A fuzzy multistage evolutionary (FUME) clustering technique

n this paper, a multistage evolutionary scheme is proposed for clustering in a large data base, like speech data. This is achieved by clustering a small subset of the entire sample set in each stage and treating the cluster centroids so obtained as samples, together with another subset of samples not considered previously, as input data to the next stage. This is continued till the whole sample set is exhausted. The clustering is accomplished by constructing a fuzzy similarity matrix and using the fuzzy techniques proposed here. The technique is illustrated by an efficient scheme for voiced-unvoiced-silence classification of speech.

A Fuzzy Approximation Scheme for Sequential Learning in Pattern Recognition

An adaptive learning scheme, based on a fuzzy approximation to the gradient descent method for training a pattern classifier using unlabeled samples, is described. The objective function defined for the fuzzy ISODATA clustering procedure is used as the loss function for computing the gradient. Learning is based on simultaneous fuzzy decisionmaking and estimation. It uses conditional fuzzy measures on unlabeled samples. An exponential membership function is assumed for each class, and the parameters constituting these membership functions are estimated, using the gradient, in a recursive fashion. The induced possibility of occurrence of each class is useful for estimation and is computed using 1) the membership of the new sample in that class and 2) the previously computed average possibility of occurrence of the same class. An inductive entropy measure is defined in terms of induced possibility distribution to measure the extent of learning. The method is illustrated with relevant examples.

Standard yet unusual mechanisms of long-distance dispersal: Seed dispersal of Corymbia torelliana by bees

Mellitochory, seed dispersal by bees, has been implicated in long-distance dispersal of the tropical rain forest tree, Corymbia torelliana (Myrtaceae). We examined natural and introduced populations of C. torelliana for 4 years to determine the species of bees that disperse seeds, and the extent and distance of seed dispersal. The mechanism of seed dispersal by bees was also investigated, including fruit traits that promote dispersal, foraging behaviour of bees at fruits, and the fate of seeds. The fruit structure of C. torelliana, with seed presented in a resin reward, is a unique trait that promotes seed dispersal by bees and often results in long-distance dispersal. We discovered that a guild of four species of stingless bees, Trigona carbonaria, T. clypearis, T. sapiens, and T. hockingsi, dispersed seeds of C. torelliana in its natural range. More than half of the nests found within 250 m of fruiting trees had evidence of seed transport. Seeds were transported minimum distances of 20-220 m by bees. Approximately 88% of seeds were dispersed by gravity but almost all fruits retained one or two seeds embedded in resin for bee dispersal. Bee foraging for resin peaked immediately after fruit opening and corresponded to a peak of seed dispersal at the hive. There were strong correlations between numbers of seeds brought in and taken out of each hive by bees (r = 0.753-0.992, P < 0.05), and germination rates were 95 ± 5%. These results showed that bee-transported seeds were effectively dispersed outside of the hive soon after release from fruits. Seed dispersal by bees is a non-standard dispersal mechanism for C. torelliana, as most seeds are dispersed by gravity before bees can enter fruits. However, many C. torelliana seeds are dispersed by bees, since seeds are retained in almost all fruits, and all of these are dispersed by bees.

A comparison of mark-recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos

Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

A fuzzy dynamic flood routing model for natural channels

A fuzzy dynamic flood routing model (FDFRM) for natural channels is presented, wherein the flood wave can be approximated to a monoclinal wave. This study is based on modification of an earlier published work by the same authors, where the nature of the wave was of gravity type. Momentum equation of the dynamic wave model is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. Hence, the FDFRM gets rid of the assumptions associated with the momentum equation. Also, it overcomes the necessity of calculating friction slope (S-f) in flood routing and hence the associated uncertainties are eliminated. The fuzzy rule based model is developed on an equation for wave velocity, which is obtained in terms of discontinuities in the gradient of flow parameters. The channel reach is divided into a number of approximately uniform sub-reaches. Training set required for development of the fuzzy rule based model for each sub-reach is obtained from discharge-area relationship at its mean section. For highly heterogeneous sub-reaches, optimized fuzzy rule based models are obtained by means of a neuro-fuzzy algorithm. For demonstration, the FDFRM is applied to flood routing problems in a fictitious channel with single uniform reach, in a fictitious channel with two uniform sub-reaches and also in a natural channel with a number of approximately uniform sub-reaches. It is observed that in cases of the fictitious channels, the FDFRM outputs match well with those of an implicit numerical model (INM), which solves the dynamic wave equations using an implicit numerical scheme. For the natural channel, the FDFRM Outputs are comparable to those of the HEC-RAS model.

