Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

Alcohol use in South Africa : findings from the first demographic and health survey (1998)

Objective This study formed part of the 1998 South African Demographic and Health Survey, which included questions assessing the extent of alcohol use, risky drinking and alcohol problems among South Africans to obtain up-to-date baseline estimates of consumption and risky drinking and to inform intervention efforts. Method A two-stage random sample of 13,826 persons ages 15 or older (59% women) was included in the survey. Alcohol use was assessed through eight questions, including the CAGE questionnaire. Frequency analyses for different age groups, geographic setting, education level, population group and gender were calculated, as were odds ratios for these variables in relation to symptoms of alcohol problems. Results Current alcohol consumption was reported by 45% of the men and 17% of the women. White men (71%) were most likely and Asian women (9%) least likely to be current drinkers. Urban residents were more likely than nonurban dwellers to report current drinking. One third of the current drinkers reported risky drinking over weekends, and 28% of the men and 10% of the women scored above the cutoff level on the CAGE questionnaire. Symptoms of alcohol problems were significantly associated with lower socioeconomic status, no school education in women and being older than 25 years of age. Conclusions A comprehensive strategy is required to address the high levels of risky drinking and reported symptoms of alcohol problems.

“I was proud of myself that I didn’t give up and I did it”: Experiences of pride and triumph in learning science

The role that specific emotions, such as pride and triumph, play during instruction in science education is an under-researched field of study. Emotions are recognized as central to learning yet little is known about the way in which they are produced in naturalistic settings, how emotions relate to classroom learning during interactions, and what antecedent factors are associated with emotional experiences during instruction. Data sources for the study include emotion diaries, student written artifacts, video recordings of class interactions, and interviews. Emotions produced in the moment during classroom interactions are analyzed from video data and audio data through a novel theoretical framework related to the sociology of human emotions. These direct observations are compared with students’ recollected emotional experiences reported through emotion diaries and interviews. The study establishes links between pride and triumph within classroom interactions and instructional tasks during learning episodes in a naturalistic setting. We discuss particular classroom activities that are associated with justified feelings of pride and triumph. More specifically, classroom events associated with these emotions were related to understanding science concepts, social interactions, and achieving success on challenging tasks.

Some comparison on whole-proteome phylogeny of large dsDNA viruses based on dynamical language approach and feature frequency profiles method

There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among them, CVTree method, feature frequency profiles method and dynamical language approach were used to investigate the whole-proteome phylogeny of large dsDNA viruses. Using the data set of large dsDNA viruses from Gao and Qi (BMC Evol. Biol. 2007), the phylogenetic results based on the CVTree method and the dynamical language approach were compared in Yu et al. (BMC Evol. Biol. 2010). In this paper, we first apply dynamical language approach to the data set of large dsDNA viruses from Wu et al. (Proc. Natl. Acad. Sci. USA 2009) and compare our phylogenetic results with those based on the feature frequency profiles method. Then we construct the whole-proteome phylogeny of the larger dataset combining the above two data sets. According to the report of The International Committee on the Taxonomy of Viruses (ICTV), the trees from our analyses are in good agreement to the latest classification of large dsDNA viruses.

High-resolution GNSS-tracked drifter for studying surface dispersion in shallow water

The use of GNSS tracked Lagrangian drifters allows more realistic quantification of fluid motion and dispersion coefficients than Eulerian techniques because such drifters are analogues of particles that are relevant to flow field characterisation and pollutant dispersion. Using the fast growing Real Time Kinematic (RTK) positioning technique derived from Global Satellite Navigation Systems (GNSS), drifters are developed for high frequency (10 Hz) sampling with position estimates to centimetre accuracy. The drifters are designed with small size and less direct wind drag to follow the sub-surface flow which characterizes dispersion in shallow waters. An analysis of position error from stationary observation indicates that the drifter can efficiently resolve motion up to 1 Hz. The result of the field deployments of the drifter in conjunction with acoustic Eulerian devices shows higher estimate of the drifter streamwise velocities. Single particle statistical analysis of field deployments in a shallow estuarine zone yielded dispersion coefficients estimate comparable to those of dye tracer studies. The drifters capture the tidal elevation during field studies in a tidal estuary.

The entrepreneurial break-up : disengaging from the start-up phase

Research on firm exit has grown considerably in volume and sophistication in recent years, leading to new insights and strengthened research-based evidence. However, no framework explicitly explains nascent disengagement, i.e., termination of start-up efforts before the firm has reached an operational stage. Further, prior research has had limited success at explaining nascent entrepreneurial behaviour using theories based on logics of resource availability and economic rationality. In response, this chapter approaches nascent stage disengagement unconventionally by proposing to analogously apply Sternberg’s (1986) Triangular Theory of Love, arguing that founders are less likely to give up the start-up effort if they create strong, almost loving relations to their businesses. Nascent entrepreneurs who terminate the start-up process are proposed to lack one or more of the components – intimacy, passion, and commitment – which are essential according to Sternberg’s theory.

ACE research vignette 038 : Cracking the start-up code : does it matter when you do what?

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. This vignette deals with the process of new venture creation, and specifically the sequence in which different ‘start-up activities’ are undertaken.

