Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.

The “virtual” producer in the recording studio : media networks in long distance peripheral performances

The producer has for many years been a central agent in recording studio sessions; the validation of this role was, in many ways, related to the producer’s physical presence in the studio, to a greater or lesser extent. However, improvements in the speed of digital networks have allowed studio sessions to be produced long-distance, in real-time, through communication programs such as Skype or REDIS. How does this impact on the role of the producer, a “nexus between the creative inspiration of the artist, the technology of the recording studio, and the commercial aspirations of the record company” (Howlett 2012)? From observations of a studio recording session in Lisbon produced through Skype from New York, this article focuses on the role of the producer in these relatively new recording contexts involving long distance media networks. Methodology involved participant observation carried out in Estúdios Namouche in Lisbon (where the session took place), as part of doctoral research. This ethnographic approach also included a number of semi-directed ethnographic interviews of the different actors in this scenario—musicians, recording engineers, composers and producers. As a theoretical framework, the research of De Zutter and Sawyer on Distributed Creativity is used, as the recording studio sets an example of “a cognitive system where […] tasks are not accomplished by separate individuals, but rather through the interactions of those individuals” (DeZutter 2009:4). Therefore, creativity often emerges as a result of this interaction.

Analysis of distance learner value assessment of distance education in engineering

Numerous research studies have evaluated whether distance learning is a viable alternative to traditional learning methods. These studies have generally made use of cross-sectional surveys for collecting data, comparing distance to traditional learners with intent to validate the former as a viable educational tool. Inherent fundamental differences between traditional and distance learning pedagogies, however, reduce the reliability of these comparative studies and constrain the validity of analyses resulting from this analytical approach. This article presents the results of a research project undertaken to analyze expectations and experiences of distance learners with their degree programs. Students were given surveys designed to examine factors expected to affect their overall value assessment of their distance learning program. Multivariate statistical analyses were used to analyze the correlations among variables of interest to support hypothesized relationships among them. Focusing on distance learners overcomes some of the limitations with assessments that compare off- and on-campus student experiences. Evaluation and modeling of distance learner responses on perceived value for money of the distance education they received indicate that the two most important influences are course communication requirements, which had a negative effect, and course logistical simplicity, which revealed a positive effect. Combined, these two factors accounted for approximately 47% of the variability in perceived value for money of the educational program of sampled students. A detailed focus on comparing expectations with outcomes of distance learners complements the existing literature dominated by comparative studies of distance and nondistance learners.

New criterion for the stability of a human body in floodwaters

The authors must be congratulated for their original and important study. The flooding of urbanised areas constitutes a hazard to the population and infrastructure. Floods through inundated urban environments have been studied only recently and few considered the potential impact of flowing waters on pedestrians...

Artefact ecologies : supporting embodied meeting practices with distance access

Frameworks such as activity theory, distributed cognition and structuration theory, amongst others, have shown that detailed study of contextual settings where users work (or live) can help the design of interactive systems. However, these frameworks do not adequately focus on accounting for the materiality (and embodiment) of the contextual settings. Within the IST-EU funded AMIDA project (Augmented Multiparty Interaction with Distance Access) we are looking into supporting meeting practices with distance access. Meetings are inherently embodied in everyday work life and that material artefacts associated with meeting practices play a critical role in their formation. Our eventual goal is to develop a deeper understanding of the dynamic and embodied nature of meeting practices and designing technologies to support these. In this paper we introduce the notion of "artefact ecologies" as a conceptual base for understanding embodied meeting practices with distance access. Artefact ecologies refer to a system consisting of different digital and physical artefacts, people, their work practices and values and lays emphasis on the role artefacts play in embodiment, work coordination and supporting remote awareness. In the end we layout our plans for designing technologies for supporting embodied meeting practices within the AMIDA project.

