianfeng
2015-08-01
In narrow waterways, closed ships might interact due to hydrodynamic forces. To avoid clashes, different lane-changing rules are required. In this paper, a two-lane cellular automata model is proposed to investigate the traffic flow patterns in narrow water channels. Numerical experiments show that ship interaction can form "lumps" in traffic flow which will significantly depress the flux. We suggest that the lane-changing frequency of fast ships should be limited.
2014-01-01
Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area
Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach.
Kumar, Anand; Ligatti, Jay; Tu, Yi-Cheng
2015-11-01
Privacy and usage restriction issues are important when valuable data are exchanged or acquired by different organizations. Standard access control mechanisms either restrict or completely grant access to valuable data. On the other hand, data obfuscation limits the overall usability and may result in loss of total value. There are no standard policy enforcement mechanisms for data acquired through mutual and copyright agreements. In practice, many different types of policies can be enforced in protecting data privacy. Hence there is the need for an unified framework that encapsulates multiple suites of policies to protect the data. We present our vision of an architecture named security automata model (SAM) to enforce privacy-preserving policies and usage restrictions. SAM analyzes the input queries and their outputs to enforce various policies, liberating data owners from the burden of monitoring data access. SAM allows administrators to specify various policies and enforces them to monitor queries and control the data access. Our goal is to address the problems of data usage control and protection through privacy policies that can be defined, enforced, and integrated with the existing access control mechanisms using SAM. In this paper, we lay out the theoretical foundation of SAM, which is based on an automata named Mandatory Result Automata. We also discuss the major challenges of implementing SAM in a real-world database environment as well as ideas to meet such challenges.
NASA Astrophysics Data System (ADS)
Heng, Fong Wan; Siang, Gan Yee; Sarmin, Nor Haniza; Turaev, Sherzod
2014-06-01
Recently, the relation of automata and groups has been studied. It was shown that properties of groups can be studied using state diagrams of modified automata and modified Watson-Crick automata. In this work, we investigate the relation of subgroups with the modified finite and Watson-Crick automata. We also establish the conditions for the recognition of subgroups by using the modified automata.
Simulation of abrasive water jet cutting process: Part 2. Cellular automata approach
NASA Astrophysics Data System (ADS)
Orbanic, Henri; Junkar, Mihael
2004-11-01
A new two-dimensional cellular automata (CA) model for the simulation of the abrasive water jet (AWJ) cutting process is presented. The CA calculates the shape of the cutting front, which can be used as an estimation of the surface quality. The cutting front is formed based on material removal rules and AWJ propagation rules. The material removal rule calculates when a particular part of the material will be removed with regard to the energy of AWJ. The AWJ propagation rule calculates the distribution of AWJ energy through CA by using a weighted average. The modelling with CA also provides a visual narrative of the moving of the cutting front, which is hard to observe in real process. The algorithm is fast and has been successfully tested in comparison to cutting fronts obtained with cutting experiments of aluminium alloy.
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.
NASA Astrophysics Data System (ADS)
Liucci, Luisa; Melelli, Laura; Suteanu, Cristian; Ponziani, Francesco
2017-08-01
Power law scaling has been widely observed in the frequency distribution of landslide sizes. The exponent of the power-law characterizes the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. The reason for the universal scaling behavior of landslides is still debated and the role of topography has been explored in terms of possible explanation for this type of behavior. We built a simple cellular automata model to investigate this issue, as well as the relationships between the scaling properties of landslide areas and the changes suffered by the topographic surface affected by landslides. The dynamics of the model is controlled by a temporal rate of weakening, which drives the system to instability, and by topography, which defines both the quantity of the displaced mass and the direction of the movement. Results show that the model is capable of reproducing the scaling behavior of real landslide areas and suggest that topography is a good candidate to explain their scale-invariance. In the model, the values of the scaling exponents depend on how fast the system is driven to instability; they are less sensitive to the duration of the driving rate, thus suggesting that the probability of landslide areas could depend on the intensity of the triggering mechanism rather than on its duration, and on the topographic setting of the area. Topography preserves the information concerning the statistical distribution of areas of landslides caused by a driving mechanism of given intensity and duration.
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.
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.
Approaches to Machine Learning.
1984-02-16
The field of machine learning strives to develop methods and techniques to automatic the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition. We illustrate each of the basic approaches with paradigmatic examples. (Author)
Granmo, Ole-Christoffer; Oommen, B John; Myrer, Svein Arild; Olsen, Morten Goodwin
2007-02-01
This paper considers the nonlinear fractional knapsack problem and demonstrates how its solution can be effectively applied to two resource allocation problems dealing with the World Wide Web. The novel solution involves a "team" of deterministic learning automata (LA). The first real-life problem relates to resource allocation in web monitoring so as to "optimize" information discovery when the polling capacity is constrained. The disadvantages of the currently reported solutions are explained in this paper. The second problem concerns allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. This is the scenario encountered when the user has to evaluate multiple web sites by accessing a limited number of web pages, and the proportions of interest are the fraction of each web site that is successfully validated by an HTML validator. Using the general LA paradigm to tackle both of the real-life problems, the proposed scheme improves a current solution in an online manner through a series of informed guesses that move toward the optimal solution. At the heart of the scheme, a team of deterministic LA performs a controlled random walk on a discretized solution space. Comprehensive experimental results demonstrate that the discretization resolution determines the precision of the scheme, and that for a given precision, the current solution (to both problems) is consistently improved until a nearly optimal solution is found--even for switching environments. Thus, the scheme, while being novel to the entire field of LA, also efficiently handles a class of resource allocation problems previously not addressed in the literature.
NASA Astrophysics Data System (ADS)
Dottori, F.; Todini, E.
2011-01-01
Over the last decade, several flood inundation models based on a reduced complexity approach have been developed and successfully applied in a wide range of practical cases. In the present paper, a model based on the cellular automata approach is analyzed in detail and tested in several numerical cases, comparing the results both with analytical solutions and different hydraulic models. In order to improve the model’s performance, the original code based on the diffusive wave equations and a constant time step scheme is modified through the implementation of two techniques available in literature: an inertial formulation for the computation of discharges, originally developed for the LISFLOOD-FP model by Bates et al. (2010); and the incorporation of a local adaptive time step algorithm, based on a technique originally presented by Zhang et al. (1994). The analysis of the numerical cases showed that the proposed model can be a valuable tool for the simulation of flood inundation events. When applied to one-dimensional numerical cases, the model well reproduced the wave propagation, whereas it showed some limitations in reproducing two-dimensional flow dynamics in respect to a model based on the full shallow water equations. However, differences were found to be comparable with the uncertainty level related to available data for actual flood events. The use of the inertial formulation was very effective in all the cases, and reduced run time up to 97% as compared with the diffusive formulation, although it did not improve the overall accuracy of results. Finally, the incorporation of the local time step algorithm produced a speedup from 1.2 x to 4 x, depending on the simulation and the model version in use, with no loss of accuracy in the results.
Cellular automata and its applications in protein bioinformatics.
Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen
2011-09-01
With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.
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.
A cellular automata model for social-learning processes in a classroom context
NASA Astrophysics Data System (ADS)
Bordogna, C. M.; Albano, E. V.
2002-02-01
A model for teaching-learning processes that take place in the classroom is proposed and simulated numerically. Recent ideas taken from the fields of sociology, educational psychology, statistical physics and computational science are key ingredients of the model. Results of simulations are consistent with well-established empirical results obtained in classrooms by means of different evaluation tools. It is shown that students engaged in collaborative groupwork reach higher achievements than those attending traditional lectures only. However, in many cases, this difference is subtle and consequently very difficult to be detected using tests. The influence of the number of students forming the collaborative groups on the average knowledge achieved is also studied and discussed.
Knot Invariants and Cellular Automata
1993-05-04
lattice gases. Since our approach equates the spacetime evolution of a dynamical system with an equilibrium configuration of a statistical mechanics...model in one higher dimension, a model of ’t Hooft for two dimensional spacetime with discrete local coordinate invariance was a natural inspiration [5...thermodynamic equilibrium, as well as demonstrating the efficacy of constructing and analyzing lattice gas automata according to ( spacetime ) symmetry principles
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.
Verifying Safety Properties Using Non-Deterministic Infinite-State Automata
1989-09-08
automata [18]. Sistla proved that the verifi- cation problem for unbounded non-deterministic automata is II -completeJ [15]. For languages over...restrain stuttering and allow time-bounded and unbounded stuttering when needed, we prefer these automata. Using a similar approach as in [1], Sistla ...Concurrent Programs by V-automata. Proc. Fourteenth Symp. on the Principles of Programming Languages, ACM, 1987, pp. 1-12. [15] Sistla , A.P. On Verifying
Automata representation for Abelian groups
NASA Astrophysics Data System (ADS)
Fong, Wan Heng; Gan, Yee Siang; Sarmin, Nor Haniza; Turaev, Sherzod
2013-04-01
A finite automaton is one of the classic models of recognition devices, which is used to determine the type of language a string belongs to. A string is said to be recognized by a finite automaton if the automaton "reads" the string from the left to the right starting from the initial state and finishing at a final state. Another type of automata which is a counterpart of sticker systems, namely Watson-Crick automata, is finite automata which can scan the double-stranded tapes of DNA strings using the complimentary relation. The properties of groups have been extended for the recognition of finite automata over groups. In this paper, two variants of automata, modified deterministic finite automata and modified deterministic Watson-Crick automata are used in the study of Abelian groups. Moreover, the relation between finite automata diagram over Abelian groups and the Cayley table is introduced. In addition, some properties of Abelian groups are presented in terms of automata.
Plasmonic Nanostructured Cellular Automata
NASA Astrophysics Data System (ADS)
Alkhazraji, Emad; Ghalib, A.; Manzoor, K.; Alsunaidi, M. A.
2017-03-01
In this work, we have investigated the scattering plasmonic resonance characteristics of silver nanospheres with a geometrical distribution that is modelled by Cellular Automata using time-domain numerical analysis. Cellular Automata are discrete mathematical structures that model different natural phenomena. Two binary one-dimensional Cellular Automata rules are considered to model the nanostructure, namely rule 30 and rule 33. The analysis produces three-dimensional scattering profiles of the entire plasmonic nanostructure. For the Cellular Automaton rule 33, the introduction of more Cellular Automata generations resulted only in slight red and blue shifts in the plasmonic modes with respect to the first generation. On the other hand, while rule 30 introduced significant red shifts in the resonance peaks at early generations, at later generations however, a peculiar effect is witnessed in the scattering profile as new peaks emerge as a feature of the overall Cellular Automata structure rather than the sum of the smaller parts that compose it. We strongly believe that these features that emerge as a result adopting the different 256 Cellular Automata rules as configuration models of nanostructures in different applications and systems might possess a great potential in enhancing their capability, sensitivity, efficiency, and power utilization.
ERIC Educational Resources Information Center
WIENS, JACOB H.
TO PERMIT COMPARATIVE ANALYSIS FOR PURPOSES OF EDUCATIONAL PLANNING AT SAN MATEO, FIVE INSTITUTIONS WITH SYSTEMS PROGRAMS ARE EVALUATED ON THE BASIS OF TRIP NOTES. OAKLAND COMMUNITY COLLEGE HAS BEEN COMPLETELY ORGANIZED AROUND THE VOLUNTARY WORK-STUDY LABORATORY APPROACH TO LEARNING. ORAL ROBERTS UNIVERSITY, OKLAHOMA CHRISTIAN COLLEGE, HENRY FORD…
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.
Synchronization of Regular Automata
NASA Astrophysics Data System (ADS)
Caucal, Didier
Functional graph grammars are finite devices which generate the class of regular automata. We recall the notion of synchronization by grammars, and for any given grammar we consider the class of languages recognized by automata generated by all its synchronized grammars. The synchronization is an automaton-related notion: all grammars generating the same automaton synchronize the same languages. When the synchronizing automaton is unambiguous, the class of its synchronized languages forms an effective boolean algebra lying between the classes of regular languages and unambiguous context-free languages. We additionally provide sufficient conditions for such classes to be closed under concatenation and its iteration.
Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin
2017-06-15
Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.
Immune Responses: Getting Close to Experimental Results with Cellular Automata Models
NASA Astrophysics Data System (ADS)
Dos Santos, Rita Maria Zorzenon
Cellular automata approaches are powerful tools to model local and nonlocal interactions generating cooperative behavior. In the last decade, the question of whether cellular automata could embed realistic assumptions about the interactions among cells and molecules of the immune system was quite controversial. Recent results have shown that it is possible to use cellular automata approaches to describe realistically the interactions between the elements of the immune system. The first models using cellular automata approaches, boolean and threshold or window automata, were based on experimental evidence and were mainly used to understand the logic of global immune responses like immunization, tolerance, paralysis, etc. Recently, new classes of cellular automata models which include time delay, stochasticity or adaptation have lead to results that can be compared with in vivo experimental data.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Behera, Mukunda D.; Borate, Santosh N.; Panda, Sudhindra N.; Behera, Priti R.; Roy, Partha S.
2012-08-01
Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)-Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socio-economic drivers including residential/industrial development, road-rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.
Actin Automata: Phenomenology and Localizations
NASA Astrophysics Data System (ADS)
Adamatzky, Andrew; Mayne, Richard
Actin is a globular protein which forms long filaments in the eukaryotic cytoskeleton, whose roles in cell function include structural support, contractile activity to intracellular signaling. We model actin filaments as two chains of one-dimensional binary-state semi-totalistic automaton arrays to describe hypothetical signaling events therein. Each node of the actin automaton takes state "0" (resting) or "1" (excited) and updates its state in discrete time depending on its neighbor's states. We analyze the complete rule space of actin automata using integral characteristics of space-time configurations generated by these rules and compute state transition rules that support traveling and mobile localizations. Approaches towards selection of the localization supporting rules using the global characteristics are outlined. We find that some properties of actin automata rules may be predicted using Shannon entropy, activity and incoherence of excitation between the polymer chains. We also show that it is possible to infer whether a given rule supports traveling or stationary localizations by looking at ratios of excited neighbors that are essential for generations of the localizations. We conclude by applying biomolecular hypotheses to this model and discuss the significance of our findings in context with cell signaling and emergent behavior in cellular computation.
Weighted Automata and Weighted Logics
NASA Astrophysics Data System (ADS)
Droste, Manfred; Gastin, Paul
In automata theory, a fundamental result of Büchi and Elgot states that the recognizable languages are precisely the ones definable by sentences of monadic second order logic. We will present a generalization of this result to the context of weighted automata. We develop syntax and semantics of a quantitative logic; like the behaviors of weighted automata, the semantics of sentences of our logic are formal power series describing ‘how often’ the sentence is true for a given word. Our main result shows that if the weights are taken in an arbitrary semiring, then the behaviors of weighted automata are precisely the series definable by sentences of our quantitative logic. We achieve a similar characterization for weighted Büchi automata acting on infinite words, if the underlying semiring satisfies suitable completeness assumptions. Moreover, if the semiring is additively locally finite or locally finite, then natural extensions of our weighted logic still have the same expressive power as weighted automata.
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.
Designing for Learning: An Active Learning Approach
ERIC Educational Resources Information Center
Coelho, Jeffrey D.
2005-01-01
An active learning environment is one in which students are able to "seek" out new experiences, "interpret" them, and "relate" them to previous experiences. This approach allows students to engage in independent thinking, problem solving, and guided discovery as they explore broad movement concepts. An active learning means that students are…
Using cellular automata to generate image representation for biological sequences.
Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C
2005-02-01
A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.
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.
Evolution of cellular automata with memory: The Density Classification Task.
Stone, Christopher; Bull, Larry
2009-08-01
The Density Classification Task is a well known test problem for two-state discrete dynamical systems. For many years researchers have used a variety of evolutionary computation approaches to evolve solutions to this problem. In this paper, we investigate the evolvability of solutions when the underlying Cellular Automaton is augmented with a type of memory based on the Least Mean Square algorithm. To obtain high performance solutions using a simple non-hybrid genetic algorithm, we design a novel representation based on the ternary representation used for Learning Classifier Systems. The new representation is found able to produce superior performance to the bit string traditionally used for representing Cellular automata. Moreover, memory is shown to improve evolvability of solutions and appropriate memory settings are able to be evolved as a component part of these solutions.