Structural Damage Detection Using Modal Curvature and Fuzzy Logic

A fuzzy logic system (FLS) with a new sliding window defuzzifier is proposed for structural damage detection using modal curvatures. Changes in the modal curvatures due to damage are fuzzified using Gaussian fuzzy sets and mapped to damage location and size using the FLS. The first four modal vectors obtained from finite element simulations of a cantilever beam are used for identifying the location and size of damage. Parametric studies show that modal curvatures can be used to accurately locate the damage; however, quantifying the size of damage is difficult. Tests with noisy simulated data show that the method detects damage very accurately at different noise levels and when some modal data are missing.

Estimation of fuzzy memberships from histograms

Based on the conclusions drawn in the bijective transformation between possibility and probability, a method is proposed to estimate the fuzzy membership function for pattern recognition purposes. A rational function approximation to the probability density function is obtained from the histogram of a finite (and sometimes very small) number of samples. This function is normalized such that the highest ordinate is one. The parameters representing the rational function are used for classifying the pattern samples based on a max-min decision rule. The method is illustrated with examples.

The physiological and behavioral responses of steers to gaseous ammonia in simulated long distance transport by ship.

Ammonia (NH3) can accumulate in high density cattle accommodation during live export shipments and could potentially threaten the animals' health and welfare. The effects of 4 NH3 concentrations, control (<8), 15, 30, and 45 ppm, on the physiology and behavior of steers were recorded. The animals were held for 12 d under a micro-climate and stocking density similar to shipboard conditions experienced on voyages from Australia to the Middle East during the northern hemispheric summer. In bronchoalveolar lavage samples, ammonia increased (P < 0.05) macrophage activity in proportion to NH3 concentration and it increased (P < 0.05) neutrophil percentage at 30 and 45 ppm, indicating active pulmonary inflammation. It also increased (P < 0.05) lacrimation, nasal secretions and coughing, particularly at 45 ppm, indicating that the NH3 was irritating the mucous membranes of the eyes, nasal cavity and respiratory tract. Ammonia had no effect (P > 0.05) on hematological parameters or body weight. Twenty-eight days after exposure to NH3, the steers' pulmonary macrophage activity and neutrophil levels had returned to normal. It was concluded that ammonia concentrations of 30 and 45 ppm induced temporary inflammatory responses which indicate an adverse effect on the welfare of steers.

Distance Relay Co-ordination Using Support Vector Machines in Power Transmission System

In this paper, a new approach to enhance the transmission system distance relay co-ordination is presented. The approach depends on the apparent impedance loci seen by the distance relay during all possible disturbances. In a distance relay, the impedance loci seen at the relay location is obtained by extensive transient stability studies. Support vector machines (SVMs), a class of patterns classifiers are used in discriminating zone settings (zone-1, zone-2 and zone-3) using the signals to be used by the relay. Studies on a sample 9-bus are presented for illustrating the proposed scheme.

Information sharing in distance collaboration: A software engineering perspective

Information sharing in distance collaboration: A software engineering perspective, QueenslandFactors in software engineering workgroups such as geographical dispersion and background discipline can be conceptually characterized as "distances", and they are obstructive to team collaboration and information sharing. This thesis focuses on information sharing across multidimensional distances and develops an information sharing distance model, with six core dimensions: geography, time zone, organization, multi-discipline, heterogeneous roles, and varying project tenure. The research suggests that the effectiveness of workgroups may be improved through mindful conducts of information sharing, especially proactive consideration of, and explicit adjustment for, the distances of the recipient when sharing information.

