Fuzzy logic optimized wireless sensor network routing protocol

Wireless sensor networks (WSNs) are used in health monitoring, tracking and security applications. Such networks transfer data from specific areas to a nominated destination. In the network, each sensor node acts as a routing element for other sensor nodes during the transmission of data. This can increase energy consumption of the sensor node. In this paper, we propose a routing protocol for improving network lifetime and performance. The proposed protocol uses type-2 fuzzy logic to minimize the effects of uncertainty produced by the environmental noise. Simulation results show that the proposed protocol performs better than a recently developed routing protocol in terms of extending network lifetime and saving energy and also reducing data packet lost.

A new neural network-based type reduction algorithm for interval type-2 fuzzy logic systems

This paper introduces a new type reduction (TR) algorithm for interval type-2 fuzzy logic systems (IT2 FLSs). Flexibility and adaptiveness are the key features of the proposed non-parametric algorithm. Lower and upper firing strengths of rules as well as their consequent coefficients are fed into a neural network (NN). NN output is a crisp value that corresponds to the defuzzified output of IT2 FLSs. The NN type reducer is trained through minimization of an error-based cost function with the purpose of improving modelling and forecasting performance of IT2 FLS models. Simulation results indicate that application of the proposed TR algorithm greatly enhances modelling and forecasting performance of IT2 FLS models. This benefit is achieved in no cost, as the computational requirement of the proposed algorithm is less than or at most equivalent to traditional TR algorithms.

Review short: Rachael Briggs’s Free Logic

 Review of Rachael Briggs' poetry collection, Free Logic, UQP, 2013.

Control of polystyrene batch reactor using fuzzy logic controller

Control of polymerization reactors is a challenging issue for researchers due to the complex reaction mechanisms. A lot of reactions occur simultaneously during polymerization. This leads to a polymerization system that is highly nonlinear in nature. In this work, a nonlinear advanced controller, named fuzzy logic controller (FLC), is developed for monitoring the batch free radical polymerization of polystyrene (PS) reactor. Temperature is used as an intermediate control variable to control polymer quality, because the products quality and quantity of polymer are directly depends on temperature. Different FLCs are developed through changing the number of fuzzy membership functions (MFs) for inputs and output. The final tuned FLC results are compared with the results of another advanced controller, named neural network based model predictive controller (NN-MPC). The simulation results reveal that the FLC performance is better than NN-MPC in terms of quantitative and qualitative performance criterion.

Deleuze's neo-leibnizianism, events and the logic of sense's 'static ontological genesis'

In The Logic of Sense, Deleuze effectively argues that two types of relation between events govern their ‘evental’ or ‘ideal play’, and ultimately underlie determined substances, that is, worldly individuals and persons. Leibniz calls these relations ‘compossibility’ and ‘incompossibility’. Deleuze calls them ‘convergence’ and ‘divergence’. This paper explores how Deleuze appropriates and extends a number of Leibnizian concepts in order to ground the idea that events have ontological priority over substances ‘all the way down’.

Classification of healthcare data using genetic fuzzy logic system and wavelets

Healthcare plays an important role in promoting the general health and well-being of people around the world. The difficulty in healthcare data classification arises from the uncertainty and the high-dimensional nature of the medical data collected. This paper proposes an integration of fuzzy standard additive model (SAM) with genetic algorithm (GA), called GSAM, to deal with uncertainty and computational challenges. GSAM learning process comprises three continual steps: rule initialization by unsupervised learning using the adaptive vector quantization clustering, evolutionary rule optimization by GA and parameter tuning by the gradient descent supervised learning. Wavelet transformation is employed to extract discriminative features for high-dimensional datasets. GSAM becomes highly capable when deployed with small number of wavelet features as its computational burden is remarkably reduced. The proposed method is evaluated using two frequently-used medical datasets: the Wisconsin breast cancer and Cleveland heart disease from the UCI Repository for machine learning. Experiments are organized with a five-fold cross validation and performance of classification techniques are measured by a number of important metrics: accuracy, F-measure, mutual information and area under the receiver operating characteristic curve. Results demonstrate the superiority of the GSAM compared to other machine learning methods including probabilistic neural network, support vector machine, fuzzy ARTMAP, and adaptive neuro-fuzzy inference system. The proposed approach is thus helpful as a decision support system for medical practitioners in the healthcare practice.

River flows and profit flows: the powerful logic driving local news

The importance of local news is gaining traction with industry and in journalism scholarship. But there is a need for careful analysis of what it means to be “local” and how we might theorise the role and place of news organisations and journalists who serve local audiences. This paper draws on three qualitative case studies of local newspapers serving small towns and cities in Australia to generate concepts that can be used to deepen understanding about this form of news. Our research highlights that to be local is practical and embodied. It requires individuals, groups, organisations or institution to be anchored in a particular locale and have in-depth understanding of that place that has developed over time. We extend the scholarship of Pierre Bourdieu to suggest this may be understood as local habitus—a powerful set of dispositions and practical logic developed within a place—that the small newspaper is inherently tied to. Reading a newspaper is part of one's local habitus while an individual who possesses it in the journalistic field may have a significant advantage in their day-to-day practices. We suggest this theoretical lens can offer rich insights into the future of local news production across the western world.