Learning Approach and Learning: Exploring a New Technological Learning System
ERIC Educational Resources Information Center
Aflalo, Ester; Gabay, Eyal
2013-01-01
This study furthers the understanding of the connections between learning approaches and learning. The research population embraced 44 males from the Jewish ultraorthodox community, who abide by distinct methods of study. One group follows the very didactic, linear and structured approach of a methodical and gradual order, while the second group…
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.
Multipebble Simulations for Alternating Automata
NASA Astrophysics Data System (ADS)
Clemente, Lorenzo; Mayr, Richard
We study generalized simulation relations for alternating Büchi automata (ABA), as well as alternating finite automata. Having multiple pebbles allows the Duplicator to "hedge her bets" and delay decisions in the simulation game, thus yielding a coarser simulation relation. We define (k 1,k 2)-simulations, with k 1/k 2 pebbles on the left/right, respectively. This generalizes previous work on ordinary simulation (i.e., (1,1)-simulation) for nondeterministic Büchi automata (NBA)[4] in and ABA in [5], and (1,k)-simulation for NBA in [3].
Clemente-Juan, Juan Modesto; Palii, Andrew; Coronado, Eugenio; Tsukerblat, Boris
2016-08-09
In this article, we focus on the electron-vibrational problem of the tetrameric mixed-valence (MV) complexes proposed for implementation as four-dot molecular quantum cellular automata (mQCA).1 Although the adiabatic approximation explored in ref 2 is an appropriate tool for the qualitative analysis of the basic characteristics of mQCA, like vibronic trapping of the electrons encoding binary information and cell-cell response, it loses its accuracy providing moderate vibronic coupling and fails in the description of the discrete pattern of the vibronic levels. Therefore, a precise solution of the quantum-mechanical vibronic problem is of primary importance for the evaluation of the shapes of the electron transfer optical absorption bands and quantitative analysis of the main parameters of tetrameric quantum cells. Here, we go beyond the Born-Oppenheimer paradigm and present a solution of the quantum-mechanical pseudo Jahn-Teller (JT) vibronic problem in bielectronic MV species (exemplified by the tetra-ruthenium complexes) based on the recently developed symmetry-assisted approach.3,4 The mathematical approach to the vibronic eigenproblem takes into consideration the point symmetry basis, and therefore, the total matrix of the JT Hamiltonian is blocked to the maximum extent. The submatrices correspond to the irreducible representations (irreps) of the point group. With this tool, we also extend the theory of the mQCA cell beyond the limit of prevailing Coulomb repulsion in the electronic pair (adopted in ref 2), and therefore, the general pseudo-JT problems for spin-singlet ((1)B1g, 2(1)A1g, (1)B2g, (1)Eu) ⊗ (b1g + eu) and spin-triplet states ((3)A2g, (3)B1g, 2(3)Eu) ⊗ (b1g + eu) in a square-planar bielectronic system are solved. The obtained symmetry-adapted electron-vibrational functions are employed for the calculation of the profiles (shape functions) of the charge transfer absorption bands in the tetrameric MV complexes and for the discussion of the
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.
Modeling and analyzing mixed reality applications using timed automata
NASA Astrophysics Data System (ADS)
Didier, Jean-Yves; Djafri, Bachir; Klaudel, Hanna
2008-06-01
We propose a compositional modeling framework for Mixed Reality (MR) software architectures in order to express, simulate and validate formally the real-time properties of such systems. Our approach is first based on a functional decomposition of such systems into generic components. The obtained elements as well as their typical interactions give rise to generic representations in terms of timed automata. A whole application is then obtained as a composition of such defined components. The approach is illustrated on a case study modeled by timed automata synchronizing through channels and including a large number of time constraints. This system has been simulated in UPPAAL and checked against basic behavioral properties.
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.
Integrated approaches to perceptual learning.
Jacobs, Robert A
2010-04-01
New technologies and new ways of thinking have recently led to rapid expansions in the study of perceptual learning. We describe three themes shared by many of the nine articles included in this topic on Integrated Approaches to Perceptual Learning. First, perceptual learning cannot be studied on its own because it is closely linked to other aspects of cognition, such as attention, working memory, decision making, and conceptual knowledge. Second, perceptual learning is sensitive to both the stimulus properties of the environment in which an observer exists and to the properties of the tasks that the observer needs to perform. Moreover, the environmental and task properties can be characterized through their statistical regularities. Finally, the study of perceptual learning has important implications for society, including implications for science education and medical rehabilitation. Contributed articles relevant to each theme are summarized.
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
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.
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
Toward a Social Approach to Learning in Community Service Learning
ERIC Educational Resources Information Center
Cooks, Leda; Scharrer, Erica; Paredes, Mari Castaneda
2004-01-01
The authors describe a social approach to learning in community service learning that extends the contributions of three theoretical bodies of scholarship on learning: social constructionism, critical pedagogy, and community service learning. Building on the assumptions about learning described in each of these areas, engagement, identity, and…
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…
Blended Learning: An Innovative Approach
ERIC Educational Resources Information Center
Lalima; Dangwal, Kiran Lata
2017-01-01
Blended learning is an innovative concept that embraces the advantages of both traditional teaching in the classroom and ICT supported learning including both offline learning and online learning. It has scope for collaborative learning; constructive learning and computer assisted learning (CAI). Blended learning needs rigorous efforts, right…
Scalable asynchronous execution of cellular automata
NASA Astrophysics Data System (ADS)
Folino, Gianluigi; Giordano, Andrea; Mastroianni, Carlo
2016-10-01
The performance and scalability of cellular automata, when executed on parallel/distributed machines, are limited by the necessity of synchronizing all the nodes at each time step, i.e., a node can execute only after the execution of the previous step at all the other nodes. However, these synchronization requirements can be relaxed: a node can execute one step after synchronizing only with the adjacent nodes. In this fashion, different nodes can execute different time steps. This can be a notable advantageous in many novel and increasingly popular applications of cellular automata, such as smart city applications, simulation of natural phenomena, etc., in which the execution times can be different and variable, due to the heterogeneity of machines and/or data and/or executed functions. Indeed, a longer execution time at a node does not slow down the execution at all the other nodes but only at the neighboring nodes. This is particularly advantageous when the nodes that act as bottlenecks vary during the application execution. The goal of the paper is to analyze the benefits that can be achieved with the described asynchronous implementation of cellular automata, when compared to the classical all-to-all synchronization pattern. The performance and scalability have been evaluated through a Petri net model, as this model is very useful to represent the synchronization barrier among nodes. We examined the usual case in which the territory is partitioned into a number of regions, and the computation associated with a region is assigned to a computing node. We considered both the cases of mono-dimensional and two-dimensional partitioning. The results show that the advantage obtained through the asynchronous execution, when compared to the all-to-all synchronous approach is notable, and it can be as large as 90% in terms of speedup.
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
NASA Astrophysics Data System (ADS)
Snider, Gregory
2000-03-01
Quantum-dot Cellular Automata (QCA) [1] is a promising architecture which employs quantum dots for digital computation. It is a revolutionary approach that holds the promise of high device density and low power dissipation. A basic QCA cell consists of four quantum dots coupled capacitively and by tunnel barriers. The cell is biased to contain two excess electrons within the four dots, which are forced to opposite "corners" of the four-dot cell by mutual Coulomb repulsion. These two possible polarization states of the cell will represent logic "0" and "1". Properly arranged, arrays of these basic cells can implement Boolean logic functions. Experimental results from functional QCA devices built of nanoscale metal dots defined by tunnel barriers will be presented. The experimental devices to be presented consist of Al islands, which we will call quantum dots, interconnected by tunnel junctions and lithographically defined capacitors. Aluminum/ aluminum-oxide/aluminum tunnel junctions were fabricated using a standard e-beam lithography and shadow evaporation technique. The experiments were performed in a dilution refrigerator at a temperature of 70 mK. The operation of a cell is evaluated by direct measurements of the charge state of dots within a cell as the input voltage is changed. The experimental demonstration of a functioning cell will be presented. A line of three cells demonstrates that there are no metastable switching states in a line of cells. A QCA majority gate will also be presented, which is a programmable AND/OR gate and represents the basic building block of QCA systems. The results of recent experiments will be presented. 1. C.S. Lent, P.D. Tougaw, W. Porod, and G.H. Bernstein, Nanotechnology, 4, 49 (1993).
Algebraic Systems and Pushdown Automata
NASA Astrophysics Data System (ADS)
Petre, Ion; Salomaa, Arto
We concentrate in this chapter on the core aspects of algebraic series, pushdown automata, and their relation to formal languages. We choose to follow here a presentation of their theory based on the concept of properness. We introduce in Sect. 2 some auxiliary notions and results needed throughout the chapter, in particular the notions of discrete convergence in semirings and C-cycle free infinite matrices. In Sect. 3 we introduce the algebraic power series in terms of algebraic systems of equations. We focus on interconnections with context-free grammars and on normal forms. We then conclude the section with a presentation of the theorems of Shamir and Chomsky-Schützenberger. We discuss in Sect. 4 the algebraic and the regulated rational transductions, as well as some representation results related to them. Section 5 is dedicated to pushdown automata and focuses on the interconnections with classical (non-weighted) pushdown automata and on the interconnections with algebraic systems. We then conclude the chapter with a brief discussion of some of the other topics related to algebraic systems and pushdown automata.
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…
Selective networks and recognition automata.
Reeke, G N; Edelman, G M
1984-01-01
The results we have presented demonstrate that a network based on a selective principle can function in the absence of forced learning or an a priori program to give recognition, classification, generalization, and association. While Darwin II is not a model of any actual nervous system, it does set out to solve one of the same problems that evolution had to solve--the need to form categories in a bottom-up manner from information in the environment, without incorporating the assumptions of any particular observer. The key features of the model that make this possible are (1) Darwin II incorporates selective networks whose initial specificities enable them to respond without instruction to unfamiliar stimuli; (2) degeneracy provides multiple possibilities of response to any one stimulus, at the same time providing functional redundancy against component failure; (3) the output of Darwin II is a pattern of response, making use of the simultaneous responses of multiple degenerate groups to avoid the need for very high specificity and the combinatorial disaster that would imply; (4) reentry within individual networks vitiates the limitations described by Minsky and Papert for a class of perceptual automata lacking such connections; and (5) reentry between intercommunicating networks with different functions gives rise to new functions, such as association, that either one alone could not display. The two kinds of network are roughly analogous to the two kinds of category formation that people use: Darwin, corresponding to the exemplar description of categories, and Wallace, corresponding to the probabilistic matching description of categories. These principles lead to a new class of pattern-recognizing machine of which Darwin II is just an example. There are a number of obvious extensions to this work that we are pursuing. These include giving Darwin II the capability to deal with stimuli that are in motion, an ability that probably precedes the ability of biological
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.
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.
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.
Learning Process Questionnaire Manual. Student Approaches to Learning and Studying.
ERIC Educational Resources Information Center
Biggs, John B.
This manual describes the theory behind the Learning Process Questionnaire (LPQ) used in Australia and defines what the subscale and scale scores mean. The LPQ is a 36-item self-report questionnaire that yields scores on three basic motives for learning and three learning strategies, and on the approaches to learning that are formed by these…
A Colloquial Approach: An Active Learning Technique.
ERIC Educational Resources Information Center
Arce, Pedro
1994-01-01
Addresses the problem of the effectiveness of teaching methodologies on fundamental engineering courses such as transport phenomena. Recommends the colloquial approach, an active learning strategy, to increase student involvement in the learning process. (ZWH)
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…
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…
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.
Classifying cellular automata using grossone
NASA Astrophysics Data System (ADS)
D'Alotto, Louis
2016-10-01
This paper proposes an application of the Infinite Unit Axiom and grossone, introduced by Yaroslav Sergeyev (see [7] - [12]), to the development and classification of one and two-dimensional cellular automata. By the application of grossone, new and more precise nonarchimedean metrics on the space of definition for one and two-dimensional cellular automata are established. These new metrics allow us to do computations with infinitesimals. Hence configurations in the domain space of cellular automata can be infinitesimally close (but not equal). That is, they can agree at infinitely many places. Using the new metrics, open disks are defined and the number of points in each disk computed. The forward dynamics of a cellular automaton map are also studied by defined sets. It is also shown that using the Infinite Unit Axiom, the number of configurations that follow a given configuration, under the forward iterations of cellular automaton maps, can now be computed and hence a classification scheme developed based on this computation.
Chua's Nonlinear Dynamics Perspective of Cellular Automata
NASA Astrophysics Data System (ADS)
Pazienza, Giovanni E.
2013-01-01
Chua's `Nonlinear Dynamics Perspective of Cellular Automata' represents a genuine breakthrough in this area and it has had a major impact on the recent scientific literature. His results have been accurately described in a series of fourteen papers appeared over the course of eight years but there is no compendious introduction to his work. Therefore, here for the first time, we present Chua's main ideas as well as a few unpublished results that have not been included in his previous papers. This overview illustrates the essence of Chua's work by using a clear terminology and a consistent notation, and it is aimed at those who want to approach this subject through a concise but thorough exposition.
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…
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"…
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.
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.
Optimal online learning: a Bayesian approach
NASA Astrophysics Data System (ADS)
Solla, Sara A.; Winther, Ole
1999-09-01
A recently proposed Bayesian approach to online learning is applied to learning a rule defined as a noisy single layer perceptron. In the Bayesian online approach, the exact posterior distribution is approximated by a simple parametric posterior that is updated online as new examples are incorporated to the dataset. In the case of binary weights, the approximate posterior is chosen to be a biased binary distribution. The resulting online algorithm is shown to outperform several other online approaches to this problem.
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.
Cellular automata for traffic simulations
NASA Astrophysics Data System (ADS)
Wolf, Dietrich E.
1999-02-01
Traffic phenomena such as the transition from free to congested flow, lane inversion and platoon formation can be accurately reproduced using cellular automata. Being computationally extremely efficient, they simulate large traffic systems many times faster than real time so that predictions become feasible. A riview of recent results is given. The presence of metastable states at the jamming transition is discussed in detail. A simple new cellular automation is introduced, in which the interaction between cars is Galilei-invariant. It is shown that this type of interaction accounts for metastable states in a very natural way.
Stochastic computing with biomolecular automata.
Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud
2004-07-06
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.
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 Approaches, Study Time and Academic Performance.
ERIC Educational Resources Information Center
Kember, David; And Others
1995-01-01
Investigation of the study habits and approaches to study tasks of 34 mechanical engineering students over the course of 1 week found that use of a surface approach to learning was positively correlated with high class attendance and greater study time, suggesting an inefficient approach. The research methodology used is found useful for…
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.
Learning Geometry through Discovery Learning Using a Scientific Approach
ERIC Educational Resources Information Center
In'am, Akhsanul; Hajar, Siti
2017-01-01
The objective of this present research is to analyze the implementation of learning geometry through a scientific learning consisting of three aspects: 1) teacher's activities, 2) students' activities and, 3) the achievement results. The adopted approach is a descriptive-quantitative one and the subject is the Class VII students of Islamic Junior…
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…
A Reinforcement Learning Approach to Control.
1997-05-31
acquisition is inherently a partially observable Markov decision problem. This report describes an efficient, scalable reinforcement learning approach to the...deployment of refined intelligent gaze control techniques. This report first lays a theoretical foundation for reinforcement learning . It then introduces...perform well in both high and low SNR ATR environments. Reinforcement learning coupled with history features appears to be both a sound foundation and a practical scalable base for gaze control.
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)
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)
A Guided Discovery Approach for Learning Glycolysis.
ERIC Educational Resources Information Center
Schultz, Emeric
1997-01-01
Argues that more attention should be given to teaching students how to learn the rudiments of specific metabolic pathways. This approach describes a unique way of learning the glycolytic pathway in stepwise fashion. The pedagogy involves clear rote components that are connected to a set of generalizations that develop and enhance important…
A Guided Discovery Approach for Learning Glycolysis.
