Optimisation of on-line principal component analysis

Different techniques, used to optimise on-line principal component analysis, are investigated by methods of statistical mechanics. These include local and global optimisation of node-dependent learning-rates which are shown to be very efficient in speeding up the learning process. They are investigated further for gaining insight into the learning rates' time-dependence, which is then employed for devising simple practical methods to improve training performance. Simulations demonstrate the benefit gained from using the new methods.Comment: 10 pages, 5 figure

An adaptive behavioral immune system: a model of population health behavior

The understanding that immunity could be strengthened in the general population (e.g., through vaccine interventions) supported global advances upon acute infectious disease epidemics in the eighteenth, nineteenth, and twentieth centuries. However, in the twenty-first century, global populations face chronic disease epidemics. Research demonstrates that diseases largely emerge from health risk behavior. The understanding of how health behavior, like the biological immune system, can be strengthened in the general population, could support advances in the twenty-first century. To consider how health behavior can be strengthened in the general population, the authors present a theoretical model of population health behavior. The model operationalizes health behavior as a system of functions that, like the biological immune system, exists in each member of the population. Constructs are presented that operationalize the specific decisions and habits that drive health behavior and behavior change in the general population. The constructs allow the authors to present parallels (1) among existing behavior change theories and (2) between the proposed system and the biological immune system. Through these parallels, the authors introduce a model and a logic of population-level health behavior change. The Adaptive Behavioral Immune System is an integrative model of population health behavior

A philosophy of health: life as reality, health as a universal value

Emphases on biomarkers (e.g. when making diagnoses) and pharmaceutical/drug methods (e.g. when researching/disseminating population level interventions) in primary care evidence philosophies of health (and healthcare) that reduce health to the biological level. However, with chronic diseases being responsible for the majority of all cause deaths and being strongly linked to health behavior and lifestyle; predominantly biological views are becoming increasingly insufficient when discussing this health crisis. A philosophy that integrates biological, behavioral, and social determinants of health could benefit multidisciplinary discussions of healthy publics. This manuscript introduces a Philosophy of Health by presenting its first five principles of health. The philosophy creates parallels among biological immunity, health behavior change, social change by proposing that two general functions—precision and variation—impact population health at biological, behavioral, and social levels. This higher-level of abstraction is used to conclude that integrating functions, rather than separated (biological) structures drive healthy publics. A Philosophy of Health provides a framework that can integrate existing theories, models, concepts, and constructs

Dynamics of Learning with Restricted Training Sets I: General Theory

We study the dynamics of supervised learning in layered neural networks, in the regime where the size $p$ of the training set is proportional to the number $N$ of inputs. Here the local fields are no longer described by Gaussian probability distributions and the learning dynamics is of a spin-glass nature, with the composition of the training set playing the role of quenched disorder. We show how dynamical replica theory can be used to predict the evolution of macroscopic observables, including the two relevant performance measures (training error and generalization error), incorporating the old formalism developed for complete training sets in the limit $\alpha=p/N\to\infty$ as a special case. For simplicity we restrict ourselves in this paper to single-layer networks and realizable tasks.Comment: 39 pages, LaTe

Functional Optimisation of Online Algorithms in Multilayer Neural Networks

We study the online dynamics of learning in fully connected soft committee machines in the student-teacher scenario. The locally optimal modulation function, which determines the learning algorithm, is obtained from a variational argument in such a manner as to maximise the average generalisation error decay per example. Simulations results for the resulting algorithm are presented for a few cases. The symmetric phase plateaux are found to be vastly reduced in comparison to those found when online backpropagation algorithms are used. A discussion of the implementation of these ideas as practical algorithms is given

Globally optimal parameters for on-line learning in multilayer neural networks

We present a framework for calculating globally optimal parameters, within a given time frame, for on-line learning in multilayer neural networks. We demonstrate the capability of this method by computing optimal learning rates in typical learning scenarios. A similar treatment allows one to determine the relevance of related training algorithms based on modifications to the basic gradient descent rule as well as to compare different training methods

EXTRACTIVE-SPECTROPHOTOMETRIC DETERMINATION OF SOME ANTIMUSCARINIC ANTAGONIST IN TABLET FORMULATIONS USING ERIOCHROME CYANINE R

Objective: To develop and validate simple, rapid and sensitive spectrophotometric method for the assay of four antimuscarinic antagonists, namely oxybutynin (OXB), solifenacin (SOL), tolterodine (TOL) and fesoterodine (FES) in bulk and pharmaceutical formulations.Methods: The proposed method is based on the reaction of the selected drugs with eriochrome cyanine R (ECR) in buffered aqueous solution at pH 1.0. The formed ion-pair complexes were extracted with dichloromethane and measured quantitatively with maximum absorption at 464 nm. All variables that affect on color intensity such as pH, buffer volume and concentration of ECR and extractive solvents were studied and optimized.Results: The calibration graphs were linear over the concentration range of 4–24, 4–32, 4–32 and 2–22 mg/ml for OXB, SOL, TOL and FES, respectively. The stoichiometry of the reaction was found to be 1:1 in all cases. Molar absorptivity values were found to be 2.043×104, 1.856×104, 1.798×104 and 2.856×104 l/mol/cm for OXB, SOL, TOL and FES, respectively. Excipients which used as an additive in commercial formulations did not interfere in the analysis.Conclusion: The developed method was successfully applied to determine OXB, SOL, TOL and FES in pharmaceutical preparations. The developed method can be used for quality control and routine analysis where time, cost effectiveness and high specificity of analytical technique are of great importance