Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Pancreatic islet basement membrane loss and remodeling after mouse islet isolation and transplantation: Impact for allograft rejection

The isolation of islets by collagenase digestion can cause damage and impact the efficiency of islet engraftment and function. In this study, we assessed the basement membranes (BMs) of mouse pancreatic islets as a molecular biomarker for islet integrity, damage after isolation, and islet repair in vitro as well as in the absence or presence of an immune response after transplantation. Immunofluorescence staining of BM matrix proteins and the endothelial cell marker platelet endothelial cell adhesion molecule-1 (PECAM-1) was performed on pancreatic islets in situ, isolated islets, islets cultured for 4 days, and islet grafts at 3-10 days posttransplantation. Flow cytometry was used to investigate the expression of BM matrix proteins in isolated islet β-cells. The islet BM, consisting of collagen type IV and components of Engelbreth-Holm-Swarm (EHS) tumor laminin 111, laminin α2, nidogen-2, and perlecan in pancreatic islets in situ, was completely lost during islet isolation. It was not reestablished during culture for 4 days. Peri- and intraislet BM restoration was identified after islet isotransplantation and coincided with the migration pattern of PECAM-1(+) vascular endothelial cells (VECs). After islet allotransplantation, the restoration of VEC-derived peri-islet BMs was initiated but did not lead to the formation of the intraislet vasculature. Instead, an abnormally enlarged peri-islet vasculature developed, coinciding with islet allograft rejection. The islet BM is a sensitive biomarker of islet damage resulting from enzymatic isolation and of islet repair after transplantation. After transplantation, remodeling of both peri- and intraislet BMs restores β-cell-matrix attachment, a recognized requirement for β-cell survival, for isografts but not for allografts. Preventing isolation-induced islet BM damage would be expected to preserve the intrinsic barrier function of islet BMs, thereby influencing both the effector mechanisms required for allograft rejection and the antirejection strategies needed for allograft survival.

Increasing autonomy transparency through capability communication in multiple heterogeneous UAV management

Interest in the area of collaborative Unmanned Aerial Vehicles (UAVs) in a Multi-Agent System is growing to compliment the strengths and weaknesses of the human-machine relationship. To achieve effective management of multiple heterogeneous UAVs, the status model of the agents must be communicated to each other. This paper presents the effects on operator Cognitive Workload (CW), Situation Awareness (SA), trust and performance by increasing the autonomy capability transparency through text-based communication of the UAVs to the human agents. The results revealed a reduction in CW, increase in SA, increase in the Competence, Predictability and Reliability dimensions of trust, and the operator performance.

Editorial of "Communication Research and Practice, 1(3)"

For the third issue of Communication Research and Practice, we bring together a mix of submitted content and papers presented at events that were hosted under the auspices of the International Communication Association. Dal Yong Jin captures the dynamic and contradictory elements of both convergence and transmedia storytelling, and the ‘Korean Wave’, in his paper on webtoons. Exploring this distinctive online form of transmedia storytelling, Jin considers its evolution from the perspectives of digital content, political economy, convergent media and digital labour, and the tensions that surround its potential expansion into global cultural markets.

A new load distribution strategy for linear network with communication delays

In this paper, we propose a new load distribution strategy called `send-and-receive' for scheduling divisible loads, in a linear network of processors with communication delay. This strategy is designed to optimally utilize the network resources and thereby minimizes the processing time of entire processing load. A closed-form expression for optimal size of load fractions and processing time are derived when the processing load originates at processor located in boundary and interior of the network. A condition on processor and link speed is also derived to ensure that the processors are continuously engaged in load distributions. This paper also presents a parallel implementation of `digital watermarking problem' on a personal computer-based Pentium Linear Network (PLN) topology. Experiments are carried out to study the performance of the proposed strategy and results are compared with other strategies found in literature.