ERIC Educational Resources Information Center
Schultz, Emeric
1997-01-01
Argues that more attention should be given to teaching students how to learn the rudiments of specific metabolic pathways. This approach describes a unique way of learning the glycolytic pathway in stepwise fashion. The pedagogy involves clear rote components that are connected to a set of generalizations that develop and enhance important…
Constructivist Learning Approach in Science Teaching
ERIC Educational Resources Information Center
Demirci, Cavide
2009-01-01
Constructivism is not a new concept. It has its roots in philosophy and has been applied to sociology and anthropology, as well as cognitive psychology and education. The aim of this research is to reveal if there is a significant difference between the means of achievement and retention learning scores of constructivist learning approach applied…
A Hybrid Approach to Active Learning.
ERIC Educational Resources Information Center
Ramsier, R. D.
2001-01-01
Describes an approach to incorporate active learning strategies into the first semester of a university-level introductory physics course. Combines cooperative and peer-based methods inside the classroom with project-based learning outside the classroom in an attempt to develop students' transferable skills as well as improving their understanding…
A Hybrid Approach to Active Learning.
ERIC Educational Resources Information Center
Ramsier, R. D.
2001-01-01
Describes an approach to incorporate active learning strategies into the first semester of a university-level introductory physics course. Combines cooperative and peer-based methods inside the classroom with project-based learning outside the classroom in an attempt to develop students' transferable skills as well as improving their understanding…
Constructivist Learning Approach in Science Teaching
ERIC Educational Resources Information Center
Demirci, Cavide
2009-01-01
Constructivism is not a new concept. It has its roots in philosophy and has been applied to sociology and anthropology, as well as cognitive psychology and education. The aim of this research is to reveal if there is a significant difference between the means of achievement and retention learning scores of constructivist learning approach applied…
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…
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)
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.
Reversibility of a Symmetric Linear Cellular Automata
NASA Astrophysics Data System (ADS)
Del Rey, A. Martín; Sánchez, G. Rodríguez
The characterization of the size of the cellular space of a particular type of reversible symmetric linear cellular automata is introduced in this paper. Specifically, it is shown that those symmetric linear cellular with 2k + 1 cells, and whose transition matrix is a k-diagonal square band matrix with nonzero entries equal to 1 are reversible. Furthermore, in this case the inverse cellular automata are explicitly computed. Moreover, the reversibility condition is also studied for a general number of cells.
A Transfer Learning Approach for Network Modeling
Huang, Shuai; Li, Jing; Chen, Kewei; Wu, Teresa; Ye, Jieping; Wu, Xia; Yao, Li
2012-01-01
Networks models have been widely used in many domains to characterize the interacting relationship between physical entities. A typical problem faced is to identify the networks of multiple related tasks that share some similarities. In this case, a transfer learning approach that can leverage the knowledge gained during the modeling of one task to help better model another task is highly desirable. In this paper, we propose a transfer learning approach, which adopts a Bayesian hierarchical model framework to characterize task relatedness and additionally uses the L1-regularization to ensure robust learning of the networks with limited sample sizes. A method based on the Expectation-Maximization (EM) algorithm is further developed to learn the networks from data. Simulation studies are performed, which demonstrate the superiority of the proposed transfer learning approach over single task learning that learns the network of each task in isolation. The proposed approach is also applied to identification of brain connectivity networks of Alzheimer’s disease (AD) from functional magnetic resonance image (fMRI) data. The findings are consistent with the AD literature. PMID:24526804
Diversity Learning: A Different Approach.
ERIC Educational Resources Information Center
Wilcox, Herbert S.; Waagbo, Jean M.
2001-01-01
Reports on the Community College of Baltimore County's (Maryland) service learning program for diversity education, which is unique to American community colleges. States that students and faculty members spent two weeks in Belize, establishing a summer camp program for children to develop English skills. Asserts that volunteers benefited from the…
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
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.
Learning Centers: A Personalized Approach to Mainstreaming.
ERIC Educational Resources Information Center
Babich, Betsy; Thompson, Cecelia
The manual provides information about using learning centers in mainstreamed home economics classrooms. The initial chapter introduces the rationale for the approach and presents a three-stage model depicting an integrational approach to mainstreaming. Chapter 2 outlines typical characteristics and recommendations for accommodating students with…
Student Centred Approaches: Teachers' Learning and Practice
ERIC Educational Resources Information Center
Vale, Colleen; Davies, Anne; Weaven, Mary; Hooley, Neil
2010-01-01
Student centred approaches to teaching and learning in mathematics is one of the reforms currently being advocated and implemented to improve mathematics outcomes for students from low socio-economic status (SES) backgrounds. The models, meanings and practices of student centred approaches explored in this paper reveal that a constructivist model…
Generic framework for mining cellular automata models on protein-folding simulations.
Diaz, N; Tischer, I
2016-05-13
Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.
Iterons, fractals and computations of automata
NASA Astrophysics Data System (ADS)
Siwak, Paweł
1999-03-01
Processing of strings by some automata, when viewed on space-time (ST) diagrams, reveals characteristic soliton-like coherent periodic objects. They are inherently associated with iterations of automata mappings thus we call them the iterons. In the paper we present two classes of one-dimensional iterons: particles and filtrons. The particles are typical for parallel (cellular) processing, while filtrons, introduced in (32) are specific for serial processing of strings. In general, the images of iterated automata mappings exhibit not only coherent entities but also the fractals, and quasi-periodic and chaotic dynamics. We show typical images of such computations: fractals, multiplication by a number, and addition of binary numbers defined by a Turing machine. Then, the particles are presented as iterons generated by cellular automata in three computations: B/U code conversion (13, 29), majority classification (9), and in discrete version of the FPU (Fermi-Pasta-Ulam) dynamics (7, 23). We disclose particles by a technique of combinational recoding of ST diagrams (as opposed to sequential recoding). Subsequently, we recall the recursive filters based on FCA (filter cellular automata) window operators, and considered by Park (26), Ablowitz (1), Fokas (11), Fuchssteiner (12), Bruschi (5) and Jiang (20). We present the automata equivalents to these filters (33). Some of them belong to the class of filter automata introduced in (30). We also define and illustrate some properties of filtrons. Contrary to particles, the filtrons interact nonlocally in the sense that distant symbols may influence one another. Thus their interactions are very unusual. Some examples have been given in (32). Here we show new examples of filtron phenomena: multifiltron solitonic collisions, attracting and repelling filtrons, trapped bouncing filtrons (which behave like a resonance cavity) and quasi filtrons.
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
Modelling of the cellular automata space deformation within the RCAFE framework
NASA Astrophysics Data System (ADS)
Sitko, Mateusz; Madej, Łukasz
2016-10-01
Development of the innovative approach to micro scale cellular automata (CA) space deformation during dynamic recrystallization process (DRX) is the main goal of the present paper. Major assumptions of the developed CA DRX model as well as novel space deformation algorithm, which is based on the random cellular automata concept and FE method, are described. Algorithms and methods to transfer input/output data between FE and CA are presented in detail. Visualization tool to analyze progress of deformation in the irregular CA space is also highlighted. Finally, initial results in the form of deformed and recrystallized microstructures are presented and discussed.
Noisy Quantum Cellular Automata for Quantum versus Classical Excitation Transfer
NASA Astrophysics Data System (ADS)
Avalle, Michele; Serafini, Alessio
2014-05-01
We introduce a class of noisy quantum cellular automata on a qubit lattice that includes all classical Markov chains, as well as maps where quantum coherence between sites is allowed to build up over time. We apply such a construction to the problem of excitation transfer through 1D lattices, and compare the performance of classical and quantum dynamics with equal local transition probabilities. Our discrete approach has the merits of stripping down the complications of the open system dynamics, of clearly isolating coherent effects, and of allowing for an exact treatment of conditional dynamics, all while capturing a rich variety of dynamical behaviors.
Noisy quantum cellular automata for quantum versus classical excitation transfer.
Avalle, Michele; Serafini, Alessio
2014-05-02
We introduce a class of noisy quantum cellular automata on a qubit lattice that includes all classical Markov chains, as well as maps where quantum coherence between sites is allowed to build up over time. We apply such a construction to the problem of excitation transfer through 1D lattices, and compare the performance of classical and quantum dynamics with equal local transition probabilities. Our discrete approach has the merits of stripping down the complications of the open system dynamics, of clearly isolating coherent effects, and of allowing for an exact treatment of conditional dynamics, all while capturing a rich variety of dynamical behaviors.
Lattice gas automata for flow and transport in geochemical systems
Janecky, D.R.; Chen, S.; Dawson, S.; Eggert, K.C.; Travis, B.J.
1992-05-01
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.
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.
Machine Learning Approaches in Cardiovascular Imaging.
Henglin, Mir; Stein, Gillian; Hushcha, Pavel V; Snoek, Jasper; Wiltschko, Alexander B; Cheng, Susan
2017-10-01
Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine learning methods can now address data-related problems ranging from simple analytic queries of existing measurement data to the more complex challenges involved in analyzing raw images. To date, machine learning has been used in 2 broad and highly interconnected areas: automation of tasks that might otherwise be performed by a human and generation of clinically important new knowledge. Most cardiovascular imaging studies have focused on task-oriented problems, but more studies involving algorithms aimed at generating new clinical insights are emerging. Continued expansion in the size and dimensionality of cardiovascular imaging databases is driving strong interest in applying powerful deep learning methods, in particular, to analyze these data. Overall, the most effective approaches will require an investment in the resources needed to appropriately prepare such large data sets for analyses. Notwithstanding current technical and logistical challenges, machine learning and especially deep learning methods have much to offer and will substantially impact the future practice and science of cardiovascular imaging. © 2017 American Heart Association, Inc.
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 within the…
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…
Approach to Learning and Assessment in Physics.
ERIC Educational Resources Information Center
Dickie, Leslie
The objectives of this exploratory study were to determine: (1) the approach to learning of physics students (N=142) at John Abbott College (Quebec, Canada) as determined by the Study Process Questionnaire; (2) the intellectual demands of quizzes, tests, and final exams in physics using a scheme derived from Bloom's taxonomy; and (3) the…
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…
Team Building: A Structured Learning Approach.
ERIC Educational Resources Information Center
Mears, Peter; Voehl, Frank
This book is a learner's manual for a course on how to develop empowered teams for higher education management, how to function effectively as a team member, and how to objectively evaluate one's impact on the team. Taking a hands-on approach to learning about quality, the course introduces quality principles, asks students to apply these in a…
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 within the…
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…
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…
ERIC Educational Resources Information Center
Chiu, Thomas K. F.; Churchill, Daniel
2016-01-01
Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…
ERIC Educational Resources Information Center
Chiu, Thomas K. F.; Churchill, Daniel
2016-01-01
Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…
Cellular Automata Simulation for Wealth Distribution
NASA Astrophysics Data System (ADS)
Lo, Shih-Ching
2009-08-01
Wealth distribution of a country is a complicate system. A model, which is based on the Epstein & Axtell's "Sugars cape" model, is presented in Netlogo. The model considers the income, age, working opportunity and salary as control variables. There are still other variables should be considered while an artificial society is established. In this study, a more complicate cellular automata model for wealth distribution model is proposed. The effects of social welfare, tax, economical investment and inheritance are considered and simulated. According to the cellular automata simulation for wealth distribution, we will have a deep insight of financial policy of the government.
A Machine Learning Approach to Student Modeling.
1984-05-01
machine learning , and describe ACN, a student modeling system that incorporates this approach. This system begins with a set of overly general rules, which it uses to search a problem space until it arrives at the same answer as the student. The ACM computer program then uses the solution path it has discovered to determine positive and negative instances of its initial rules, and employs a discrimination learning mechanism to place additional conditions on these rules. The revised rules will reproduce the solution path without search, and constitute a cognitive model of
Prehospital curriculum development: a learning objective approach.
Schafermeyer, R W
1993-02-01
Prehospital curriculum development is a time-consuming, yet essential, component of emergency medical technician and paramedic education. Over the past several years, much has changed within the EMS system and with the approach to educating the prehospital care provider. Learning is defined as a permanent change in behavior that comes about as a result of a planned experience. This planned experience must include learning objectives that incorporate assessment of presenting signs and symptoms and demonstrate the prehospital care providers' psychomotor skills in providing prehospital care based on that assessment.
Comparing Team Learning Approaches through the Lens of Activity Theory
ERIC Educational Resources Information Center
Park, Sunyoung; Cho, Yonjoo; Yoon, Seung Won; Han, Heeyoung
2013-01-01
Purpose: The purpose of this study is to examine the distinctive features of three team learning approaches (action learning, problem-based learning, and project-based learning), compare and contrast them, and discuss implications for practice and research. Design/methodology/approach: The authors used Torraco's integrative literature review…
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…
Comparing Team Learning Approaches through the Lens of Activity Theory
ERIC Educational Resources Information Center
Park, Sunyoung; Cho, Yonjoo; Yoon, Seung Won; Han, Heeyoung
2013-01-01
Purpose: The purpose of this study is to examine the distinctive features of three team learning approaches (action learning, problem-based learning, and project-based learning), compare and contrast them, and discuss implications for practice and research. Design/methodology/approach: The authors used Torraco's integrative literature review…
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…
Towards an Integrated Approach for Research on Lifelong Learning
ERIC Educational Resources Information Center
van Merrienboer, Jeroen J. G.; Kirschner, Paul A.; Paas, Fred; Sloep, Peter B.; J. Caniels, Marjolein C.
2009-01-01
There is little dispute that lifelong learning is essential to the further development of the knowledge society. Nonetheless, lifelong learning is not reaching its full potential because the currently used approaches to lifelong learning are too fragmented and, often, formal approaches to education and learning are simply "translated" from initial…
ChemApproach: Validation of a Questionnaire to Assess the Learning Approaches of Chemistry Students
ERIC Educational Resources Information Center
Lastusaari, Mika; Laakkonen, Eero; Murtonen, Mari
2016-01-01
The theory of learning approaches has proven to be one of the most powerful theories explaining university students' learning. However, learning approaches are sensitive to the situation and the content of learning. Chemistry has its own specific features that should be considered when exploring chemistry students' learning habits, specifically…
ChemApproach: Validation of a Questionnaire to Assess the Learning Approaches of Chemistry Students
ERIC Educational Resources Information Center
Lastusaari, Mika; Laakkonen, Eero; Murtonen, Mari
2016-01-01
The theory of learning approaches has proven to be one of the most powerful theories explaining university students' learning. However, learning approaches are sensitive to the situation and the content of learning. Chemistry has its own specific features that should be considered when exploring chemistry students' learning habits, specifically…
Fuzzy cellular automata models in immunology
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.
Maximizing the Adjacent Possible in Automata Chemistries.
Hickinbotham, Simon; Clark, Edward; Nellis, Adam; Stepney, Susan; Clarke, Tim; Young, Peter
2016-01-01
Automata chemistries are good vehicles for experimentation in open-ended evolution, but they are by necessity complex systems whose low-level properties require careful design. To aid the process of designing automata chemistries, we develop an abstract model that classifies the features of a chemistry from a physical (bottom up) perspective and from a biological (top down) perspective. There are two levels: things that can evolve, and things that cannot. We equate the evolving level with biology and the non-evolving level with physics. We design our initial organisms in the biology, so they can evolve. We design the physics to facilitate evolvable biologies. This architecture leads to a set of design principles that should be observed when creating an instantiation of the architecture. These principles are Everything Evolves, Everything's Soft, and Everything Dies. To evaluate these ideas, we present experiments in the recently developed Stringmol automata chemistry. We examine the properties of Stringmol with respect to the principles, and so demonstrate the usefulness of the principles in designing automata chemistries.
Gabrijel, Ivan; Dobnikar, Andrej
2003-01-01
In this paper finite automata are treated as general discrete dynamical systems from the viewpoint of systems theory. The unconditional on-line identification of an unknown finite automaton is the problem considered. A generalized architecture of recurrent neural networks with a corresponding on-line learning scheme is proposed as a solution to the problem. An on-line rule-extraction algorithm is further introduced. The architecture presented, the on-line learning scheme and the on-line rule-extraction method are tested on different, strongly connected automata, ranging from a very simple example with two states only to a more interesting and complex one with 64 states; the results of both training and extraction processes are very promising.
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.
Characterization of one-dimensional cellular automata rules through topological network features
NASA Astrophysics Data System (ADS)
D'Alotto, Lou; Pizzuti, Clara
2016-10-01
The paper investigates the relationship between the classification schemes, defined by Wolfram and Gilman, of one-dimensional cellular automata through concepts coming from network theory. An automaton is represented with a network, generated from the elementary rule defining its behavior. Characteristic features of this graph are computed and machine learning classification models are built. Such models allow to classify automaton rules and to compare Wolfram's and Gilman's classes by comparing the classes predicted by these models.
