Rule Extraction, Fuzzy ARTMAP, and Medical Databases

This paper shows how knowledge, in the form of fuzzy rules, can be derived from a self-organizing supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning removes those recognition nodes whose confidence index falls below a selected threshold; and quantization of continuous learned weights allows the final system state to be translated into a usable set of rules. Simulations on a medical prediction problem, the Pima Indian Diabetes (PID) database, illustrate the method. In the simulations, pruned networks about 1/3 the size of the original actually show improved performance. Quantization yields comprehensible rules with only slight degradation in test set prediction performance.British Petroleum (89-A-1204); Defense Advanced Research Projects Agency (AFOSR-90-0083, ONR-N00014-92-J-4015); National Science Foundation (IRI-90-00530); Office of Naval Research (N00014-91-J-4100); Air Force Office of Scientific Research (90-0083); Institute of Systems Science (National University of Singapore

Time Quantified Monte Carlo Algorithm for Interacting Spin Array Micromagnetic Dynamics

In this paper, we reexamine the validity of using time quantified Monte Carlo (TQMC) method [Phys. Rev. Lett. 84, 163 (2000); Phys. Rev. Lett. 96, 067208 (2006)] in simulating the stochastic dynamics of interacting magnetic nanoparticles. The Fokker-Planck coefficients corresponding to both TQMC and Langevin dynamical equation (Landau-Lifshitz-Gilbert, LLG) are derived and compared in the presence of interparticle interactions. The time quantification factor is obtained and justified. Numerical verification is shown by using TQMC and Langevin methods in analyzing spin-wave dispersion in a linear array of magnetic nanoparticles.Comment: Accepted for publication in Phys. Rev.

Solving the Master Equation for Extremely Long Time Scale Calculations

The dynamics of magnetic reversal process plays an important role in the design of the magnetic recording devices in the long time scale limit. In addition to long time scale, microscopic effects such as the entropic effect become important in magnetic nano-scale systems. Many advanced simulation methods have been developed, but few have the ability to simulate the long time scale limit and to accurately model the microscopic effects of nano-scale systems at the same time. We develop a new Monte Carlo method for calculating the dynamics of magnetic reversal at arbitrary long time. For example, actual calculations were performed up to 1e50 Monte Carlo steps. This method is based on microscopic interactions of many constituents and the master equation for magnetic probability distribution function is solved symbolically.Comment: accepted for publication in Computer Physics and Communication

Reweighting for Nonequilibrium Markov Processes Using Sequential Importance Sampling Methods

We present a generic reweighting method for nonequilibrium Markov processes. With nonequilibrium Monte Carlo simulations at a single temperature, one calculates the time evolution of physical quantities at different temperatures, which greatly saves the computational time. Using the dynamical finite-size scaling analysis for the nonequilibrium relaxation, one can study the dynamical properties of phase transitions together with the equilibrium ones. We demonstrate the procedure for the Ising model with the Metropolis algorithm, but the present formalism is general and can be applied to a variety of systems as well as with different Monte Carlo update schemes.Comment: accepted for publication in Phys. Rev. E (Rapid Communications

Analytical Solution to Transport in Brownian Ratchets via Gambler's Ruin Model

We present an analogy between the classic Gambler's Ruin problem and the thermally-activated dynamics in periodic Brownian ratchets. By considering each periodic unit of the ratchet as a site chain, we calculated the transition probabilities and mean first passage time for transitions between energy minima of adjacent units. We consider the specific case of Brownian ratchets driven by Markov dichotomous noise. The explicit solution for the current is derived for any arbitrary temperature, and is verified numerically by Langevin simulations. The conditions for vanishing current and current reversal in the ratchet are obtained and discussed.Comment: 4 pages, 3 figure

Pseudo spin-orbit coupling of Dirac particles in graphene spintronics

We study the pseudo spin-orbital (SO) effects experienced by massive Dirac particles in graphene, which can potentially be of a larger magnitude compared to the conventional Rashba SO effects experienced by particles in a 2DEG semiconductor heterostructure. In order to generate a uniform vertical pseudo SO field, we propose an artificial atomic structure, consisting of a graphene ring and a charged nanodot at the center which produces a large radial electric field. In this structure, a large pseudo SO coupling strength can be achieved by accelerating the Dirac particles around the ring, due to the small energy gap in graphene and the large radial electric field emanating from the charged nanodot. We discuss the theoretical possibility of harnessing the pseudo SO effects in mesoscopic applications, e.g. pseudo spin relaxation and switching.Comment: 12 pages, 1 figur

