Review of vibration-based damage detection and condition assessment of bridge structures using structural health monitoring

As a part of vital infrastructure and transportation networks, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs always make the infrastructure owners difficult to undertake. Structural health monitoring (SHM) is set to assess condition and foresee probable failures of designated bridge(s), so as to monitor the structural health of the bridges. The SHM systems proposed recently are incorporated with Vibration-Based Damage Detection (VBDD) techniques, Statistical Methods and Signal processing techniques and have been regarded as efficient and economical ways to solve the problem. The recent development in damage detection and condition assessment techniques based on VBDD and statistical methods are reviewed. The VBDD methods based on changes in natural frequencies, curvature/strain modes, modal strain energy (MSE) dynamic flexibility, artificial neural networks (ANN) before and after damage and other signal processing methods like Wavelet techniques and empirical mode decomposition (EMD) / Hilbert spectrum methods are discussed here.

Prediction of highway truck conveyance configuration under over-limit prohibition and conveyance equilibrium

Aiming at the shortage of prevailing prediction methods about highway truck conveyance configuration in over-limit freight research that transferring the goods attributed to over-limit portion to another fully loaded truck of the same configuration and developing the truck traffic volume synchronously, a new way to get accumulated probability function of truck power tonnage in basal year by highway truck classified by wheel and axle type load mass spectrum investigation was presented. Logit models were used to forecast overall highway freight diversion and single cargo tonnage diversion when the weight rules and strict of enforcement intensity of overload were changed in scheme year. Assumption that the probability distribution of single truck loadage should be consistent with the probability distribution of single goods freighted, the model describes the truck conveyance configuration in the future under strict over-limit prohibition. The model was used and tested in Highway Over-limit Research Project in Anhui by World Bank.

State-of-the-Art Review on Opinion Mining from Online Customers’ Feedback

Dealing with the ever-growing information overload in the Internet, Recommender Systems are widely used online to suggest potential customers item they may like or find useful. Collaborative Filtering is the most popular techniques for Recommender Systems which collects opinions from customers in the form of ratings on items, services or service providers. In addition to the customer rating about a service provider, there is also a good number of online customer feedback information available over the Internet as customer reviews, comments, newsgroups post, discussion forums or blogs which is collectively called user generated contents. This information can be used to generate the public reputation of the service providers’. To do this, data mining techniques, specially recently emerged opinion mining could be a useful tool. In this paper we present a state of the art review of Opinion Mining from online customer feedback. We critically evaluate the existing work and expose cutting edge area of interest in opinion mining. We also classify the approaches taken by different researchers into several categories and sub-categories. Each of those steps is analyzed with their strength and limitations in this paper.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Collaborative filtering recommender systems using tag information

Recommender Systems is one of the effective tools to deal with information overload issue. Similar with the explicit rating and other implicit rating behaviours such as purchase behaviour, click streams, and browsing history etc., the tagging information implies user’s important personal interests and preferences information, which can be used to recommend personalized items to users. This paper is to explore how to utilize tagging information to do personalized recommendations. Based on the distinctive three dimensional relationships among users, tags and items, a new user profiling and similarity measure method is proposed. The experiments suggest that the proposed approach is better than the traditional collaborative filtering recommender systems using only rating data.

Polydipsia : a feature of peritoneal dialysis

Background Some dialysis patients fail to comply with their fluid restriction causing problems due to volume overload. These patients sometimes blame excessive thirst. There has been little work in this area and no work documenting polydipsia among peritoneal dialysis (PD) patients. Methods We measured motivation to drink and fluid consumption in 46 haemodialysis patients (HD), 39 PD patients and 42 healthy controls (HC) using a modified palmtop computer to collect visual analogue scores at hourly intervals. Results Mean thirst scores were markedly depressed on the dialysis day (day 1) for HD (P<0.0001). The profile for day 2 was similar to that of HC. PD generated consistently higher scores than HD day 1 and HC (P = 0.01 vs. HC and P<0.0001 vs HD day 1). Reported mean daily water consumption was similar for HD and PD with both significantly less than HC (P<0.001 for both). However, measured fluid losses were similar for PD and HC whilst HD were lower (P<0.001 for both) suggesting that the PD group may have underestimated their fluid intake. Conclusion Our results indicate that HD causes a protracted period of reduced thirst but that the population's thirst perception is similar to HC on the interdialytic day despite a reduced fluid intake. In contrast, the PD group recorded high thirst scores throughout the day and were apparently less compliant with their fluid restriction. This is potentially important because the volume status of PD patients influences their survival.