Material representations: from the genetic code to the evolution of cellular automata.
Rocha, Luis Mateus; Hordijk, Wim
2005-01-01
We present a new definition of the concept of representation for cognitive science that is based on a study of the origin of structures that are used to store memory in evolving systems. This study consists of novel computer experiments in the evolution of cellular automata to perform nontrivial tasks as well as evidence from biology concerning genetic memory. Our key observation is that representations require inert structures to encode information used to construct appropriate dynamic configurations for the evolving system. We propose criteria to decide if a given structure is a representation by unpacking the idea of inert structures that can be used as memory for arbitrary dynamic configurations. Using a genetic algorithm, we evolved cellular automata rules that can perform nontrivial tasks related to the density task (or majority classification problem) commonly used in the literature. We present the particle catalogs of the new rules following the computational mechanics framework. We discuss if the evolved cellular automata particles may be seen as representations according to our criteria. We show that while they capture some of the essential characteristics of representations, they lack an essential one. Our goal is to show that artificial life can be used to shed new light on the computation-versus-dynamics debate in cognitive science, and indeed function as a constructive bridge between the two camps. Our definitions of representation and cellular automata experiments are proposed as a complementary approach, with both dynamics and informational modes of explanation.
Simulating invasion with cellular automata: connecting cell-scale and population-scale properties.
Simpson, Matthew J; Merrifield, Alistair; Landman, Kerry A; Hughes, Barry D
2007-08-01
Interpretive and predictive tools are needed to assist in the understanding of cell invasion processes. Cell invasion involves cell motility and proliferation, and is central to many biological processes including developmental morphogenesis and tumor invasion. Experimental data can be collected across a wide range of scales, from the population scale to the individual cell scale. Standard continuum or discrete models used in isolation are insufficient to capture this wide range of data. We develop a discrete cellular automata model of invasion with experimentally motivated rules. The cellular automata algorithm is applied to a narrow two-dimensional lattice and simulations reveal the formation of invasion waves moving with constant speed. The simulation results are averaged in one dimension-these data are used to identify the time history of the leading edge to characterize the population-scale wave speed. This allows the relationship between the population-scale wave speed and the cell-scale parameters to be determined. This relationship is analogous to well-known continuum results for Fisher's equation. The cellular automata algorithm also produces individual cell trajectories within the invasion wave that are analogous to cell trajectories obtained with new experimental techniques. Our approach allows both the cell-scale and population-scale properties of invasion to be predicted in a way that is consistent with multiscale experimental data. Furthermore we suggest that the cellular automata algorithm can be used in conjunction with individual data to overcome limitations associated with identifying cell motility mechanisms using continuum models alone.
Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios
NASA Astrophysics Data System (ADS)
Avolio, MV; Di Gregorio, Salvatore; Mantovani, Franco; Pasuto, Alessandro; Rongo, Rocco; Silvano, Sandro; Spataro, William
Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.
Maximizing exposure therapy: an inhibitory learning approach.
Craske, Michelle G; Treanor, Michael; Conway, Christopher C; Zbozinek, Tomislav; Vervliet, Bram
2014-07-01
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.
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
Nonsynchronous updating in the multiverse of cellular automata
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Kinouchi, Osame
2015-04-01
In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.
Nonsynchronous updating in the multiverse of cellular automata.
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.
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
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…
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.
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…
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…
Information-theoretic approach to interactive learning
NASA Astrophysics Data System (ADS)
Still, S.
2009-01-01
The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating feedback from the learner. A quantitative approach to interactive learning and adaptive behavior is proposed, integrating model- and decision-making into one theoretical framework. This paper follows simple principles by requiring that the observer's world model and action policy should result in maximal predictive power at minimal complexity. Classes of optimal action policies and of optimal models are derived from an objective function that reflects this trade-off between prediction and complexity. The resulting optimal models then summarize, at different levels of abstraction, the process's causal organization in the presence of the learner's actions. A fundamental consequence of the proposed principle is that the learner's optimal action policies balance exploration and control as an emerging property. Interestingly, the explorative component is present in the absence of policy randomness, i.e. in the optimal deterministic behavior. This is a direct result of requiring maximal predictive power in the presence of feedback.
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…
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…
Investigative Primary Science: A Problem-Based Learning Approach
ERIC Educational Resources Information Center
Etherington, Matthew B.
2011-01-01
This study reports on the success of using a problem-based learning approach (PBL) as a pedagogical mode of learning open inquiry science within a traditional four-year undergraduate elementary teacher education program. In 2010, a problem-based learning approach to teaching primary science replaced the traditional content driven syllabus. During…
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…
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…
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…
Unambiguous Finite Automata over a Unary Alphabet
NASA Astrophysics Data System (ADS)
Okhotin, Alexander
Nondeterministic finite automata (NFA) with at most one accepting computation on every input string are known as unambiguous finite automata (UFA). This paper considers UFAs over a unary alphabet, and determines the exact number of states in DFAs needed to represent unary languages recognized by n-state UFAs: the growth rate of this function is e^{Θ(sqrt[3]{n ln^2 n})}. The conversion of an n-state unary NFA to a UFA requires UFAs with g(n)+O(n^2)=e^{sqrt{n ln n}(1+o(1))} states, where g(n) is Landau's function. In addition, it is shown that the complement of n-state unary UFAs requires up to at least n 2 - o(1) states in an NFA, while the Kleene star requires up to exactly (n - 1)2 + 1 states.
Chaos automata: iterated function systems with memory
NASA Astrophysics Data System (ADS)
Ashlock, Dan; Golden, Jim
2003-07-01
Transforming biological sequences into fractals in order to visualize them is a long standing technique, in the form of the traditional four-cornered chaos game. In this paper we give a generalization of the standard chaos game visualization for DNA sequences. It incorporates iterated function systems that are called under the control of a finite state automaton, yielding a DNA to fractal transformation system with memory. We term these fractal visualizers chaos automata. The use of memory enables association of widely separated sequence events in the drawing of the fractal, finessing the “forgetfulness” of other fractal visualization methods. We use a genetic algorithm to train chaos automata to distinguish introns and exons in Zea mays (corn). A substantial issue treated here is the creation of a fitness function that leads to good visual separation of distinct data types.
Cellular Automata Model of Cardiac Pacemaker
NASA Astrophysics Data System (ADS)
Makowiec, D.
2008-05-01
A network of Greenberg-Hasting cellular automata with cyclic intrinsic dynamics F rightarrow R rightarrow A rightarrow F rightarrow ... is shown to be a reliable approximation to the cardiac pacemaker. The three possible cell's states F, R, A are characterized by fixed timings { nF, nR, nA } -- time steps spent in each state. Dynamical properties of a simple line network are found to be critical with respect to the relation between nF and nR. The properties of a network arisen from a square lattice where some edges are rewired (locally and with the preference to link to cells which are more connected to other cells) are also studied. The resulted system evolves rhythmically with the period determined by timings. The emergence of a small group of neighboring automata where the whole system activity initiates is observed. The dominant evolution is accompanied with other rhythms, characterized by longer periods.
ERIC Educational Resources Information Center
Van Petegem, Peter; Donche, Vincent; Vanhoof, Jan
2005-01-01
Within two Flemish institutes of pre-service and inservice teacher education, the relationship between the learning styles and preferences for learning environments of pre-service teachers were examined. Results indicate that some components of pre-service teachers' learning approaches (learning conceptions, learning strategies and learning…
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…
Learning Styles in the e-Learning Environment: The Approaches and Research on Longitudinal Changes
ERIC Educational Resources Information Center
Doulik, Pavel; Skoda, Jiri; Simonova, Ivana
2017-01-01
The paper focuses on the field of learning styles in e-learning. The study is structured in two main parts: (1) a brief overview of traditional approaches to learning styles is presented and their role in the process of instruction is set; this part results in the reflection of current state, when learning styles are considered within e-learning;…
Symmetric Fractals Generated by Cellular Automata
2000-01-01
configuration is, e.g., rotationally symmetric. If is a regular k-invariant of A0, then 6(E fiX j) gives anther top row of a 0-configuration of size kN; what...Technology and Culture (JUAP P4-02). References 1. J.-P. Allouche, F. von Haeseler, E. Lange, A. Petersen, G. Skordev. Linear cellular automata and
Cellular automata in photonic cavity arrays.
Li, Jing; Liew, T C H
2016-10-31
We propose theoretically a photonic Turing machine based on cellular automata in arrays of nonlinear cavities coupled with artificial gauge fields. The state of the system is recorded making use of the bistability of driven cavities, in which losses are fully compensated by an external continuous drive. The sequential update of the automaton layers is achieved automatically, by the local switching of bistable states, without requiring any additional synchronization or temporal control.
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.
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…
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…
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
Kavianpour, Hamidreza; Vasighi, Mahdi
2017-02-01
Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.
Quantum state transfer through noisy quantum cellular automata
NASA Astrophysics Data System (ADS)
Avalle, Michele; Genoni, Marco G.; Serafini, Alessio
2015-05-01
We model the transport of an unknown quantum state on one dimensional qubit lattices by means of a quantum cellular automata (QCA) evolution. We do this by first introducing a class of discrete noisy dynamics, in the first excitation sector, in which a wide group of classical stochastic dynamics is embedded within the more general formalism of quantum operations. We then extend the Hilbert space of the system to accommodate a global vacuum state, thus allowing for the transport of initial on-site coherences besides excitations, and determine the dynamical constraints that define the class of noisy QCA in this subspace. We then study the transport performance through numerical simulations, showing that for some instances of the dynamics perfect quantum state transfer is attainable. Our approach provides one with a natural description of both unitary and open quantum evolutions, where the homogeneity and locality of interactions allow one to take into account several forms of quantum noise in a plausible scenario.
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.
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.
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…
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…
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…
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…
A Narrative Approach for Organizational Learning in a Diverse Organisation
ERIC Educational Resources Information Center
Lamsa, Anna-Maija; Sintonen, Teppo
2006-01-01
Purpose: This paper aims to construct an approach referred to as "the participatory narrative" for organizational learning in diverse organizations. The approach is grounded in an understanding of organizational learning as the process of social construction which is narratively mediated. Design/methodology/approach: The participatory narrative is…
Alternative Assessment Approaches for Online Learning Environments in Higher Education.
ERIC Educational Resources Information Center
Reeves, Thomas C.
2000-01-01
Describes the need and prospects for alternative assessment approaches in online learning environments in higher education. Explains the difference between assessment and evaluation and discusses three approaches to integrating alternative assessment approaches into online learning environments: cognitive assessment, performance assessment, and…
Edu-mining: A Machine Learning Approach
NASA Astrophysics Data System (ADS)
Srimani, P. K.; Patil, Malini M.
2011-12-01
Mining Educational data is an emerging interdisciplinary research area that mainly deals with the development of methods to explore the data stored in educational institutions. The educational data is referred as Edu-DATA. Queries related to Edu-DATA are of practical interest as SQL approach is insufficient and needs to be focused in a different way. The paper aims at developing a technique called Edu-MINING which converts raw data coming from educational institutions using data mining techniques into useful information. The discovered knowledge will have a great impact on the educational research and practices. Edu-MINING explores Edu-DATA, discovers new knowledge and suggests useful methods to improve the quality of education with regard to teaching-learning process. This is illustrated through a case study.
Simple derivation of the Weyl and Dirac quantum cellular automata
NASA Astrophysics Data System (ADS)
Raynal, Philippe
2017-06-01
We consider quantum cellular automata on a body-centered cubic lattice and provide a simple derivation of the only two homogenous, local, isotropic, and unitary two-dimensional automata [G. M. D'Ariano and P. Perinotti, Phys. Rev. A 90, 062106 (2014), 10.1103/PhysRevA.90.062106]. Our derivation relies on the notion of Gram matrix and emphasizes the link between the transition matrices that characterize the automata and the body-centered cubic lattice: The transition matrices essentially are the matrix representation of the vertices of the lattice's primitive cell. As expected, the dynamics of these two automata reduce to the Weyl equation in the limit of small wave vectors and continuous time. We also briefly examine the four-dimensional case, where we find two one-parameter families of automata that reduce to the Dirac equation in a suitable limit.
Machine learning: An artificial intelligence approach
Michalski, R.S.; Carbonell, J.G.; Mitchell, T.M.
1983-01-01
This book contains tutorial overviews and research papers on contemporary trends in the area of machine learning viewed from an AI perspective. Research directions covered include: learning from examples, modeling human learning strategies, knowledge acquisition for expert systems, learning heuristics, discovery systems, and conceptual data analysis.
Approaches to learning: psychometric testing of a study process questionnaire.
Snelgrove, Sherrill; Slater, Julie
2003-09-01
One method of evaluating students' learning is to measure surface, deep and achieving approaches to learning using a questionnaire. In comparison with research on student nurses' learning styles, there has been little examination of their 'approaches to learning'. Much of the 'approaches to learning' research has been conducted with higher education students in Australia and Hong Kong and this kind of measurement is viewed as a valid and reliable way to assess learning. The aim of study reported here was to establish the validity of an 'approaches to learning' questionnaire, the study process questionnaire, for use with student nurses by undertaking psychometrical testing, including exploratory factor analysis. The study process questionnaire is a 42-item questionnaire measuring surface, deep and achieving approaches to learning. It was distributed to 300 student nurses attending a common foundation programme in a higher education establishment in the United Kingdom (UK) in July 2000. Principal components analysis was conducted to determine the validity of the deep, surface and achievement scales in the questionnaire. A new factor structure was identified comprising three main scales which were similar in content but not identical to the original questionnaire. The deep factor correlated positively and significantly with grade performance average and sociology examination results. The study process questionnaire is a valid and useful tool for nurse teachers to gain knowledge about student nurses' approaches to learning. Deep learning appears to influence academic performance. More work is required to elucidate the complex nature of deep learning.
A Conceptual Data Model for Flood Based on Cellular Automata Using Moving Object Data Model
NASA Astrophysics Data System (ADS)
Rachmatullah, R. S.; Azizah, F. N.
2017-01-01
Flood is considered as the costliest natural disaster in Indonesia due to its frequent occurrences as well as the extensive damage that it causes. Several studies provide different flood prediction models based on various hydrological factors. A lot of these models use grid-to-grid approach, making them suitable to be modelled as cellular automata. This paper presents a conceptual data model for flood based on cellular automata model using spatio-temporal data model, especially the moving object data model, as the modelling approach. The conceptual data model serves as the model of data structures within an environment for flood prediction simulation. We describe two conceptual data models as the alternatives to model the data structures of flood model. We create the data model based on the study to the factors that constitute the flood models. The first conceptual data model alternative focuses on the cell/grid as the main entity type. The changes of the states of the cells are stored as moving integer. The second alternative emphasizes on flood as the main entity type. The changes of the flood area are stored as moving region. Both alternatives introduce some advantages and disadvantages and the choice rely on the purpose of the use of the data model. We present a proposal of the architecture of a flood prediction system using cellular automata as the modelling approach. As the continuation of this work, further design and implementation details must be provided.
Pharmacy students' approaches to learning in an Australian university.
Smith, Lorraine; Saini, Bandana; Krass, Ines; Chen, Timothy; Bosnic-Anticevich, Sinthia; Sainsbury, Erica
2007-12-15
To investigate how pharmacy students' approaches to learning change over the duration of a bachelor of pharmacy degree program. Data were obtained from a cross-sectional, repeated measures design, using a validated self-report survey instrument. Areas examined included processing and regulation strategies, motivational preferences for learning, and the relationship between approaches to learning and academic performance. Pharmacy students were strongly vocationally oriented in their studies across all year groups. This approach had a significant relationship to academic performance. Overall, students indicated a preference for external regulation strategies. There was little evidence of maturation in approaches to learning as students progressed through the curriculum. Students' preference for vocationally related strategies can be harnessed to increase both adoption of self-regulation behaviors and motivation for mastery of material. Comparison of our results with other studies indicates that approaches to learning may be influenced more by the learning environment than the discipline of study.