An Efficient Load Distribution Strategy for a Distributed Linear Network of Processors with Communication Delays

In this paper, we present an improved load distribution strategy, for arbitrarily divisible processing loads, to minimize the processing time in a distributed linear network of communicating processors by an efficient utilization of their front-ends. Closed-form solutions are derived, with the processing load originating at the boundary and at the interior of the network, under some important conditions on the arrangement of processors and links in the network. Asymptotic analysis is carried out to explore the ultimate performance limits of such networks. Two important theorems are stated regarding the optimal load sequence and the optimal load origination point. Comparative study of this new strategy with an earlier strategy is also presented.

Leveraging coherent distributed space-time codes for noncoherent communication in relay networks via training

For point to point multiple input multiple output systems, Dayal-Brehler-Varanasi have proved that training codes achieve the same diversity order as that of the underlying coherent space time block code (STBC) if a simple minimum mean squared error estimate of the channel formed using the training part is employed for coherent detection of the underlying STBC. In this letter, a similar strategy involving a combination of training, channel estimation and detection in conjunction with existing coherent distributed STBCs is proposed for noncoherent communication in Amplify-and-Forward (AF) relay networks. Simulation results show that the proposed simple strategy outperforms distributed differential space-time coding for AF relay networks. Finally, the proposed strategy is extended to asynchronous relay networks using orthogonal frequency division multiplexing.

Implementation of Art1 and Art2 Artificial Neural Networks on Ring and Mesh Architectures

The Artificial Neural Networks (ANNs) are being used to solve a variety of problems in pattern recognition, robotic control, VLSI CAD and other areas. In most of these applications, a speedy response from the ANNs is imperative. However, ANNs comprise a large number of artificial neurons, and a massive interconnection network among them. Hence, implementation of these ANNs involves execution of computer-intensive operations. The usage of multiprocessor systems therefore becomes necessary. In this article, we have presented the implementation of ART1 and ART2 ANNs on ring and mesh architectures. The overall system design and implementation aspects are presented. The performance of the algorithm on ring, 2-dimensional mesh and n-dimensional mesh topologies is presented. The parallel algorithm presented for implementation of ART1 is not specific to any particular architecture. The parallel algorithm for ARTE is more suitable for a ring architecture.

Xylan-Degrading Enzymes from the Thermophilic Fungus Humicola Zanuginosa (Griffon and Maublanc) Bunce: Action Pattern of Xylanase and beta-Glucosidase on Xylans, Xylooligomers and Arabinoxylooligomers

The mode of action of xylanase and beta-glucosidase purified from the culture filtrate of Humicola lanuginosa (Griffon and Maublanc) Bunce on the xylan extracted from sugarcane bagasse and on two commercially available larchwood and oat spelt xylans, on xylooligomers and on arabinoxylooligomers was studied. While larchwood and oat spelt xylans were hydrolyzed to the same extent in 24 h, sugarcane bagasse xylan was hydrolyzed to a lesser extent in the same period. It was found that the rate of hydrolysis of xylooligomers by xylanase increased with increase in chain length, while beta-glucosidase acted rather slowly on all the oligomers tested. Xylanase exhibited predominant ''endo'' action on xylooligomers attacking the xylan chain at random while beta-glucosidase had ''exo'' action, releasing one xylose residue at a time. On arabinoxylooligomers, however, xylanase exhibited ''exo'' action. Thus, it appears that the presence of the arabinose substituent has, in some way, rendered the terminal xylose-xylose linkage more susceptible to xylanase action. It was also observed that even after extensive hydrolysis with both the enzymes, substantial amounts of the parent arabinoxylooligomer remained unhydrolyzed together with the accumulation of arabinoxylobiose. It can therefore be concluded that the presence of the arabinose substituent in the xylan chain results in linkages that offer resistance to both xylanase and beta-glucosidase action.