Role of low affinity beta1-adrenergic receptors in normal and diseased hearts

ROLE OF LOW AFFINITY β1-ADRENERGIC RECEPTOR IN NORMAL AND DISEASED HEARTS Background: The β1-adrenergic receptor (AR) has at least two binding sites, 1HAR and 1LAR (high and low affinity site of the 1AR respectively) which cause cardiostimulation. Some β-blockers, for example (-)-pindolol and (-)-CGP 12177 can activate β1LAR at higher concentrations than those required to block β1HAR. While β1HAR can be blocked by all clinically used β-blockers, β1LAR is relatively resistant to blockade. Thus, chronic β1LAR activation may occur in the setting of β-blocker therapy, thereby mediating persistent βAR signaling. Thus, it is important to determine the potential significance of β1LAR in vivo, particularly in disease settings. Method and result: C57Bl/6 male mice were used. Chronic (4 weeks) β1LAR activation was achieved by treatment with (-)-CGP12177 via osmotic minipump. Cardiac function was assessed by echocardiography and catheterization. (-)-CGP12177 treatment in healthy mice increased heart rate and left ventricular (LV) contractility without detectable LV remodelling or hypertrophy. In mice subjected to an 8-week period of aorta banding, (-)-CGP12177 treatment given during 4-8 weeks led to a positive inotropic effect. (-)-CGP12177 treatment exacerbated LV remodelling indicated by a worsening of LV hypertrophy by ??% (estimated by weight, wall thickness, cardiomyocyte size) and interstitial/perivascular fibrosis (by histology). Importantly, (-)-CGP12177 treatment to aorta banded mice exacerbated cardiac expression of hypertrophic, fibrogenic and inflammatory genes (all p<0.05 vs. non-treated control with aorta banding).. Conclusion: β1LAR activation provides functional support to the heart, in both normal and diseased (pressure overload) settings. Sustained β1LAR activation in the diseased heart exacerbates LV remodelling and therefore may promote disease progression from compensatory hypertrophy to heart failure. Word count: 270

Structural health monitoring : vibration-based damage detection and condition assessment of bridges

Structural health is a vital aspect of infrastructure sustainability. As a part of a vital infrastructure and transportation network, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs are a difficult burden for infrastructure owners. The structural health monitoring (SHM) systems proposed recently are incorporated with vibration-based damage detection techniques, statistical methods and signal processing techniques and have been regarded as efficient and economical ways to assess bridge condition and foresee probable costly failures. In this chapter, the recent developments in damage detection and condition assessment techniques based on vibration-based damage detection and statistical methods are reviewed. The vibration-based damage detection methods based on changes in natural frequencies, curvature or strain modes, modal strain energy, dynamic flexibility, artificial neural networks, before and after damage, and other signal processing methods such as Wavelet techniques, empirical mode decomposition and Hilbert spectrum methods are discussed in this chapter.

Pandemic (H1N1) 2009 Influenza Outbreak in Australia: Impact on Emergency Departments.