ERIC Educational Resources Information Center
Belaineh, Matheas Shemelis
2017-01-01
Quality of education in higher institutions can be affected by different factors. It partly rests on the learning environment created by teachers and the learning approach students are employing during their learning. The main purpose of this study is to examine the learning environment at Mizan Tepi University from students' perspective and their…
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)
Simulating Space Radiation-Induced Breast Tumor Incidence Using Automata.
Heuskin, A C; Osseiran, A I; Tang, J; Costes, S V
2016-07-01
Estimating cancer risk from space radiation has been an ongoing challenge for decades primarily because most of the reported epidemiological data on radiation-induced risks are derived from studies of atomic bomb survivors who were exposed to an acute dose of gamma rays instead of chronic high-LET cosmic radiation. In this study, we introduce a formalism using cellular automata to model the long-term effects of ionizing radiation in human breast for different radiation qualities. We first validated and tuned parameters for an automata-based two-stage clonal expansion model simulating the age dependence of spontaneous breast cancer incidence in an unexposed U.S. We then tested the impact of radiation perturbation in the model by modifying parameters to reflect both targeted and nontargeted radiation effects. Targeted effects (TE) reflect the immediate impact of radiation on a cell's DNA with classic end points being gene mutations and cell death. They are well known and are directly derived from experimental data. In contrast, nontargeted effects (NTE) are persistent and affect both damaged and undamaged cells, are nonlinear with dose and are not well characterized in the literature. In this study, we introduced TE in our model and compared predictions against epidemiologic data of the atomic bomb survivor cohort. TE alone are not sufficient for inducing enough cancer. NTE independent of dose and lasting ∼100 days postirradiation need to be added to accurately predict dose dependence of breast cancer induced by gamma rays. Finally, by integrating experimental relative biological effectiveness (RBE) for TE and keeping NTE (i.e., radiation-induced genomic instability) constant with dose and LET, the model predicts that RBE for breast cancer induced by cosmic radiation would be maximum at 220 keV/μm. This approach lays the groundwork for further investigation into the impact of chronic low-dose exposure, inter-individual variation and more complex space radiation
Students' Questions: Building a Bridge between Kolb's Learning Styles and Approaches to Learning
ERIC Educational Resources Information Center
de Jesus, Helena T. Pedrosa; Almeida, Patricia Albergaria; Teixeira-Dias, Jose Joaquim; Watts, Mike
2006-01-01
Purpose: The purpose of this study is to identify the types of questions that students ask during the learning of chemistry; discuss the role of students' questions in the process of constructing knowledge, and investigate the relationship between students' questions, approaches to learning, and learning styles. Design/methodology/approach: The…
Do Learning Approaches of Medical Students Affect Their Satisfaction with Problem-Based Learning?
ERIC Educational Resources Information Center
Gurpinar, Erol; Kulac, Esin; Tetik, Cihat; Akdogan, Ilgaz; Mamakli, Sumer
2013-01-01
The aim of this research was to determine the satisfaction of medical students with problem-based learning (PBL) and their approaches to learning to investigate the effect of learning approaches on their levels of satisfaction. The study group was composed of medical students from three different universities, which apply PBL at different levels…
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'…
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…
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…
A reinforcement learning approach to online clustering.
Likas, A
1999-11-15
A general technique is proposed for embedding online clustering algorithms based on competitive learning in a reinforcement learning framework. The basic idea is that the clustering system can be viewed as a reinforcement learning system that learns through reinforcements to follow the clustering strategy we wish to implement. In this sense, the reinforcement guided competitive learning (RGCL) algorithm is proposed that constitutes a reinforcement-based adaptation of learning vector quantization (LVQ) with enhanced clustering capabilities. In addition, we suggest extensions of RGCL and LVQ that are characterized by the property of sustained exploration and significantly improve the performance of those algorithms, as indicated by experimental tests on well-known data sets.
Curriculum Design Requirements and Challenges of the Learning Society Approach
ERIC Educational Resources Information Center
Karimi, Sedighe; Nasr, Ahmad-Reza; Sharif, Mostafa
2012-01-01
Entering the twenty-first century with the development of communities, they are faced with the necessity of moving towards a learning society. University must extend the learning opportunities and improve the quality of them with curriculum design by learning society approach to respond to the necessity. Researchers believe that some conditions…
Approaches of Inquiry Learning With Multimedia Resources in Primary Classrooms
ERIC Educational Resources Information Center
So, Wing-Mui Winnie; Kong, Siu-Cheung
2007-01-01
This study aims to examine the design of approaches for inquiry learning with multimedia resources in primary classrooms. The study describes the development of a multimedia learning unit that helps learners understand the natural phenomenon of the movement of the Earth. An analysis of the use of the multimedia learning unit by a teacher in two…
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…
Clickers in the Classroom: An Active Learning Approach
ERIC Educational Resources Information Center
Martyn, Margie
2007-01-01
Current research describes the benefits of active learning approaches. Clickers, or student response systems, are a technology used to promoted active learning. Most research on the benefits of using clickers in the classroom has shown that students become engaged and enjoy using them. However, research on learning outcomes has only compared the…
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…
A Blended Learning Approach to Teach Fluid Mechanics in Engineering
ERIC Educational Resources Information Center
Rahman, Ataur
2017-01-01
This paper presents a case study on the teaching and learning of fluid mechanics at the University of Western Sydney (UWS), Australia, by applying a blended learning approach (BLA). In the adopted BLA, various flexible learning materials have been made available to the students such as online recorded lectures, online recorded tutorials, hand…
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…
A Learning Progressions Approach to Early Algebra Research and Practice
ERIC Educational Resources Information Center
Fonger, Nicole L.; Stephens, Ana; Blanton, Maria; Knuth, Eric
2015-01-01
We detail a learning progressions approach to early algebra research and how existing work around learning progressions and trajectories in mathematics and science education has informed our development of a four-component theoretical framework consisting of: a curricular progression of learning goals across big algebraic ideas; an instructional…
(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…
Implementing Project Based Learning Approach to Graphic Design Course
ERIC Educational Resources Information Center
Riyanti, Menul Teguh; Erwin, Tuti Nuriah; Suriani, S. H.
2017-01-01
The purpose of this study was to develop a learning model based Commercial Graphic Design Drafting project-based learning approach, was chosen as a strategy in the learning product development research. University students as the target audience of this model are the students of the fifth semester Visual Communications Design Studies Program…
Approaches of Inquiry Learning With Multimedia Resources in Primary Classrooms
ERIC Educational Resources Information Center
So, Wing-Mui Winnie; Kong, Siu-Cheung
2007-01-01
This study aims to examine the design of approaches for inquiry learning with multimedia resources in primary classrooms. The study describes the development of a multimedia learning unit that helps learners understand the natural phenomenon of the movement of the Earth. An analysis of the use of the multimedia learning unit by a teacher in two…
Clickers in the Classroom: An Active Learning Approach
ERIC Educational Resources Information Center
Martyn, Margie
2007-01-01
Current research describes the benefits of active learning approaches. Clickers, or student response systems, are a technology used to promoted active learning. Most research on the benefits of using clickers in the classroom has shown that students become engaged and enjoy using them. However, research on learning outcomes has only compared the…
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…
Many-body approach to the dynamics of batch learning
NASA Astrophysics Data System (ADS)
Wong, K. Y. Michael; Li, S.; Tong, Y. W.
2000-09-01
Using the cavity method and diagrammatic methods, we model the dynamics of batch learning of restricted sets of examples, widely applicable to general learning cost functions, and fully taking into account the temporal correlations introduced by the recycling of the examples. The approach is illustrated using the Adaline rule learning teacher-generated or random examples.
University students' approaches to learning first-year mathematics.
Alkhateeb, Haitham M
2003-12-01
This study assessed reliability and validity of the Approaches to earning Mathematics Questionnaire, for 218 university students. The study also identified the relationship between subscales. Internal consistency as Cronbach alpha was .77 for the Surface Approach to Learning scale and .88 for the Deep Approach to Learning scale. Principal components analysis yielded a two-factor solution accounting for only 34.6% of variance. The factors were interpreted as Surface Approach and Deep Approach to learning mathematics, as in Australia. The former subscale scores were negatively correlated -.2 with the latter subscale scores.
CarboCAT: A cellular automata model of heterogeneous carbonate strata
NASA Astrophysics Data System (ADS)
Burgess, Peter M.
2013-04-01
CarboCAT is a new numerical model of carbonate deposystems that uses a cellular automata to calculate lithofacies spatial distributions and hence to calculate the accumulation of heterogeneous carbonate strata in three dimensions. CarboCAT includes various geological processes, including tectonic subsidence, eustatic sea-level oscillations, water depth-dependent carbonate production rates in multiple carbonate factories, lateral migration of carbonate lithofacies bodies, and a simple representation of sediment transport. Results from the model show stratigraphically interesting phenomena such as heterogeneous strata with complex stacking patterns, laterally discontinuous subaerial exposure surfaces, nonexponential lithofacies thickness distributions, and sensitive dependence on initial conditions whereby small changes in the model initial conditions have a large effect on the final model outcome. More work is required to fully assess CarboCAT, but these initial results suggest that a cellular automata approach to modeling carbonate strata is likely to be a useful tool for investigating the nature and origins of heterogeneity in carbonate strata.
Scaling behavior in probabilistic neuronal cellular automata.
Manchanda, Kaustubh; Yadav, Avinash Chand; Ramaswamy, Ramakrishna
2013-01-01
We study a neural network model of interacting stochastic discrete two-state cellular automata on a regular lattice. The system is externally tuned to a critical point which varies with the degree of stochasticity (or the effective temperature). There are avalanches of neuronal activity, namely, spatially and temporally contiguous sites of activity; a detailed numerical study of these activity avalanches is presented, and single, joint, and marginal probability distributions are computed. At the critical point, we find that the scaling exponents for the variables are in good agreement with a mean-field theory.
Modelling robot's behaviour using finite automata
NASA Astrophysics Data System (ADS)
Janošek, Michal; Žáček, Jaroslav
2017-07-01
This paper proposes a model of a robot's behaviour described by finite automata. We split robot's knowledge into several knowledge bases which are used by the inference mechanism of the robot's expert system to make a logic deduction. Each knowledgebase is dedicated to the particular behaviour domain and the finite automaton helps us switching among these knowledge bases with the respect of actual situation. Our goal is to simplify and reduce complexity of one big knowledgebase splitting it into several pieces. The advantage of this model is that we can easily add new behaviour by adding new knowledgebase and add this behaviour into the finite automaton and define necessary states and transitions.
On Binary-State Phyllosilicate Automata
NASA Astrophysics Data System (ADS)
Adamatzky, Andrew
Phyllosilicate is a sheet of silicate tetrahedra bound by basal oxygens. A phyllosilicate automaton is a regular network of finite state machines, which mimics the structure of phyllosilicate. A node of a binary state phyllosilicate automaton takes states 0 and 1. A node updates its state in discrete time depending on a sum of states of its three (silicon nodes) or six (oxygen nodes) closest neighbors. We phenomenologically select the main types of patterns generated by phyllosilicate automata based on their shape: convex and concave hulls, almost circularly growing patterns, octagonal patterns, and those with dendritic growth; and, the patterns' interior: disordered, solid, labyrinthine. We also present the rules exhibiting traveling localizations.
Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A
2016-01-07
Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.
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.
Parpala, Anna; Lindblom-Ylänne, Sari; Komulainen, Erkki; Litmanen, Topi; Hirsto, Laura
2010-06-01
There is evidence of disciplinary variation in students' approaches to learning. Furthermore, previous research has shown that students' approaches are related to their perceptions of the learning environment. The overall objective of the study was to analyse combinations of approaches to learning among undergraduates in different disciplines. More precisely, the aim was to cluster students on the basis of their scores on different items measuring approaches to learning, and to explore the relationship between the clusters and both the disciplines of the students and their perceptions of the teaching-learning environment. A total of 2,509 students participated in the study. The students were asked to complete an on-line questionnaire, which was a revised version of the Experience of Teaching and Learning Questionnaire. It included items covering approaches to learning and perceptions of the teaching-learning environment. The students were classified in four clusters. There were significant differences in how the respondents from the 10 faculties were represented in these clusters. There were also differences in their perceptions of the teaching-learning environment in the different faculties. It appears that there is disciplinary variation in approaches to learning. Furthermore, the results indicate that both approaches to learning and the discipline have an effect on students' experiences of the teaching-learning environment.
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…
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…
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…
The Learning of Consumer Skills in Adolescents: An Eclectic Approach.
ERIC Educational Resources Information Center
Kuo, Cheng
A study investigated the learning of consumer skills by adolescents, using two theoretical approaches--the social learning and the family communication pattern approaches. It was hypothesized that (1) assuming that parents are more experienced consumers than are adolescents, frequent discussion with parents on consumption matters are likely to…
Manpower Development for Workers in Tertiary Institutions: Distance Learning Approach
ERIC Educational Resources Information Center
Hassan, Moshood Ayinde
2011-01-01
The purpose of this study is to determine the extent to which workers patronize distance learning approach to further their education. Other purposes include: determine problems facing workers in the process of improving their knowledge and skills through distance learning approach; establish the level of attainment of manpower development…
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…
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…
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…
High Velocity--A Capacity Building Approach to Learning
ERIC Educational Resources Information Center
Hurford, Grace; Metcalfe Meer, Nicky
2007-01-01
Many teaching and learning strategies are based on a deficit/gap analysis approach to student needs. Our capacity-building approach is a modest attempt to focus on what students already know and can do, and concentrates on building on that knowledge and skill in order to accelerate learning that becomes, deep, meaningful and enjoyable. Student…
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…
Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie
2016-01-01
Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807
Aberg, Kristoffer Carl; Doell, Kimberly C; Schwartz, Sophie
2016-01-01
Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits.
A Constructivist Approach to Distance Learning for Counterterrorist Intelligence Analysis
2005-01-01
A CONSTRUCTIVIST APPROACH TO DISTANCE LEARNING FOR COUNTERTERRORIST INTELLIGENCE ANALYSIS Tamitha Carpenter, Daniel Fu, Phillip Michalak, Laurie...Learning for Counterterrorist Intelligence Analysis 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 A CONSTRUCTIVIST APPROACH TO DISTANCE LEARNING FOR COUNTERTERRORIST INTELLIGENCE ANALYSIS Tamitha
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…
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…
Intelligent Machine Learning Approaches for Aerospace Applications
NASA Astrophysics Data System (ADS)
Sathyan, Anoop
Machine Learning is a type of artificial intelligence that provides machines or networks the ability to learn from data without the need to explicitly program them. There are different kinds of machine learning techniques. This thesis discusses the applications of two of these approaches: Genetic Fuzzy Logic and Convolutional Neural Networks (CNN). Fuzzy Logic System (FLS) is a powerful tool that can be used for a wide variety of applications. FLS is a universal approximator that reduces the need for complex mathematics and replaces it with expert knowledge of the system to produce an input-output mapping using If-Then rules. The expert knowledge of a system can help in obtaining the parameters for small-scale FLSs, but for larger networks we will need to use sophisticated approaches that can automatically train the network to meet the design requirements. This is where Genetic Algorithms (GA) and EVE come into the picture. Both GA and EVE can tune the FLS parameters to minimize a cost function that is designed to meet the requirements of the specific problem. EVE is an artificial intelligence developed by Psibernetix that is trained to tune large scale FLSs. The parameters of an FLS can include the membership functions and rulebase of the inherent Fuzzy Inference Systems (FISs). The main issue with using the GFS is that the number of parameters in a FIS increase exponentially with the number of inputs thus making it increasingly harder to tune them. To reduce this issue, the FLSs discussed in this thesis consist of 2-input-1-output FISs in cascade (Chapter 4) or as a layer of parallel FISs (Chapter 7). We have obtained extremely good results using GFS for different applications at a reduced computational cost compared to other algorithms that are commonly used to solve the corresponding problems. In this thesis, GFSs have been designed for controlling an inverted double pendulum, a task allocation problem of clustering targets amongst a set of UAVs, a fire
A systems biology approach to learning autophagy.