Flow pattern analysis in a highly stenotic patient-specific carotid bifurcation model using a turbulence model

The aim of this study is to investigate the blood flow pattern in carotid bifurcation with a high degree of luminal stenosis, combining in vivo magnetic resonance imaging (MRI) and computational fluid dynamics (CFD). A newly developed two-equation transitional model was employed to evaluate wall shear stress (WSS) distribution and pressure drop across the stenosis, which are closely related to plaque vulnerability. A patient with an 80% left carotid stenosis was imaged using high resolution MRI, from which a patient-specific geometry was reconstructed and flow boundary conditions were acquired for CFD simulation. A transitional model was implemented to investigate the flow velocity and WSS distribution in the patient-specific model. The peak time-averaged WSS value of approximately 73Pa was predicted by the transitional flow model, and the regions of high WSS occurred at the throat of the stenosis. High oscillatory shear index values up to 0.50 were present in a helical flow pattern from the outer wall of the internal carotid artery immediately after the throat. This study shows the potential suitability of a transitional turbulent flow model in capturing the flow phenomena in severely stenosed carotid arteries using patient-specific MRI data and provides the basis for further investigation of the links between haemodynamic variables and plaque vulnerability. It may be useful in the future for risk assessment of patients with carotid disease.

Intercellular Communication in the Multicellular Stage of Dictyostelium-Discoideum

The aim of the present study was to draw inferences regarding the properties of single cells responsible for co-operative behaviour in the slug of the soil amoeba Dictyostelium discoideum. The slug is an integrated multicellular mass formed by the aggregation of starved cells. The amoebae comprising the slug differentiate according to their spatial locations relative to one another, implying that, as in the case of other regulative embryos, they must be in mutual communication. We have previously shown that one manifestation of this communication is the time taken for the anteriormost fragment of the slug, the tip, to regenerate from slugs which have been rendered tipless by amputation. We present results of tip-regeneration experiments performed on genetically mosaic slugs. By comparing the mosaics with their component pure genotypes, we were able to discriminate between a set of otherwise equally plausible modes of intercellular signalling. Neither a'pacemaker' model, in which the overall rate of tip regeneration is determined by the cell with the highest frequency of autonomous oscillation, nor an 'independent-particle' model, in which the rate of regeneration is the arithmetical average of independent cell-dependent rates, is in quantitative accord with our findings. Our results are best explained by a form of signalling which operates by means of cell-to-cell relay. Therefore intercellular communication Seems to be essential for tip regeneration.

Maintaining student engagement in a multidisciplinary allied health communication skills course

Effective communication is an important graduate capability for allied health students but there are few opportunities for students to engage with these skills in a dedicated manner at an undergraduate level. This paper reported on the use of active learning and relevance-building strategies to maintain student engagement in a multidisciplinary allied health communication skills course at an Australian university. Students (N = 736) completed an engagement survey during the first and final lecture. While most degree programs reported no difference in engagement across semester, nursing/paramedic students reported a significant decrease in student engagement. A perceived lack of disciplinary relevance may account for student disengagement in this group, illustrating the challenge of delivering an authentic learning experience whilst engaging students from diverse degree programs.

A Pattern Recognition Model of Voice-Based Personal Verification Systems for Forensic Applications

Abstract-The success of automatic speaker recognition in laboratory environments suggests applications in forensic science for establishing the Identity of individuals on the basis of features extracted from speech. A theoretical model for such a verification scheme for continuous normaliy distributed featureIss developed. The three cases of using a) single feature, b)multipliendependent measurements of a single feature, and c)multpleindependent features are explored.The number iofndependent features needed for areliable personal identification is computed based on the theoretcal model and an expklatory study of some speech featues.

Spoilage pattern of five species of Australian prawns: Deterioration is influenced by environment of capture and mode of storage

Five species of commercial prawns Penaeus plebejus, P. merguiensis, P. semisulcatus/P. esculentus and M. bennettae, were obtained from South-East and North Queensland, chilled soon after capture and then stored either whole or deheaded on ice and ice slurry, until spoilage. Total bacterial counts, total volatile nitrogen, K-values and total demerit scores were assessed at regular intervals. Their shelf lives ranged from 10-17 days on ice and >20 days on ice slurry. Initial bacterial flora on prawns from shallower waters (4-15m) were dominated by Gram-positives and had lag periods around 7 days, whereas prawns from deeper waters (100m) were dominant in Pseudomonas spp. with no lag periods in bacterial growth. The dominant spoiler in ice was mainly Pseudomonas fragi whereas the main spoiler in ice slurry was Shewanella putrefaciens. Bacterial interactions seem to play a major role in the patterns of spoilage in relation to capture environment and pattern of storage

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.