Executive summary Objective: The aims of this study were to identify the impact of Pandemic (H1N1) 2009 Influenza on Australian Emergency Departments (EDs) and their staff, and to inform planning, preparedness, and response management arrangements for future pandemics, as well as managing infectious patients presenting to EDs in everyday practice. Methods This study involved three elements: 1. The first element of the study was an examination of published material including published statistics. Standard literature research methods were used to identify relevant published articles. In addition, data about ED demand was obtained from Australian Government Department of Health and Ageing (DoHA) publications, with several state health departments providing more detailed data. 2. The second element of the study was a survey of Directors of Emergency Medicine identified with the assistance of the Australasian College for Emergency Medicine (ACEM). This survey retrieved data about demand for ED services and elicited qualitative comments on the impact of the pandemic on ED management. 3. The third element of the study was a survey of ED staff. A questionnaire was emailed to members of three professional colleges—the ACEM; the Australian College of Emergency Nursing (ACEN); and the College of Emergency Nursing Australasia (CENA). The overall response rate for the survey was 18.4%, with 618 usable responses from 3355 distributed questionnaires. Topics covered by the survey included ED conditions during the (H1N1) 2009 influenza pandemic; information received about Pandemic (H1N1) 2009 Influenza; pandemic plans; the impact of the pandemic on ED staff with respect to stress; illness prevention measures; support received from others in work role; staff and others’ illness during the pandemic; other factors causing ED staff to miss work during the pandemic; and vaccination against Pandemic (H1N1) 2009 Influenza. Both qualitative and quantitative data were collected and analysed. Results: The results obtained from Directors of Emergency Medicine quantifying the impact of the pandemic were too limited for interpretation. Data sourced from health departments and published sources demonstrated an increase in influenza-like illness (ILI) presentations of between one and a half and three times the normal level of presentations of ILIs. Directors of Emergency Medicine reported a reasonable level of preparation for the pandemic, with most reporting the use of pandemic plans that translated into relatively effective operational infection control responses. Directors reported a highly significant impact on EDs and their staff from the pandemic. Growth in demand and related ED congestion were highly significant factors causing distress within the departments. Most (64%) respondents established a ‘flu clinic’ either as part of Pandemic (H1N1) 2009 Influenza Outbreak in Australia: Impact on Emergency Departments. the ED operations or external to it. They did not note a significantly higher rate of sick leave than usual. Responses relating to the impact on staff were proportional to the size of the colleges. Most respondents felt strongly that Pandemic (H1N1) 2009 Influenza had a significant impact on demand in their ED, with most patients having low levels of clinical urgency. Most respondents felt that the pandemic had a negative impact on the care of other patients, and 94% revealed some increase in stress due to lack of space for patients, increased demand, and filling staff deficits. Levels of concern about themselves or their family members contracting the illness were less significant than expected. Nurses displayed significantly higher levels of stress overall, particularly in relation to skill-mix requirements, lack of supplies and equipment, and patient and patients’ family aggression. More than one-third of respondents became ill with an ILI. Whilst respondents themselves reported taking low levels of sick leave, respondents cited difficulties with replacing absent staff. Ranked from highest to lowest, respondents gained useful support from ED colleagues, ED administration, their hospital occupational health department, hospital administration, professional colleges, state health department, and their unions. Respondents were generally positive about the information they received overall; however, the volume of information was considered excessive and sometimes inconsistent. The media was criticised as scaremongering and sensationalist and as being the cause of many unnecessary presentations to EDs. Of concern to the investigators was that a large proportion (43%) of respondents did not know whether a pandemic plan existed for their department or hospital. A small number of staff reported being redeployed from their usual workplace for personal risk factors or operational reasons. As at the time of survey (29 October –18 December 2009), 26% of ED staff reported being vaccinated against Pandemic (H1N1) 2009 Influenza. Of those not vaccinated, half indicated they would ‘definitely’ or ‘probably’ not get vaccinated, with the main reasons being the vaccine was ‘rushed into production’, ‘not properly tested’, ‘came out too late’, or not needed due to prior infection or exposure, or due to the mildness of the disease. Conclusion: Pandemic (H1N1) 2009 Influenza had a significant impact on Australian Emergency Departments. The pandemic exposed problems in existing plans, particularly a lack of guidelines, general information overload, and confusion due to the lack of a single authoritative information source. Of concern was the high proportion of respondents who did not know if their hospital or department had a pandemic plan. Nationally, the pandemic communication strategy needs a detailed review, with more engagement with media networks to encourage responsible and consistent reporting. Also of concern was the low level of immunisation, and the low level of intention to accept vaccination. This is a problem seen in many previous studies relating to seasonal influenza and health care workers. The design of EDs needs to be addressed to better manage infectious patients. Significant workforce issues were confronted in this pandemic, including maintaining appropriate staffing levels; staff exposure to illness; access to, and appropriate use of, personal protective equipment (PPE); and the difficulties associated with working in PPE for prolonged periods. An administrative issue of note was the reporting requirement, which created considerable additional stress for staff within EDs. Peer and local support strategies helped ensure staff felt their needs were provided for, creating resilience, dependability, and stability in the ED workforce. Policies regarding the establishment of flu clinics need to be reviewed. The ability to create surge capacity within EDs by considering staffing, equipment, physical space, and stores is of primary importance for future pandemics.