Klionsky, Daniel J; Kumar, Anuj
2006-01-01
With its relevance to our understanding of eukaryotic cell function in the normal and disease state, autophagy is an important topic in modern cell biology; yet, few textbooks discuss autophagy beyond a two- or three-sentence summary. Here, we report an undergraduate/graduate class lesson for the in-depth presentation of autophagy using an active learning approach. By our method, students will work in small groups to solve problems and interpret an actual data set describing genes involved in autophagy. The problem-solving exercises and data set analysis will instill within the students a much greater understanding of the autophagy pathway than can be achieved by simple rote memorization of lecture materials; furthermore, the students will gain a general appreciation of the process by which data are interpreted and eventually formed into an understanding of a given pathway. As the data sets used in these class lessons are largely genomic and complementary in content, students will also understand first-hand the advantage of an integrative or systems biology study: No single data set can be used to define the pathway in full-the information from multiple complementary studies must be integrated in order to recapitulate our present understanding of the pathways mediating autophagy. In total, our teaching methodology offers an effective presentation of autophagy as well as a general template for the discussion of nearly any signaling pathway within the eukaryotic kingdom.
Measuring students’ approaches to learning in different clinical rotations
2012-01-01
Background Many studies have explored approaches to learning in medical school, mostly in the classroom setting. In the clinical setting, students face different conditions that may affect their learning. Understanding students’ approaches to learning is important to improve learning in the clinical setting. The aim of this study was to evaluate the Study Process Questionnaire (SPQ) as an instrument for measuring clinical learning in medical education and also to show whether learning approaches vary between rotations. Methods All students involved in this survey were undergraduates in their clinical phase. The SPQ was adapted to the clinical setting and was distributed in the last week of the clerkship rotation. A longitudinal study was also conducted to explore changes in learning approaches. Results Two hundred and nine students participated in this study (response rate 82.0%). The SPQ findings supported a two-factor solution involving deep and surface approaches. These two factors accounted for 45.1% and 22.5%, respectively, of the variance. The relationships between the two scales and their subscales showed the internal consistency and factorial validity of the SPQ to be comparable with previous studies. The clinical students in this study had higher scores for deep learning. The small longitudinal study showed small changes of approaches to learning with different rotation placement but not statistically significant. Conclusions The SPQ was found to be a valid instrument for measuring approaches to learning among clinical students. More students used a deep approach than a surface approach. Changes of approach not clearly occurred with different clinical rotations. PMID:23153333
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.
A Janus-Faced Approach to Learning. A Critical Discussion of Habermas' Pragmatic Approach
ERIC Educational Resources Information Center
Italia, Salvatore
2017-01-01
A realist approach to learning is what I propose here. This is based on a non-epistemic dimension whose presence is a necessary assumption for a concept of learning of a life-world as complementary to learning within a life-world. I develop my approach in opposition to Jürgen Habermas' pragmatic approach, which seems to lack of something from a…
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.
A cellular automata model of bone formation.
Van Scoy, Gabrielle K; George, Estee L; Opoku Asantewaa, Flora; Kerns, Lucy; Saunders, Marnie M; Prieto-Langarica, Alicia
2017-04-01
Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model.
Canalization and control in automata networks: body segmentation in Drosophila melanogaster.
Marques-Pita, Manuel; Rocha, Luis M
2013-01-01
We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics--a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity--with the ultimate goal of explaining how do cells and tissues 'compute'.
Canalization and Control in Automata Networks: Body Segmentation in Drosophila melanogaster
Marques-Pita, Manuel; Rocha, Luis M.
2013-01-01
We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics – a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity – with the ultimate goal of explaining how do cells and tissues ‘compute’. PMID:23520449
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…
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…
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.
NASA Astrophysics Data System (ADS)
Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen
2016-06-01
In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to explore the relationships among undergraduates' conceptions of, approaches to, and self-efficacy for learning earth science by adopting the structural equation modeling technique. A total of 268 Taiwanese undergraduates (144 females) participated in this study. Three instruments were modified to assess the students' conceptions of, approaches to, and self-efficacy for learning earth science. The results indicated that students' conceptions of learning made a significant contribution to their approaches to learning, which were consequently correlated with their learning self-efficacy. More specifically, students with stronger agreement that learning earth science involves applying the knowledge and skills learned to unknown problems were prone to possess higher confidence in learning earth science. Moreover, students viewing earth science learning as understanding earth science knowledge were more likely to adopt meaningful strategies to learn earth science, and hence expressed a higher sense of self-efficacy. Based on the results, practical implications and suggestions for future research are discussed.
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)
A Learning Center Approach to Infant Education.
ERIC Educational Resources Information Center
Adams, Polly K.; Taylor, Michaell K.
Following a prefatory description of infant development and high-quality infant day care centers, this paper focuses on the construction of learning centers for infants and toddlers in day care. Issues for consideration are specified, and 18 different care/learning centers and 6 work sstations for parents/staff are briefly described. In addition…
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.…
How One Learning Community Approached Death
ERIC Educational Resources Information Center
Ungemah, Lori
2017-01-01
In this narrative piece, the author describes how a learning community was able to transfer their practices of care to support a colleague as he faced illness and death. The author chronicles how the learning community responded to support their team member, other members of the campus community, and the students. She reflects on this experience…
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.…
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)
Adult Learning: A Personal Construct Approach.
ERIC Educational Resources Information Center
Candy, Philip C.
A pilot study into adult learners' perceptions of adult learning was undertaken in early 1980 at Adelaide College of the Arts and Education (Australia). The research set out to explore whether there are underlying dimensions which adult learners use in evaluating and comparing learning experiences. Five volunteer subjects completed Kolb's Learning…
Ullah, Raza
2016-05-01
The main objective of the study was to see whether medical students use more desirable approaches to studying than general education students. Survey method was used to collect data from both the medical students and the general education students. The survey of the medical students was carried out between January and March, 2012. The survey was administered to all the medical students present in lecture halls on day of data collection, while general education students were randomly selected from four subject areas at two universities. In total, 976 medical students and 912 general students participated in the study. Of the general students, 494(54%) were boys and 418(46%)were girls with an overall mean age of 20.53±1.77 years (range: 17-27 years). The medical students' perceptions of their learning environment and their learning preferences were broadly similar to that of general education students with the exception of workload. The medical students perceived the workload to be less appropriate (Mean = 2.06±0.72) than the students in general education (Mean = 2.84±0.90). The medical students were more likely to use the deep approach to studying (Mean = 3.66±0.59) than the students in general education (Mean = 3.16±0.91). The students in general education were slightly more likely to use the organized studying (Mean = 3.44±0.90) than the medical students (Mean =3.23±0.90). Both medical students and the students in general education tended to use the surface approaches along with other approaches to studying. There was not a great difference between the medical students and the students pursuing general education with regard to perceptions of the learning environment and approaches to learning.
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.
White, Meagan; Shellenbarger, Teresa
E-learning provides an alternative approach to traditional professional development activities. A learning management system may help nursing professional development practitioners deliver content more efficiently and effectively; however, careful consideration is needed during planning and implementation. This article provides essential information in the selection and use of a learning management system for professional development.
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…
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…
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
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…
ERIC Educational Resources Information Center
Kusumaningrum, Indrati; Hidayat, Hendra; Ganefri; Anori, Sartika; Dewy, Mega Silfia
2016-01-01
This article describes the development of a business plan by using production-based learning approach. In addition, this development also aims to maximize learning outcomes in vocational education. Preliminary analysis of curriculum and learning and the needs of the market and society become the basic for business plan development. To produce a…
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
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…
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…
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
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…
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…
Cellular Automata Methods in Mathematical Physics.
NASA Astrophysics Data System (ADS)
Smith, Mark Andrew
Cellular automata (CA) are fully discrete, spatially -distributed dynamical systems which can serve as an alternative framework for mathematical descriptions of physical systems. Furthermore, they constitute intrinsically parallel models of computation which can be efficiently realized with special-purpose cellular automata machines. The basic objective of this thesis is to determine techniques for using CA to model physical phenomena and to develop the associated mathematics. Results may take the form of simulations and calculations as well as proofs, and applications are suggested throughout. We begin by describing the structure, origins, and modeling categories of CA. A general method for incorporating dissipation in a reversible CA rule is suggested by a model of a lattice gas in the presence of an external potential well. Statistical forces are generated by coupling the gas to a low temperature heat bath. The equilibrium state of the coupled system is analyzed using the principle of maximum entropy. Continuous symmetries are important in field theory, whereas CA describe discrete fields. However, a novel CA rule for relativistic diffusion based on a random walk shows how Lorentz invariance can arise in a lattice model. Simple CA models based on the dynamics of abstract atoms are often capable of capturing the universal behaviors of complex systems. Consequently, parallel lattice Monte Carlo simulations of abstract polymers were devised to respect the steric constraints on polymer dynamics. The resulting double space algorithm is very efficient and correctly captures the static and dynamic scaling behavior characteristic of all polymers. Random numbers are important in stochastic computer simulations; for example, those that use the Metropolis algorithm. A technique for tuning random bits is presented to enable efficient utilization of randomness, especially in CA machines. Interesting areas for future CA research include network simulation, long-range forces
Multilevel programmable logic array schemes for microprogrammed automata
Barkalov, A.A.
1995-03-01
Programmable logic arrays (PLAs) provide an efficient tool for implementation of logic schemes of microprogrammed automata (MPA). The number of PLAs in the MPA logic scheme can be minimized by increasing the number of levels. In this paper, we analyze the structures of multilevel schemes of Mealy automata, propose a number of new structures, consider the corresponding correctness conditions, and examine some problems that must be solved in order to satisfy these conditions.
Partially Ordered Two-Way Büchi Automata
NASA Astrophysics Data System (ADS)
Kufleitner, Manfred; Lauser, Alexander
We introduce partially ordered two-way Büchi automata over infinite words. As for finite words, the nondeterministic variant recognizes the fragment Σ2 of first-order logic FO[<] and the deterministic version yields the Δ2-definable ω-languages. As a byproduct of our results, we show that deterministic partially ordered two-way Büchi automata are effectively closed under Boolean operations.
Evoked prior learning experience and approach to learning as predictors of academic achievement.
Trigwell, Keith; Ashwin, Paul; Millan, Elena S
2013-09-01
In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students' perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. To investigate how students' evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. A 77-item questionnaire was used to gather students' self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was
Revising a Design Course from a Lecture Approach to a Project-Based Learning Approach
ERIC Educational Resources Information Center
Kunberger, Tanya
2013-01-01
In order to develop the evaluative skills necessary for successful performance of design, a senior, Geotechnical Engineering course was revised to immerse students in the complexity of the design process utilising a project-based learning (PBL) approach to instruction. The student-centred approach stresses self-directed group learning, which…
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 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.
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.
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,…
Approaches to Studying, Conceptions of Learning and Learning Styles in Higher Education
ERIC Educational Resources Information Center
Richardson, John T. E.
2011-01-01
Learning styles have been construed in different ways but traditionally have been regarded as relatively stable. In contrast, the "student approaches to learning" perspective tends to assume that approaches to studying are contextually driven. This article argues for a rapprochement between these two traditions. First, the evidence that students'…
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 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…
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…
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…
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.
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.
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.
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.
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…
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…
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:…
Inquiry Role Approach: A Model for Counselor Involvement in Learning.
ERIC Educational Resources Information Center
Bingman, Richard M.; And Others
The Inquiry Role Approach (IRA) is a strategy for classroom learning in which students work as 4-member teams and assume roles as Team Coordinator, Process Advisor, Data Recorder, and Technical Advisor. Cognitive as well as affective objectives are identified which relate to optimum learning and personal growth in the classroom. The counselor's…
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…
Digital Games and Learning in Cyberspace: A Dialogical Approach
ERIC Educational Resources Information Center
Ravenscroft, Andrew; McAlister, Simon
2006-01-01
Currently there is considerable enthusiasm for exploring how we can apply digital gaming paradigms to learning. But these approaches are often weak in linking the game-playing activity to transferable social or conceptual processes and skills that constitute, or are related to, learning. In contrast, this article describes a "dialogue…
A Motivational Approach to Student Learning: The Landlord Technique.
ERIC Educational Resources Information Center
Lanford, Horace
A motivational approach to student learning that has been implemented in several courses at Wright University in Ohio consists of six efforts: (1) to instill in students the knowledge of motivation, both from within and without; (2) to make students members of cohesive work groups; (3) to apply theory learned; (4) to demonstrate achievement of…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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:…
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…
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…
Designing Interactive Learning Environments: An Approach from First Principles
ERIC Educational Resources Information Center
Scott, Bernard; Cong, Chunyu
2007-01-01
Purpose: Today's technology supports the design of more and more sophisticated interactive learning environments. This paper aims to argue that such design should develop from first principles. Design/methodology/approach: In the paper by first principles is meant: learning theory and principles of course design. These principles are briefly…
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,…
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…
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…
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…
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…
ERIC Educational Resources Information Center
Tsai, Chia-Hui; Cheng, Ching-Hsue; Yeh, Duen-Yian; Lin, Shih-Yun
2017-01-01
This study applied a quasi-experimental design to investigate the influence and predictive power of learner motivation for achievement, employing a mobile game-based English learning approach. A system called the Happy English Learning System, integrating learning material into a game-based context, was constructed and installed on mobile devices…
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
2008-01-01
and † denotes the Moore - Penrose inverse . Eq. (3) asks Â to minimize the error in predicting the state at time t + 1 from the state at time t. Given...A Constraint Generation Approach to Learning Stable Linear Dynamical Systems Sajid M. Siddiqi Byron Boots Geoffrey J. Gordon January 2008...REPORT DATE JAN 2008 2. REPORT TYPE 3. DATES COVERED 00-00-2008 to 00-00-2008 4. TITLE AND SUBTITLE A Constraint Generation Approach to Learning
Mammogram segmentation using maximal cell strength updation in cellular automata.
Anitha, J; Peter, J Dinesh
2015-08-01
Breast cancer is the most frequently diagnosed type of cancer among women. Mammogram is one of the most effective tools for early detection of the breast cancer. Various computer-aided systems have been introduced to detect the breast cancer from mammogram images. In a computer-aided diagnosis system, detection and segmentation of breast masses from the background tissues is an important issue. In this paper, an automatic segmentation method is proposed to identify and segment the suspicious mass regions of mammogram using a modified transition rule named maximal cell strength updation in cellular automata (CA). In coarse-level segmentation, the proposed method performs an adaptive global thresholding based on the histogram peak analysis to obtain the rough region of interest. An automatic seed point selection is proposed using gray-level co-occurrence matrix-based sum average feature in the coarse segmented image. Finally, the method utilizes CA with the identified initial seed point and the modified transition rule to segment the mass region. The proposed approach is evaluated over the dataset of 70 mammograms with mass from mini-MIAS database. Experimental results show that the proposed approach yields promising results to segment the mass region in the mammograms with the sensitivity of 92.25% and accuracy of 93.48%.
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.
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…
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…
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…
Creating Participatory Online Learning Environments: A Social Learning Approach Revisited
ERIC Educational Resources Information Center
Conley, Quincy; Lutz, Heather S.; Padgitt, Amanda J.
2017-01-01
Online learning has never been more popular than it is today. Due to the rapid growth of online instruction at colleges and universities, questions about the effectiveness of online courses have been raised. In this paper, we suggest guidelines for the selection and application of social media tools. In addition to describing the potential…
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…
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.
An active learning approach to Bloom's Taxonomy.
Weigel, Fred K; Bonica, Mark
2014-01-01
As educators strive toward improving student learning outcomes, many find it difficult to instill their students with a deep understanding of the material the instructors share. One challenge lies in how to provide the material with a meaningful and engaging method that maximizes student understanding and synthesis. By following a simple strategy involving Active Learning across the 3 primary domains of Bloom's Taxonomy (cognitive, affective, and psychomotor), instructors can dramatically improve the quality of the lesson and help students retain and understand the information. By applying our strategy, instructors can engage their students at a deeper level and may even find themselves enjoying the process more.
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…
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…
An approach to explainable deep learning using fuzzy inference
NASA Astrophysics Data System (ADS)
Bonanno, David; Nock, Kristen; Smith, Leslie; Elmore, Paul; Petry, Fred
2017-05-01
Deep Learning has proven to be an effective method for making highly accurate predictions from complex data sources. Convolutional neural networks continue to dominate image classification problems and recursive neural networks have proven their utility in caption generation and language translations. While these approaches are powerful, they do not offer explanation for how the output is generated. Without understanding how deep learning arrives at a solution there is no guarantee that these networks will transition from controlled laboratory environments to fieldable systems. This paper presents an approach for incorporating such rule based methodology into neural networks by embedding fuzzy inference systems into deep learning networks.