Wide-band spectral power fluctuations characterize the response of simulated cortical networks to increasing stimulus intensity

The hippocampus is an anatomically distinct region of the medial temporal lobe that plays a critical role in the formation of declarative memories. Here we show that a computer simulation of simple compartmental cells organized with basic hippocampal connectivity is capable of producing stimulus intensity sensitive wide-band fluctuations of spectral power similar to that seen in real EEG. While previous computational models have been designed to assess the viability of the putative mechanisms of memory storage and retrieval, they have generally been too abstract to allow comparison with empirical data. Furthermore, while the anatomical connectivity and organization of the hippocampus is well defined, many questions regarding the mechanisms that mediate large-scale synaptic integration remain unanswered. For this reason we focus less on the specifics of changing synaptic weights and more on the population dynamics. Spectral power in four distinct frequency bands were derived from simulated field potentials of the computational model and found to depend on the intensity of a random input. The majority of power occurred in the lowest frequency band (3-6 Hz) and was greatest to the lowest intensity stimulus condition (1% maximal stimulus). In contrast, higher frequency bands ranging from 7-45 Hz show an increase in power directly related with an increase in stimulus intensity. This trend continues up to a stimulus level of 15% to 20% of the maximal input, above which power falls dramatically. These results suggest that the relative power of intrinsic network oscillations are dependent upon the level of activation and that above threshold levels all frequencies are damped, perhaps due to over activation of inhibitory interneurons.

The influence of flight speed on the ranging performance of bats using frequency modulated echolocation pulses

Many species of bat use ultrasonic frequency modulated (FM) pulses to measure the distance to objects by timing the emission and reception of each pulse. Echolocation is mainly used in flight. Since the flight speed of bats often exceeds 1% of the speed of sound,Doppler effects will lead to compression of the time between emission and reception as well as an elevation of the echo frequencies, resulting in a distortion of the perceived range. This paper describes the consequences of these Doppler effects on the ranging performance of bats using different pulse designs. The consequences of Doppler effects on ranging performance described in this paper assume bats to have a very accurate ranging resolution, which is feasible with a filterbank receiver. By modeling two receiver types, it was first established that the effects of Doppler compression are virtually independent of the receiver type. Then, used a cross-correlation model was used to investigate the effect of flight speed on Doppler tolerance and range–Doppler coupling separately. This paper further shows how pulse duration, bandwidth, function type, and harmonics influence Doppler tolerance and range–Doppler coupling. The influence of each signal parameter is illustrated using calls of several bat species. It is argued that range–Doppler coupling is a significant source of error in bat echolocation, and various strategies bats could employ to deal with this problem, including the use of range rate information are discussed.

Shape up or ship out : can we enhance productivity in coastal aquaculture to compete with other uses?

Coastal resources are coming under increasing pressure from competition between recreational, commercial and conservation uses. This is particularly so in coastal areas adjacent to major population centres. Given high recreational and conservation values in such areas, economic activities need to be highly efficient in order to persist. Management of these industries must therefore also encourage efficient production and full utilisation of the areas available. In order to achieve this, managers must first understand the level and drivers of productivity, and how these can be influenced. In this study, by way of illustration, the focus was on the Sydney rock oyster industry within Queensland's Moreton Bay, a multiple use marine park with high recreational and conservation value adjacent to Australia's third largest city. Productivity of the oyster industry in Moreton Bay is currently low compared to historic levels, and management has an objective of reversing this trend. It is unclear whether this difference is due to oyster farmers' business choices and personal characteristics or whether varying environmental conditions in the Moreton Bay limit the capacity of the oyster industry. These require different management responses in order to enhance productivity. The study examined different productivity measures of the oyster industry using data envelopment analysis (DEA) to determine where productivity gains can be made and by how much. The findings suggest that the industry is operating at a high level of capacity utilisation, but a low level of efficiency. The results also suggest that both demographic and environmental conditions affect technical efficiency in the Bay, with water characteristics improvements and appropriate training potentially providing the greatest benefits to the industry. Methods used in this study are transferable to other industries and provide a means by which coastal aquaculture may be managed to ensure it remains competitive with other uses of coastal resources.

Doubly Fed Induction Generators : Overview and Intelligent Control Strategies for Wind Energy Conversion Systems

Adjustable speed induction generators, especially the Doubly-Fed Induction Generators (DFIG) are becoming increasingly popular due to its various advantages over fixed speed generator systems. A DFIG in a wind turbine has ability to generate maximum power with varying rotational speed, ability to control active and reactive by integration of electronic power converters such as the back-to-back converter, low rotor power rating resulting in low cost converter components, etc, DFIG have become very popular in large wind power conversion systems. This chapter presents an extensive literature survey over the past 25 years on the different aspects of DFIG. Application of H8 Controller for enhanced DFIG-WT performance in terms of robust stability and reference tracking to reduce mechanical stress and vibrations is also demonstrated in the chapter.

Application of TS-Fuzzy Controller for Active Power and DC Capacitor Voltage Control in DFIG-Based Wind Energy Conversion Systems

This chapter focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the Doubly Fed Induction Generator (DFIG) based wind generator. The conventional PI control loops for mantaining desired active power and DC capacitor voltage is compared with the TS fuzzy controllers. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings is also investigated. The results from the time domain simulations are presented to elucidate the effectiveness of the TS-fuzzy controller over the conventional PI controller in the DFIG system. The proposed TS-fuzzy con-troller can improve the fault ride through capability of DFIG compared to the conventional PI controller.