An enhanced explicit rate algorithm for ABR traffic control in ATM networks

A high performance, low computational complexity rate-based flow control algorithm which can avoid congestion and achieve fairness is important to ATM available bit rate service. The explicit rate allocation algorithm proposed by Kalampoukas et al. is designed to achieve max–min fairness in ATM networks. It has several attractive features, such as a fixed computational complexity of O(1) and the guaranteed convergence to max–min fairness. In this paper, certain drawbacks of the algorithm, such as the severe overload of an outgoing link during transient period and the non-conforming use of the current cell rate field in a resource management cell, have been identified and analysed; a new algorithm which overcomes these drawbacks is proposed. The proposed algorithm simplifies the rate computation as well. Compared with Kalampoukas's algorithm, it has better performance in terms of congestion avoidance and smoothness of rate allocation.

Fusing curricula : science, technology and ICT

Curriculum demands continue to increase on school education systems with teachers at the forefront of implementing syllabus requirements. Education is reported frequently as a solution to most societal problems and, as a result of the world’s information explosion, teachers are expected to cover more and more within teaching programs. How can teachers combine subjects in order to capitalise on the competing educational agendas within school timeframes? Fusing curricula requires the bonding of standards from two or more syllabuses. Both technology and ICT complement the learning of science. This study analyses selected examples of preservice teachers’ overviews for fusing science, technology and ICT. These program overviews focused on primary students and the achievement of two standards (one from science and one from either technology or ICT). These primary preservice teachers’ fused-curricula overviews included scientific concepts and related technology and/or ICT skills and knowledge. Findings indicated a range of innovative curriculum plans for teaching primary science through technology and ICT, demonstrating that these subjects can form cohesive links towards achieving the respective learning standards. Teachers can work more astutely by fusing curricula; however further professional development may be required to advance thinking about these processes. Bonding subjects through their learning standards can extend beyond previous integration or thematic work where standards may not have been assessed. Education systems need to articulate through syllabus documents how effective fusing of curricula can be achieved. It appears that education is a key avenue for addressing societal needs, problems and issues. Education is promoted as a universal solution, which has resulted in curriculum overload (Dare, Durand, Moeller, & Washington, 1997; Vinson, 2001). Societal and curriculum demands have placed added pressure on teachers with many extenuating education issues increasing teachers’ workloads (Mobilise for Public Education, 2002). For example, as Australia has weather conducive for outdoor activities, social problems and issues arise that are reported through the media calling for action; consequently schools have been involved in swimming programs, road and bicycle safety programs, and a wide range of activities that had been considered a parental responsibility in the past. Teachers are expected to plan, implement and assess these extra-curricula activities within their already overcrowded timetables. At the same stage, key learning areas (KLAs) such as science and technology are mandatory requirements within all Australian education systems. These systems have syllabuses outlining levels of content and the anticipated learning outcomes (also known as standards, essential learnings, and frameworks). Time allocated for teaching science in obviously an issue. In 2001, it was estimated that on average the time spent in teaching science in Australian Primary Schools was almost an hour per week (Goodrum, Hackling, & Rennie, 2001). More recently, a study undertaken in the U.S. reported a similar finding. More than 80% of the teachers in K-5 classrooms spent less than an hour teaching science (Dorph, Goldstein, Lee, et al., 2007). More importantly, 16% did not spend teaching science in their classrooms. Teachers need to learn to work smarter by optimising the use of their in-class time. Integration is proposed as one of the ways to address the issue of curriculum overload (Venville & Dawson, 2005; Vogler, 2003). Even though there may be a lack of definition for integration (Hurley, 2001), curriculum integration aims at covering key concepts in two or more subject areas within the same lesson (Buxton & Whatley, 2002). This implies covering the curriculum in less time than if the subjects were taught separately; therefore teachers should have more time to cover other educational issues. Expectedly, the reality can be decidedly different (e.g., Brophy & Alleman, 1991; Venville & Dawson, 2005). Nevertheless, teachers report that students expand their knowledge and skills as a result of subject integration (James, Lamb, Householder, & Bailey, 2000). There seems to be considerable value for integrating science with other KLAs besides aiming to address teaching workloads. Over two decades ago, Cohen and Staley (1982) claimed that integration can bring a subject into the primary curriculum that may be otherwise left out. Integrating science education aims to develop a more holistic perspective. Indeed, life is not neat components of stand-alone subjects; life integrates subject content in numerous ways, and curriculum integration can assist students to make these real-life connections (Burnett & Wichman, 1997). Science integration can provide the scope for real-life learning and the possibility of targeting students’ learning styles more effectively by providing more than one perspective (Hudson & Hudson, 2001). To illustrate, technology is essential to science education (Blueford & Rosenbloom, 2003; Board of Studies, 1999; Penick, 2002), and constructing technology immediately evokes a social purpose for such construction (Marker, 1992). For example, building a model windmill requires science and technology (Zubrowski, 2002) but has a key focus on sustainability and the social sciences. Science has the potential to be integrated with all KLAs (e.g., Cohen & Staley, 1982; Dobbs, 1995; James et al., 2000). Yet, “integration” appears to be a confusing term. Integration has an educational meaning focused on special education students being assimilated into mainstream classrooms. The word integration was used in the late seventies and generally focused around thematic approaches for teaching. For instance, a science theme about flight only has to have a student drawing a picture of plane to show integration; it did not connect the anticipated outcomes from science and art. The term “fusing curricula” presents a seamless bonding between two subjects; hence standards (or outcomes) need to be linked from both subjects. This also goes beyond just embedding one subject within another. Embedding implies that one subject is dominant, while fusing curricula proposes an equal mix of learning within both subject areas. Primary education in Queensland has eight KLAs, each with its established content and each with a proposed structure for levels of learning. Primary teachers attempt to cover these syllabus requirements across the eight KLAs in less than five hours a day, and between many of the extra-curricula activities occurring throughout a school year (e.g., Easter activities, Education Week, concerts, excursions, performances). In Australia, education systems have developed standards for all KLAs (e.g., Education Queensland, NSW Department of Education and Training, Victorian Education) usually designated by a code. In the late 1990’s (in Queensland), “core learning outcomes” for strands across all KLA’s. For example, LL2.1 for the Queensland Education science syllabus means Life and Living at Level 2 standard number 1. Thus, a teacher’s planning requires the inclusion of standards as indicated by the presiding syllabus. More recently, the core learning outcomes were replaced by “essential learnings”. They specify “what students should be taught and what is important for students to have opportunities to know, understand and be able to do” (Queensland Studies Authority, 2009, para. 1). Fusing science education with other KLAs may facilitate more efficient use of time and resources; however this type of planning needs to combine standards from two syllabuses. To further assist in facilitating sound pedagogical practices, there are models proposed for learning science, technology and other KLAs such as Bloom’s Taxonomy (Bloom, 1956), Productive Pedagogies (Education Queensland, 2004), de Bono’s Six Hats (de Bono, 1985), and Gardner’s Multiple Intelligences (Gardner, 1999) that imply, warrant, or necessitate fused curricula. Bybee’s 5 Es, for example, has five levels of learning (engage, explore, explain, elaborate, and evaluate; Bybee, 1997) can have the potential for fusing science and ICT standards.