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…
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…
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…
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…
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…
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…
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…
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…
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…
A psychological approach to learning causal networks.
Zargoush, Manaf; Alemi, Farrokh; Esposito Vinzi, Vinzenzo; Vang, Jee; Kheirbek, Raya
2014-06-01
We examine the role of a common cognitive heuristic in unsupervised learning of Bayesian probability networks from data. Human beings perceive a larger association between causal than diagnostic relationships. This psychological principal can be used to orient the arcs within Bayesian networks by prohibiting the direction that is less predictive. The heuristic increased predictive accuracy by an average of 0.51 % percent, a small amount. It also increased total agreement between different network learning algorithms (Max Spanning Tree, Taboo, EQ, SopLeq, and Taboo Order) by 25 %. Prior to use of the heuristic, the multiple raters Kappa between the algorithms was 0.60 (95 % confidence interval, CI, from 0.53 to 0.67) indicating moderate agreement among the networks learned through different algorithms. After the use of the heuristic, the multiple raters Kappa was 0.85 (95 % CI from 0.78 to 0.92). There was a statistically significant increase in agreement between the five algorithms (alpha < 0.05). These data suggest that the heuristic increased agreement between networks learned through use of different algorithms, without loss of predictive accuracy. Additional research is needed to see if findings persist in other data sets and to explain why a heuristic used by humans could improve construct validity of mathematical algorithms.
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.
Approach and avoidance learning in obsessive-compulsive disorder.
Endrass, Tanja; Kloft, Lisa; Kaufmann, Christian; Kathmann, Norbert
2011-02-01
Current neurobiological models of obsessive-compulsive disorder (OCD) propose a dysfunction of cortico-striato-thalamo-cortical circuits that leads to enhanced activity in frontal and striatal brain regions. In accordance with that, OCD patients show alterations in learning and flexible adaptation to changing task requirements. The purpose of this study was to examine feedback-based learning and to investigate whether learning from positive and negative feedback is differentially altered in OCD. In this study, 18 OCD patients and 18 healthy comparison subjects conducted a probabilistic selection task. The task consisted of an acquisition and a test phase and allowed disentangling the extent of learning based on positive and negative feedback. Groups did not differ during probabilistic feedback learning in the acquisition phase. In the test phase, OCD patients showed a negative learning bias in contrast to comparison subjects who showed a positive learning bias. Patients were better at avoiding stimuli that were initially associated with negative outcomes than at approaching stimuli that were associated with positive feedbacks. This interaction was also found for reaction times in that patients were faster in avoiding negative and slower in approaching positive stimuli. Enhanced avoidance learning was found in OCD patients that points to exaggerated anticipation and avoidance of aversive outcomes. Further studies are required to investigate whether neurobiological mechanisms, such as dopaminergic signaling or outcome processing, in the orbitofrontal cortex relate to enhanced negative learning in OCD. © 2010 Wiley-Liss, Inc.
Machine learning: novel bioinformatics approaches for combating antimicrobial resistance.
Macesic, Nenad; Polubriaginof, Fernanda; Tatonetti, Nicholas P
2017-09-12
Antimicrobial resistance (AMR) is a threat to global health and new approaches to combating AMR are needed. Use of machine learning in addressing AMR is in its infancy but has made promising steps. We reviewed the current literature on the use of machine learning for studying bacterial AMR. The advent of large-scale data sets provided by next-generation sequencing and electronic health records make applying machine learning to the study and treatment of AMR possible. To date, it has been used for antimicrobial susceptibility genotype/phenotype prediction, development of AMR clinical decision rules, novel antimicrobial agent discovery and antimicrobial therapy optimization. Application of machine learning to studying AMR is feasible but remains limited. Implementation of machine learning in clinical settings faces barriers to uptake with concerns regarding model interpretability and data quality.Future applications of machine learning to AMR are likely to be laboratory-based, such as antimicrobial susceptibility phenotype prediction.
Learning disabilities and learned helplessness: a heuristic approach.
Hersh, C A; Stone, B J; Ford, L
1996-02-01
This study investigated whether students with learning disabilities exhibited learned helpless behavior at a greater rate than their normal achieving peers when confronted with reading failure. Forty-five third grade students from a suburban elementary schools were participants in the study. Thirty of the subjects were classified as having a learning disability (LD) and the remaining 15 subjects were from regular education (RE) classrooms. Fifteen of the students with LD were placed in the treatment group and the remaining fifteen were placed in the control group. All the regular education students were placed in the treatment group. After randomly assigning the students with LD into either a treatment (stressed) group or a control (nonstressed) group, the stressed students were administered a reading instrument in order to measure how they dealt with failure. A one-way ANCOVA was conducted to determine whether significant differences existed between the groups based on their posttest scores. The results indicate that stressed students with LD have a significantly more difficult time recovering from stress than their regular education peers.
NASA Astrophysics Data System (ADS)
Wolnik, Barbara; Dembowski, Marcin; Bołt, Witold; Baetens, Jan M.; De Baets, Bernard
2017-08-01
The focus of this paper is on the density classification problem in the context of affine continuous cellular automata. Although such cellular automata cannot solve this problem in the classical sense, most density-conserving affine continuous cellular automata with a unit neighborhood radius are valid solutions of a slightly relaxed version of this problem. This result follows from a detailed study of the dynamics of the density-conserving affine continuous cellular automata that we introduce.
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.
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.
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…
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…
Instructional Systems for Student Learning: The Burlington County College Approach.
ERIC Educational Resources Information Center
Evans, N. Dean, Ed.
Since its inception in 1969, Burlington County College (New Jersey) has been dedicated to implementing a systematically designed approach to instruction and student learning. The core elements of the approach are as follows: (1) development of a basic college philosophy; (2) specification of general institutional objectives; (3) selection of…
Measuring University Students' Approaches to Learning Statistics: An Invariance Study
ERIC Educational Resources Information Center
Chiesi, Francesca; Primi, Caterina; Bilgin, Ayse Aysin; Lopez, Maria Virginia; del Carmen Fabrizio, Maria; Gozlu, Sitki; Tuan, Nguyen Minh
2016-01-01
The aim of the current study was to provide evidence that an abbreviated version of the Approaches and Study Skills Inventory for Students (ASSIST) was invariant across different languages and educational contexts in measuring university students' learning approaches to statistics. Data were collected on samples of university students attending…
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:…
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:…
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…
Measuring University Students' Approaches to Learning Statistics: An Invariance Study
ERIC Educational Resources Information Center
Chiesi, Francesca; Primi, Caterina; Bilgin, Ayse Aysin; Lopez, Maria Virginia; del Carmen Fabrizio, Maria; Gozlu, Sitki; Tuan, Nguyen Minh
2016-01-01
The aim of the current study was to provide evidence that an abbreviated version of the Approaches and Study Skills Inventory for Students (ASSIST) was invariant across different languages and educational contexts in measuring university students' learning approaches to statistics. Data were collected on samples of university students attending…
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…
A Supervised Learning Approach to Monaural Segregation of Reverberant Speech
2008-02-01
Supervised Learning Approach to Monaural Segregation of Reverberant Speech Zhaozhang Jin Department of Computer Science and Engineering The Ohio State...room reverberation. Monaural speech segregation in reverberant environments is a particularly challenging prob- lem. Although inverse filtering has...been proposed to partially restore the harmonicity of reverberant speech before segregation, this approach is sensitive to specific source/receiver and
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…
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…
Machine learning and computer vision approaches for phenotypic profiling.
Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J
2017-01-02
With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.
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
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.
Learning styles and approaches to learning among medical undergraduates and postgraduates.
Samarakoon, Lasitha; Fernando, Tharanga; Rodrigo, Chaturaka
2013-03-25
The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners.Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period.
Learning styles and approaches to learning among medical undergraduates and postgraduates
2013-01-01
Background The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. Methods We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. Results A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners. Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. Conclusions The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period. PMID:23521845
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%).
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
Cellular Automata as a Computational Model for Low-Level Vision
NASA Astrophysics Data System (ADS)
Broggi, Alberto; D'Andrea, Vincenzo; Destri, Giulio
In this paper we discuss the use of the Cellular Automata (CA) computational model in computer vision applications on massively parallel architectures. Motivations and guidelines of this approach to low-level vision in the frame of the PROMETHEUS project are discussed. The hard real-time requirement of actual application can be only satisfied using an ad hoc VLSI massively parallel architecture (PAPRICA). The hardware solutions and the specific algorithms can be efficiently verified and tested only using, as a simulator, a general purpose machine with a parent architecture (CM-2). An example of application related to feature extraction is discussed.
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.
Two approaches, one course: an experience in experiential learning.
Lien, Ashlee D; Hakim, Sharon M
2013-01-01
In universities where experiential learning is not the norm, introducing this style of learning into undergraduate courses can be an intimidating process for both instructors and students. Instructors are often unsure of how to manage student experiences in the community, while a significant number of students react with skepticism toward this new type of course, as well as concern about their instructor's changing expectations for their performance. The following is a reflection of our first 2 years of teaching undergraduate courses from a distinctly experiential learning approach. Qualitative data is used to highlight the parallel learning processes that occurred over the semester, for students as well as for us as instructors. Our biggest challenges are explored in detail, and advice to instructors contemplating adapting an experiential approach to their own courses is presented.
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…
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'…
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.
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.
A blended learning approach to teaching CVAD care and maintenance.
Hainey, Karen; Kelly, Linda J; Green, Audrey
2017-01-26
Nurses working within both acute and primary care settings are required to care for and maintain central venous access devices (CVADs). To support these nurses in practice, a higher education institution and local health board developed and delivered CVAD workshops, which were supported by a workbook and competency portfolio. Following positive evaluation of the workshops, an electronic learning (e-learning) package was also introduced to further support this clinical skill in practice. To ascertain whether this blended learning approach to teaching CVAD care and maintenance prepared nurses for practice, the learning package was evaluated through the use of electronic questionnaires. Results highlighted that the introduction of the e-learning package supported nurses' practice, and increased their confidence around correct clinical procedures.
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…
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…
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…
ERIC Educational Resources Information Center
Spronken-Smith, Rachel; Walker, Rebecca; Batchelor, Julie; O'Steen, Billy; Angelo, Tom
2012-01-01
Inquiry-based learning (IBL) is promoted as a teaching approach that can enhance student learning outcomes. IBL can be categorised according to scale (e.g. tasks, course/module/paper, degree), mode (structured, guided, open) and framing (information or discovery-oriented). Our research used a survey instrument to determine how student perceptions…
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…
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…
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 appropriate,…
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…
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
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…
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…
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…
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…
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…
ERIC Educational Resources Information Center
She, Hsiao-Ching
2005-01-01
The author explored the potential to promote students' understanding of difficult science concepts through an examination of the inter-relationships among the teachers' instructional approach, students' learning preference styles, and their levels of learning process. The concept "air pressure," which requires an understanding of…
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-01-01
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-03-29
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.
University students' achievement goals and approaches to learning in mathematics.
Cano, Francisco; Berbén, A B G
2009-03-01
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. This study sets out: (a) to explore the relationship between the most representative variables of SAL and AG; (b) to identify subgroups (clusters) of students with multiple AG; and (c) to examine the differences between these clusters with respect to various SAL and AG characteristics. The participants were 680 male and female 1st year university students studying different subjects (e.g. mathematics, physics, economics) but all enrolled on mathematics courses (e.g. algebra, calculus). Participants completed a series of questionnaires that measured their conceptions of mathematics, approaches to learning, course experience, personal 2 x 2 AG, and perceived AG. SAL and AG variables were moderately associated and related to both the way students perceived their academic environment and the way they conceived of the nature of mathematics (i.e. the perceptual-cognitive framework). Four clusters of students with distinctive multiple AG were identified and when the differences between clusters were analysed, we were able to attribute them to various constructs including perceptual-cognitive framework, learning approaches, and academic performance. This study reveals a consistent pattern of relationships between SAL and AG perspectives across different methods of analysis, supports the relevance of the 2 x 2 AG framework in a mathematics learning context and suggests that AG and SAL may be intertwined aspects of students' experience of learning mathematics at university.
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
On the topological sensitivity of cellular automata.
Baetens, Jan M; De Baets, Bernard
2011-06-01
Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.
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.
On the topological sensitivity of cellular automata
NASA Astrophysics Data System (ADS)
Baetens, Jan M.; De Baets, Bernard
2011-06-01
Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.
Programmable DNA-Based Finite Automata
NASA Astrophysics Data System (ADS)
Ratner, Tamar; Keinan, Ehud
Computation using DNA has many advantages, including the potential for massive parallelism that allows for large number of operations per second, the direct interface between the computation process and a biological output, and the miniaturization of the computing devices to a molecular scale. In 2001, we reported on the first DNA-based, programmable finite automaton (2-symbol-2-state) capable of computing autonomously with all its hardware, software, input, and output being soluble biomolecules mixed in solution. Later, using similar principles, we developed advanced 3-symbol-3-state automata. We have also shown that real-time detection of the output signal, as well as real-time monitoring of all the computation intermediates, can be achieved by the use of surface plasmon resonance (SPR) technology. More recently, we have shown that it is possible to achieve a biologically relevant output, such as specific gene expression, by using a reporter-gene as an output-readout. We cloned the input into circular plasmids, and thereby achieved control over gene expression by a programmable sequence of computation events. Further efforts are currently directed to immobilization of the input molecules onto a solid chip to enable parallel computation, where the location of the input on the chip represents specific tagging.
Quantum models as classical cellular automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2017-05-01
A synopsis is offered of the properties of discrete and integer-valued, hence “natural”, cellular automata (CA). A particular class comprises the “Hamiltonian CA” with discrete updating rules that resemble Hamilton’s equations. The resulting dynamics is linear like the 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 l. Consequently, there is a one-to-one correspondence of quantum mechanical and CA conservation laws. We discuss the important issue of linearity, recalling that nonlinearities imply nonlocal effects in the continuous quantum mechanical description of intrinsically local discrete CA - requiring locality entails linearity. The admissible CA observables and the existence of solutions of the l-dependent dispersion relation for stationary states are mentioned, besides the construction of multipartite CA obeying the Superposition Principle. We point out problems when trying to match the deterministic CA here to those envisioned in ‘t Hooft’s CA Interpretation of Quantum Mechanics.
Students awareness of learning styles and their perceptions to a mixed method approach for learning.
Bhagat, Anumeha; Vyas, Rashmi; Singh, Tejinder
2015-08-01
Individualization of instructional method does not contribute significantly to learning outcomes although it is known that students have differing learning styles (LSs). Hence, in order to maximally enhance learning, one must try to use a mixed method approach. Our hypothesis was that awareness of preferred LS and motivation to incorporate multiple learning strategies might enhance learning outcomes. Our aim was to determine the impact of awareness of LS among medical undergraduates and motivating students to use mixed methods of learning. Before awareness lecture, LS preferences were determined using Visual, Aural, Read/Write, and Kinesthetic (VARK) questionnaire. Awareness of LS was assessed using a validated questionnaire. Through a lecture, students were oriented to various LSs, impact of LS on their performance, and benefit of using mixed method approach for learning. Subsequently, group discussions were organized. After 3 months, VARK preferences and awareness of LSs were reassessed. Student narratives were collected. Qualitative analysis of the data was done. There was a significant increase in the number of students who were aware of LS. The number of participants showing a change in VARK scores for various modalities of learning was also significant (P < 0.001). Thus, awareness of LSs motivated students to adapt other learning strategies and use mixed methods for learning.
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
Learning about Aboriginal contexts: the reading circle approach.
Begoray, Deborah L; Banister, Elizabeth
2008-07-01
As more opportunities arise for nursing students to obtain experience in community sites, they will be called on to practice in culturally appropriate ways more often. Although nurses remain challenged by the range of populations needing differentiated approaches, Aboriginal cultural contexts deserve special attention. Nurse educators must help students increase their understanding of Aboriginal life and ways of knowing. One way to facilitate this understanding is through a learning approach called reading circles. Reading circles offer a structure in the classroom for students to interact about ideas or readings. The reading circle process is congruent with Aboriginal ways of learning, which emphasize working in circle, with each member having a role and an equal chance to be heard. Aboriginal students in the class may be particularly comfortable with this learning method. This article describes specific steps for incorporating the reading circle approach into the nurse education classroom.