Neural modeling of episodic memory: Encoding, retrieval, and forgetting

This paper presents a neural model that learns episodic traces in response to a continuous stream of sensory input and feedback received from the environment. The proposed model, based on fusion adaptive resonance theory (ART) network, extracts key events and encodes spatio-temporal relations between events by creating cognitive nodes dynamically. The model further incorporates a novel memory search procedure, which performs a continuous parallel search of stored episodic traces. Combined with a mechanism of gradual forgetting, the model is able to achieve a high level of memory performance and robustness, while controlling memory consumption over time. We present experimental studies, where the proposed episodic memory model is evaluated based on the memory consumption for encoding events and episodes as well as recall accuracy using partial and erroneous cues. Our experimental results show that: 1) the model produces highly robust performance in encoding and recalling events and episodes even with incomplete and noisy cues; 2) the model provides enhanced performance in a noisy environment due to the process of forgetting; and 3) compared with prior models of spatio-temporal memory, our model shows a higher tolerance toward noise and errors in the retrieval cues

Re-examining Students’ Perception of E-Learning: An Australian Perspective

Purpose – Australian tertiary institutions are increasingly incorporating technologies, such as social media and Web 2.0 tools into teaching in response to changing student needs. The purpose of this paper is to revisit a fundamental question, frequently asked in marketing, “what do our ‘customers’ [students] think now?” This will help determine the effectiveness of application of these technologies in courses and teaching programs in a changing competitive educational environment. Design/methodology/approach – Using a mixed method approach, data were collected through 31 qualitative interviews and a survey of 231 university marketing students. Quantitative techniques included summary statistics, factor analysis and t-test. Findings – Results indicate while students’ perceived flexibility and better learning outcomes as positive aspects of e-learning, they have concerns about flexibility for self-paced learning, self-motivational issues, lack of human interaction and fostering teamwork. Research limitations/implications – The study is limited to one Australian university operating in domestic and international markets. However, the study needs to be replicated for better generalizability across the sector. Practical implications – The findings question the effectiveness of e-learning as an alternative approach to face-to-face learning pedagogy. However, regular review of current e-learning tools is needed to help match student and tertiary institution expectations. Originality/value – This study re-investigates students’ perception in relation to the benefits that e-learning is expected to yield. It is one of the few studies questioning whether these promised benefits are valued by the tertiary student fraternity

Mapping Monte Carlo to Langevin dynamics: A Fokker-Planck approach

We propose a general method of using the Fokker-Planck equation (FPE) to link the Monte-Carlo (MC) and the Langevin micromagnetic schemes. We derive the drift and disusion FPE terms corresponding to the MC method and show that it is analytically equivalent to the stochastic Landau-Lifshitz-Gilbert (LLG) equation of Langevin-based micromagnetics. Subsequent results such as the time quantification factor for the Metropolis MC method can be rigorously derived from this mapping equivalence. The validity of the mapping is shown by the close numerical convergence between the MC method and the LLG equation for the case of a single magnetic particle as well as interacting arrays of particles. We also found that our Metropolis MC is accurate for a large range of damping factors $\alpha$, unlike previous time-quantified MC methods which break down at low $\alpha$, where precessional motion dominates.Comment: 4 pages, 4 figures. Accepted for publication in Phys. Rev. Let

Consistency and Concern on IS Journal Rankings

This study investigates the relationship between the journal rankings reported in five previous studies and the journal rankings based on citationbased indices for journal quality. The comparison results suggest that journal rankings derived based on citation analysis and from IS researchers’ perceptions of journal quality are only moderately consistent. Additionally, this consistency for IS research journals is significantly higher than that for allied discipline research journals. Thus, ranking both IS research journals and allied discipline research journals together as one long journal list may lead to incorrect evaluation of quality of allied discipline research journals and of the IS articles published within