Damage assessment of structures with uncertainty by using mode-shape curvatures and fuzzy logic

Uncertainties associated with the structural model and measured vibration data may lead to unreliable damage detection. In this paper, we show that geometric and measurement uncertainty cause considerable problem in damage assessment which can be alleviated by using a fuzzy logic-based approach for damage detection. Curvature damage factor (CDF) of a tapered cantilever beam are used as damage indicators. Monte Carlo simulation (MCS) is used to study the changes in the damage indicator due to uncertainty in the geometric properties of the beam. Variation in these CDF measures due to randomness in structural parameter, further contaminated with measurement noise, are used for developing and testing a fuzzy logic system (FLS). Results show that the method correctly identifies both single and multiple damages in the structure. For example, the FLS detects damage with an average accuracy of about 95 percent in a beam having geometric uncertainty of 1 percent COV and measurement noise of 10 percent in single damage scenario. For multiple damage case, the FLS identifies damages in the beam with an average accuracy of about 94 percent in the presence of above mentioned uncertainties. The paper brings together the disparate areas of probabilistic analysis and fuzzy logic to address uncertainty in structural damage detection.

Designing experiences with wearables : A case study exploring the blurring boundaries of art, design, technology, culture and distance

This paper details a workshop aimed at exploring opportunities for experience design through wearable art and design concepts. Specifically it explores the structure of the workshop with respect to facilitating learning through technology in the development of experiential wearable art and design. A case study titled Cloud Workshop: Wearables and Wellbeing; Enriching connections between citizens in the Asia-Pacific region was initiated through a cooperative partnership between Hong Kong Baptist University (HKBU), Queensland University of Technology (QUT) and Griffith University (GU). Digital technologies facilitated collaboration through an inter-disciplinary, inter-national and inter- cultural approach (Facer & Sandford, 2010) between Australia and Hong Kong. Students cooperated throughout a two-week period to develop innovative wearable concepts blending art, design and technology. An unpacking of the approach, pedagogical underpinning and final outcomes revealed distinct educational benefits as well as certain learning and technological challenges of the program. Qualitative feedback uncovered additional successes with respect to student engagement and enthusiasm, while uncovering shortcomings in the delivery and management of information and difficulties with cultural interactions. Potential future versions of the program aim to take advantage of the positives and overcome the limitations of the current pedagogical approach. It is hoped the case study will become a catalyst for future workshops that blur the boundaries of art, design and technology to uncover further benefits and potentials for new outcomes in experience design.

The global distribution of Banana bunchy top virus reveals little evidence for frequent recent, human-mediated long distance dispersal events

Banana bunchy top virus (BBTV; family Nanoviridae, genus Babuvirus) is a multi-component single-stranded DNA virus, which infects banana plants in many regions of the world, often resulting in large-scale crop losses. Weanalyzed 171 banana leaf samples from fourteen countries and recovered, cloned, and sequenced 855 complete BBTV components including ninety-four full genomes. Importantly, full genomes were determined from eight countries, where previously no full genomes were available (Samoa, Burundi, Republic of Congo, Democratic Republic of Congo, Egypt, Indonesia, the Philippines, and the USA [HI]). Accounting for recombination and genome component reassortment, we examined the geographic structuring of global BBTV populations to reveal that BBTV likely originated in Southeast Asia, that the current global hotspots of BBTV diversity are Southeast Asia/Far East and India, and that BBTV populations circulating elsewhere in the world have all potentially originated from infrequent introductions. Most importantly, we find that rather than the current global BBTV distribution being due to increases in human-mediated movements of bananas over the past few decades, it is more consistent with a pattern of infrequent introductions of the virus to different parts of the world over the past 1,000 years.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.