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…
Learning with PROLOG--A New Approach.
ERIC Educational Resources Information Center
Scherz, Zahava; And Others
1986-01-01
Discusses the features and advantages of the computer language PROLOG, and explains the approach taken in teaching it as a first computer language. Includes an example of the use of PROLOG in programming a science lesson on elements for junior high students. (ML)
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.
Irreversibility and dissipation in finite-state automata
NASA Astrophysics Data System (ADS)
Ganesh, Natesh; Anderson, Neal G.
2013-12-01
Irreversibility and dissipation in finite-state automata (FSA) are considered from a physical-information-theoretic perspective. A quantitative measure for the computational irreversibility of finite automata is introduced, and a fundamental lower bound on the average energy dissipated per state transition is obtained and expressed in terms of FSA irreversibility. The irreversibility measure and energy bound are germane to any realization of a deterministic automaton that faithfully registers abstract FSA states in distinguishable states of a physical system coupled to a thermal environment, and that evolves via a sequence of interactions with an external system holding a physical instantiation of a random input string. The central result, which is shown to follow from quantum dynamics and entropic inequalities alone, can be regarded as a generalization of Landauer's Principle applicable to FSAs and tailorable to specified automata. Application to a simple FSA is illustrated.
ERIC Educational Resources Information Center
Asikainen, Henna; Gijbels, David
2017-01-01
The focus of the present paper is on the contribution of the research in the student approaches to learning tradition. Several studies in this field have started from the assumption that students' approaches to learning develop towards more deep approaches to learning in higher education. This paper reports on a systematic review of longitudinal…
Spectral Approaches to Learning Predictive Representations
2012-09-01
covariance matrices. The key to this approach is that, for linear dynamical systems, there are many possible equivalent representations for the same system...That is, two LDSs are said to be equivalent if the second order statistics of the output generated by the models is the same, i.e. the covariance...from the filter are similarly equivalent . See Equations 2.20 below for more details. Practically, the equivalence of transformed LDSs means that we can
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
Simulation of interdiffusion and voids growth based on cellular automata
NASA Astrophysics Data System (ADS)
Zhang, Fan; Zhang, Boyan; Zhang, Nan; Du, Haishun; Zhang, Xinhong
2017-02-01
In the interdiffusion of two solid-state materials, if the diffusion coefficients of the two materials are not the same, the interface of the two materials will shift to the material with the lower diffusion coefficient. This effect is known as the Kirkendall effect. The Kirkendall effect leads to Kirkendall porosity. The pores act as sinks for vacancies and become voids. In this paper, the movement of the Kirkendall plane at interdiffusion is simulated based on cellular automata. The number of vacancies, the critical radius of voids nucleation and the nucleation rate are analysed. The vacancies diffusion, vacancies aggregation and voids growth are also simulated based on cellular automata.
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.
Children's science learning: A core skills approach.
Tolmie, Andrew K; Ghazali, Zayba; Morris, Suzanne
2016-09-01
Research has identified the core skills that predict success during primary school in reading and arithmetic, and this knowledge increasingly informs teaching. However, there has been no comparable work that pinpoints the core skills that underlie success in science. The present paper attempts to redress this by examining candidate skills and considering what is known about the way in which they emerge, how they relate to each other and to other abilities, how they change with age, and how their growth may vary between topic areas. There is growing evidence that early-emerging tacit awareness of causal associations is initially separated from language-based causal knowledge, which is acquired in part from everyday conversation and shows inaccuracies not evident in tacit knowledge. Mapping of descriptive and explanatory language onto causal awareness appears therefore to be a key development, which promotes unified conceptual and procedural understanding. This account suggests that the core components of initial science learning are (1) accurate observation, (2) the ability to extract and reason explicitly about causal connections, and (3) knowledge of mechanisms that explain these connections. Observational ability is educationally inaccessible until integrated with verbal description and explanation, for instance, via collaborative group work tasks that require explicit reasoning with respect to joint observations. Descriptive ability and explanatory ability are further promoted by managed exposure to scientific vocabulary and use of scientific language. Scientific reasoning and hypothesis testing are later acquisitions that depend on this integration of systems and improved executive control. © 2016 The British Psychological Society.
[Epilepsy and learning: a neuropsychological approach].
Etchepareborda, M C
1999-02-01
The quality of life of an epileptic patient largely depends on the interplay of the control of the convulsive crises and the degree to which higher mental functions are affected. Some types of epilepsy lead to mental retardation during development and with others the basic cerebral mechanisms for processing data are damaged and this may lead to transient or permanent cogniscitive deterioration. There are certain important clinical factors such as the site of the discharge regarding the lobe, hemisphere, type of cerebral area involved and the age of the patient. We describe the clinical features of each type of epilepsy with respect to focal or generalized involvement. The subclinical effects of continuous discharges affects processing in the areas involved and therefore intellectual function, thus leading to a secondary learning disorder. The neuropsychological tests used in investigation of higher cerebral functions in epilepsy include, in general, tests to assess speed of processing, attention, memory, reasoning and visuospacial ability and frontal executive functions. These tests should be sufficiently sensitive so as to detect minimal changes in the state of the illness, the time elapsed and the medication given. Anticonvulsant drugs may themselves cause changes in mental functions. There may often be mixed neurocognitive behaviour depending on the drug used. There may also be transient cognitive deterioration.
Approach for Using Learner Satisfaction to Evaluate the Learning Adaptation Policy
ERIC Educational Resources Information Center
Jeghal, Adil; Oughdir, Lahcen; Tairi, Hamid; Radouane, Abdelhay
2016-01-01
The learning adaptation is a very important phase in a learning situation in human learning environments. This paper presents the authors' approach used to evaluate the effectiveness of learning adaptive systems. This approach is based on the analysis of learner satisfaction notices collected by a questionnaire on a learning situation; to analyze…
Approach for Using Learner Satisfaction to Evaluate the Learning Adaptation Policy
ERIC Educational Resources Information Center
Jeghal, Adil; Oughdir, Lahcen; Tairi, Hamid; Radouane, Abdelhay
2016-01-01
The learning adaptation is a very important phase in a learning situation in human learning environments. This paper presents the authors' approach used to evaluate the effectiveness of learning adaptive systems. This approach is based on the analysis of learner satisfaction notices collected by a questionnaire on a learning situation; to analyze…
Mayya, Shreemathi S; Rao, A Krishna; Ramnarayan, K
2002-11-01
This study explored the difference in learning approaches and difficulties of Nepali and Indian undergraduate students of dental science. A locally developed inventory was used to measure learning approach and learning difficulties. Data collected from 166 Indians and 69 Nepalis were compared. The scores on various scales of the inventory indicate that Nepalis are more fearful and less confident regarding examination and course completion and have significantly less positive perception about academic capability. Indian students scored significantly higher on motivation, interest, and deep processing. The language problem was significantly greater for Nepali students. Higher percentages of Nepalis experienced various academic and nonacademic problems. The study highlights the need to consider difference in learning approach among the students of health science courses that admit students from different academic, nonacademic, and cultural backgrounds.
A peer assessment approach for learning from public health emergencies.
Piltch-Loeb, Rachael N; Nelson, Christopher D; Kraemer, John D; Savoia, Elena; Stoto, Michael A
2014-01-01
As an alternative to standard quality improvement approaches and to commonly used after action report/improvement plans, we developed and tested a peer assessment approach for learning from singular public health emergencies. In this approach, health departments engage peers to analyze critical incidents, with the goal of aiding organizational learning within and across public health emergency preparedness systems. We systematically reviewed the literature in this area, formed a practitioner advisory panel to help translate these methods into a protocol, applied it retrospectively to case studies, and later field-tested the protocol in two locations. These field tests and the views of the health professionals who participated in them suggest that this peer-assessment approach is feasible and leads to a more in-depth analysis than standard methods. Engaging people involved in operating emergency health systems capitalizes on their professional expertise and provides an opportunity to identify transferable best practices.
A Peer Assessment Approach for Learning from Public Health Emergencies
Piltch-Loeb, Rachael N.; Nelson, Christopher D.; Kraemer, John D.; Savoia, Elena
2014-01-01
As an alternative to standard quality improvement approaches and to commonly used after action report/improvement plans, we developed and tested a peer assessment approach for learning from singular public health emergencies. In this approach, health departments engage peers to analyze critical incidents, with the goal of aiding organizational learning within and across public health emergency preparedness systems. We systematically reviewed the literature in this area, formed a practitioner advisory panel to help translate these methods into a protocol, applied it retrospectively to case studies, and later field-tested the protocol in two locations. These field tests and the views of the health professionals who participated in them suggest that this peer-assessment approach is feasible and leads to a more in-depth analysis than standard methods. Engaging people involved in operating emergency health systems capitalizes on their professional expertise and provides an opportunity to identify transferable best practices. PMID:25355972
System learning approach to assess sustainability and ...
This paper presents a methodology that combines the power of an Artificial Neural Network and Information Theory to forecast variables describing the condition of a regional system. The novelty and strength of this approach is in the application of Fisher information, a key method in Information Theory, to preserve trends in the historical data and prevent over fitting projections. The methodology was applied to demographic, environmental, food and energy consumption, and agricultural production in the San Luis Basin regional system in Colorado, U.S.A. These variables are important for tracking conditions in human and natural systems. However, available data are often so far out of date that they limit the ability to manage these systems. Results indicate that the approaches developed provide viable tools for forecasting outcomes with the aim of assisting management toward sustainable trends. This methodology is also applicable for modeling different scenarios in other dynamic systems. Indicators are indispensable for tracking conditions in human and natural systems, however, available data is sometimes far out of date and limit the ability to gauge system status. Techniques like regression and simulation are not sufficient because system characteristics have to be modeled ensuring over simplification of complex dynamics. This work presents a methodology combining the power of an Artificial Neural Network and Information Theory to capture patterns in a real dyna
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
Promoting learning transfer in post registration education: a collaborative approach.
Finn, Frances L; Fensom, Sue A; Chesser-Smyth, Patricia
2010-01-01
Pre-registration nurse education in Ireland became a four year undergraduate honors degree programme in 2002 (Government of Ireland, 2000. The Nursing Education Forum Report. Dublin, Dublin Stationary Office.). Consequently, the Irish Government invested significant resources in post registration nursing education in order to align certificate and diploma trained nurses with the qualification levels of new graduates. However, a general concern amongst academic and clinical staff in the South East of Ireland was that there was limited impact of this initiative on practice. These concerns were addressed through a collaborative approach to the development and implementation of a new part-time post registration degree that incorporated an enquiry and practice based learning philosophy. The principles of learning transfer (Ford, K., 1994. Defining transfer of learning the meaning is in the answers. Adult Learning 5 (4), p. 2214.) underpinned the curriculum development and implementation process with the goal of reducing the theory practice gap. This paper reports on all four stages of the curriculum development process: exploration, design, implementation and evaluation (Quinn, F.M., 2002. Principles and Practices of Nurse Education, fourth ed. Nelson Thornes, Cheltenham), and the subsequent impact of learning transfer on practice development. Eclectic approaches of quantitative and qualitative data collection techniques were utilised in the evaluation. The evaluation of this project to date supports our view that this practice based enquiry curriculum promotes the transfer of learning in the application of knowledge to practice, impacting both student and service development.
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.
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.…
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.…
Machine-learning approaches in drug discovery: methods and applications.
Lavecchia, Antonio
2015-03-01
During the past decade, virtual screening (VS) has evolved from traditional similarity searching, which utilizes single reference compounds, into an advanced application domain for data mining and machine-learning approaches, which require large and representative training-set compounds to learn robust decision rules. The explosive growth in the amount of public domain-available chemical and biological data has generated huge effort to design, analyze, and apply novel learning methodologies. Here, I focus on machine-learning techniques within the context of ligand-based VS (LBVS). In addition, I analyze several relevant VS studies from recent publications, providing a detailed view of the current state-of-the-art in this field and highlighting not only the problematic issues, but also the successes and opportunities for further advances. Copyright © 2014 Elsevier Ltd. All rights reserved.
Understanding the science-learning environment: A genetically sensitive approach.
Haworth, Claire M A; Davis, Oliver S P; Hanscombe, Ken B; Kovas, Yulia; Dale, Philip S; Plomin, Robert
2013-02-01
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 pairs of 14-year-old twins from the UK Twins Early Development Study reported on their experiences of the science-learning environment and were assessed for their performance in science using a web-based test of scientific enquiry. Multivariate twin analyses were used to investigate the genetic and environmental links between environment and outcome. The most surprising result was that the science-learning environment was almost as heritable (43%) as performance on the science test (50%), and showed negligible shared environmental influence (3%). Genetic links explained most (56%) of the association between learning environment and science outcome, indicating gene-environment correlation.
Understanding the science-learning environment: A genetically sensitive approach
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 pairs of 14-year-old twins from the UK Twins Early Development Study reported on their experiences of the science-learning environment and were assessed for their performance in science using a web-based test of scientific enquiry. Multivariate twin analyses were used to investigate the genetic and environmental links between environment and outcome. The most surprising result was that the science-learning environment was almost as heritable (43%) as performance on the science test (50%), and showed negligible shared environmental influence (3%). Genetic links explained most (56%) of the association between learning environment and science outcome, indicating gene–environment correlation. PMID:23565044
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.
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.…
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.…
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,…
An Independent Learning Approach to Piano Sight Reading.
ERIC Educational Resources Information Center
Sorel, Claudette; Diamond, Robert M.
The ability to sight read music accurately and artistically is important for pianists, expecially those who intend to become teachers and accompanists. Yet instruction in this skill is rarely available. An independent learning approach based on tachistoscopic speed reading techniques (i.e. controlled exposure) was evaluated for reducing sight…
Team Building: A Structured Learning Approach. Instructor's Manual.
ERIC Educational Resources Information Center
Mears, Peter; Voehl, Frank
This publication is an instructor's manual to a course on developing empowered management teams for higher education, teamworking skills, and team role evaluation skills. The course itself takes a hands-on approach to learning about quality, introduces continuous quality improvement principles, asks students to apply these in a structured…
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…
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…
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…
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…
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…
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,…
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…
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…
Defining Leadership: Collegiate Women's Learning Circles: A Qualitative Approach
ERIC Educational Resources Information Center
Preston-Cunningham, Tammie; Elbert, Chanda D.; Dooley, Kim E.
2017-01-01
The researchers employed qualitative methods to evaluate first-year female students' definition of "leadership" through involvement in the Women's Learning Circle. The findings revealed that students defined leadership in two dimensions: traits and behaviors. The qualitative findings explore a multidimensional approach to the voices of…
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,…
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…
Taking Laptops Schoolwide: A Professional Learning Community Approach
ERIC Educational Resources Information Center
Green, Tim; Donovan, Loretta; Bass, Kim
2010-01-01
A defined collaboration, such as a Professional Learning Community (PLC), can help expand a one-to-one program. In this article, the authors discuss four factors to consider in starting a collaborative approach at one's school: (1) school climate; (2) communication; (3) collaboration; and (4) progression of use.
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…
Teaching and Learning Cycles in a Constructivist Approach to Instruction
ERIC Educational Resources Information Center
Singer, Florence Mihaela; Moscovici, Hedy
2008-01-01
This study attempts to analyze and synthesize the knowledge collected in the area of conceptual models used in teaching and learning during inquiry-based projects, and to propose a new frame for organizing the classroom interactions within a constructivist approach. The IMSTRA model consists in three general phases: Immersion, Structuring,…
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…
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…
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…
Evaluating Experiential Learning Programs: The Case Study Approach.
ERIC Educational Resources Information Center
Stevenson, Robert
1985-01-01
Demonstrates how case study evaluation concentrates on a single situation to present a holistic view of an experiential learning program and reveals unique and unanticipated features. Outlines steps of planning, gathering, analyzing, synthesizing, and reporting data and considers the advantages and disadvantages of the case study approach. (LFL)
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…
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…