Safety in occupational driving : development of a driver behaviour scale for the workplace context

International statistics indicate that occupational, or work-related driving, crashes are the most common cause of workplace injury, death, and absence from work. The majority of research examining unsafe driver behavior in the workplace has relied on general road safety questionnaires. However, past research has failed to consider the organizational context in the use of these questionnaires, and as such, there is ambiguity in the dimensions constituting occupational driving. Using a theoretical model developed by Hockey (1993, 1997), this article proposes and validates a new scale of occupational driver behavior. This scale incorporates four dimensions of driver behavior that are influenced by demanding workplace conditions; speeding, rule violation, inattention, and driving while tired. Following a content validation process, three samples of occupational drivers in Australia were used to assess the scale. Data from the first sample (n=145) were used to reduce the number of scale items and provide an assessment of the factorial validity of the scale. Data from the second sample (n=645) were then used to confirm the factor structure and psychometric properties of the scale including reliability and construct validity. Finally, data from the third sample (n=248) were used to establish criterion validity. The results indicated that the scale is a reliable and valid measure of occupational driver behavior.

Analysis of acoustic emission data for structural health monitoring applications

Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. It is one of the several diagnostic techniques currently used for structural health monitoring (SHM) of civil infrastructure such as bridges. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. But several challenges still exist. Due to high sampling rate required for data capture, large amount of data is generated during AE testing. This is further complicated by the presence of a number of spurious sources that can produce AE signals which can then mask desired signals. Hence, an effective data analysis strategy is needed to achieve source discrimination. This also becomes important for long term monitoring applications in order to avoid massive date overload. Analysis of frequency contents of recorded AE signals together with the use of pattern recognition algorithms are some of the advanced and promising data analysis approaches for source discrimination. This paper explores the use of various signal processing tools for analysis of experimental data, with an overall aim of finding an improved method for source identification and discrimination, with particular focus on monitoring of steel bridges.