Transnational distance education : cultural and quality considerations

There have now been two decades of rhetoric on the need for culturally and contextually appropriate perspectives in international education. However, the extent to which courses, provision and pedagogy have truly reflected differences in cultural characteristics and learning preferences is still open to question. Little attention has been paid to these matters in quality assurance frameworks. This chapter discusses these issues and draws upon Hofstede’s cultural dimensions framework and studies into Asian pedagogy and uses of educational technology. It proposes a benchmark and performance indicators for assuring cultural, contextual, educational and technological appropriateness in the provision of transnational distance education in Asia by Australian universities.

Semantic spaces : measuring the distance between different subspaces

Semantic Space models, which provide a numerical representation of words’ meaning extracted from corpus of documents, have been formalized in terms of Hermitian operators over real valued Hilbert spaces by Bruza et al. [1]. The collapse of a word into a particular meaning has been investigated applying the notion of quantum collapse of superpositional states [2]. While the semantic association between words in a Semantic Space can be computed by means of the Minkowski distance [3] or the cosine of the angle between the vector representation of each pair of words, a new procedure is needed in order to establish relations between two or more Semantic Spaces. We address the question: how can the distance between different Semantic Spaces be computed? By representing each Semantic Space as a subspace of a more general Hilbert space, the relationship between Semantic Spaces can be computed by means of the subspace distance. Such distance needs to take into account the difference in the dimensions between subspaces. The availability of a distance for comparing different Semantic Subspaces would enable to achieve a deeper understanding about the geometry of Semantic Spaces which would possibly translate into better effectiveness in Information Retrieval tasks.

Opportunities and challenges : combining distance and on-campus students in concurrent courses

Through its Electronic Delivery of Gator Engineering (EDGE) program, University of Florida (UF) offers online master’s degrees from participating departments within the UF College of Engineering. Each master’s degree requires 10 courses (3 credit hours each). One interesting and unique aspect of the EDGE pro-gram is that distance learners are registered concurrently in the same courses with traditional on-campus students. This paper examines the specific challenges involved in integrating distance students into on-campus courses, including communication, interaction, access to resources, and equal grading practices.

Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

Long distance calling? Spatial preference patterns in enterprise microblogging in the retail industry

We examine enterprise social network usage data obtained from a community of store managers in a leading Australian retail organization, over a period of fifteen months. Our interest in examining this data is in spatial preferences by the network users, that is, to ascertain who is communicating with whom and where. We offer several contrasting theoretical perspectives for spatial preference patterns and examine these against data collected from over 12,000 messages exchanged between 530 managers in 897 stores. Our findings show that interactions can generally be characterized by individual preferences for local communication but also that two different user communities exist – locals and globals. We develop empirical profiles for these social network user communities and outline implications for theories on spatial influences on communication behaviours on enterprise social networks.

Blended learning : meeting the needs of distance education students

This thesis involved research into the barriers and enablers that existed for a cohort of mature-aged education support students engaging with blended learning through distance education. The findings that emerged from this research indicated that a flexible model of blended learning is possible in this context. The findings shed light on the experiences of novice technology users' participation in blended learning. The study highlighted the significance of factors such as isolation, technology, communication, connectivity, prior learning, and the growth of self-efficacy that influenced learner engagement.

Compositional data analysis (CoDA) approaches to distance in information retrieval

Many techniques in information retrieval produce counts from a sample, and it is common to analyse these counts as proportions of the whole - term frequencies are a familiar example. Proportions carry only relative information and are not free to vary independently of one another: for the proportion of one term to increase, one or more others must decrease. These constraints are hallmarks of compositional data. While there has long been discussion in other fields of how such data should be analysed, to our knowledge, Compositional Data Analysis (CoDA) has not been considered in IR. In this work we explore compositional data in IR through the lens of distance measures, and demonstrate that common measures, naïve to compositions, have some undesirable properties which can be avoided with composition-aware measures. As a practical example, these measures are shown to improve clustering. Copyright 2014 ACM.