Outdoor simultaneous localisation and mapping using RatSLAM

In this paper an existing method for indoor Simultaneous Localisation and Mapping (SLAM) is extended to operate in large outdoor environments using an omnidirectional camera as its principal external sensor. The method, RatSLAM, is based upon computational models of the area in the rat brain that maintains the rodent’s idea of its position in the world. The system uses the visual appearance of different locations to build hybrid spatial-topological maps of places it has experienced that facilitate relocalisation and path planning. A large dataset was acquired from a dynamic campus environment and used to verify the system’s ability to construct representations of the world and simultaneously use these representations to maintain localisation.

Effective shear modulus approach for two dimensional solids and plate bending problems by meshless point collocation method

For the analysis of material nonlinearity, an effective shear modulus approach based on the strain control method is proposed in this paper by using point collocation method. Hencky’s total deformation theory is used to evaluate the effective shear modulus, Young’s modulus and Poisson’s ratio, which are treated as spatial field variables. These effective properties are obtained by the strain controlled projection method in an iterative manner. To evaluate the second order derivatives of shape function at the field point, the radial basis function (RBF) in the local support domain is used. Several numerical examples are presented to demonstrate the efficiency and accuracy of the proposed method and comparisons have been made with analytical solutions and the finite element method (ABAQUS).

Face recognition across pose on video using eigen light-fields

We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fields within which the classification takes place. We modify the original light-field projection and found that it is more robust in the proposed system. Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video.

Learning informative features for indoor traversability

This paper presents a method for automatic terrain classification, using a cheap monocular camera in conjunction with a robot’s stall sensor. A first step is to have the robot generate a training set of labelled images. Several techniques are then evaluated for preprocessing the images, reducing their dimensionality, and building a classifier. Finally, the classifier is implemented and used online by an indoor robot. Results are presented, demonstrating an increased level of autonomy.

A semi-local method for iterative depth-map refinement

We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.

A strategy for delayed research method selection : deciding between grounded theory and phenomenology

This paper presents a strategy for delayed research method selection in a qualitative interpretivist research. An exemplary case details how explorative interviews were designed and conducted in accordance with a paradigm prior to deciding whether to adopt grounded theory or phenomenology for data analysis. The focus here is to determine the most appropriate research strategy in this case the methodological framing to conduct research and represent findings, both of which are detailed. Research addressing current management issues requires both a flexible framework and the capability to consider the research problem from various angles, to derive tangible results for academia with immediate application to business demands. Researchers, and in particular novices, often struggle to decide on an appropriate research method suitable to address their research problem. This often applies to interpretative qualitative research where it is not always immediately clear which is the most appropriate method to use, as the research objectives shift and crystallize over time. This paper uses an exemplary case to reveal how the strategy for delayed research method selection contributes to deciding whether to adopt grounded theory or phenomenology in the initial phase of a PhD research project. In this case, semi-structured interviews were used for data generation framed in an interpretivist approach, situated in a business context. Research questions for this study were thoroughly defined and carefully framed in accordance with the research paradigm‟s principles, while at the same time ensuring that the requirements of both potential research methods were met. The grounded theory and phenomenology methods were compared and contrasted to determine their suitability and whether they meet the research objectives based on a pilot study. The strategy proposed in this paper is an alternative to the more „traditional‟ approach, which initially selects the methodological formulation, followed by data generation. In conclusion, the suggested strategy for delayed research method selection intends to help researchers identify and apply the most appropriate method to their research. This strategy is based on explorations of data generation and analysis in order to derive faithful results from the data generated.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Behavioural evidence for social preferences

A central topic in economics is the existence of social preferences. Behavioural economics in general has approached the issue from several angles. Controlled experimental settings, surveys, and field experiments are able to show that in a number of economic environments, people usually care about immaterial things such as fairness or equity of allocations. Findings from experimental economics specifically have lead to large increase in theories addressing social preferences. Most (pro)social phenomena are well understood in the experimental settings but very difficult to observe 'in the wild'. One criticism in this regard is that many findings are bound by the artificial environment of the computer lab or survey method used. A further criticism is that the traditional methods also fail to directly attribute the observed behaviour to the mental constructs that are expected to stand behind them. This thesis will first examine the usefulness of sports data to test social preference models in a field environment, thus overcoming limitations of the lab with regards to applicability to other - non-artificial - environments. The second major contribution of this research establishes a new neuroscientific tool - the measurement of the heart rate variability - to observe participants' emotional reactions in a traditional experimental setup.

A radiological method to determine the accuracy of motion capture marker placement on palpable anatomical landmarks through a shoe

The accuracy of marker placement on palpable surface anatomical landmarks is an important consideration in biomechanics. Although marker placement reliability has been studied in some depth, it remains unclear whether or not the markers are accurately positioned over the intended landmark in order to define the static position and orientation of the segment. A novel method using commonly available X-ray imaging was developed to identify the accuracy of markers placed on the shoe surface by palpating landmarks through the shoe. An anterior–posterior and lateral–medial X-ray was taken on 24 participants with a newly developed marker set applied to both the skin and shoe. The vector magnitude of both skin- and shoe-mounted markers from the anatomical landmark was calculated, as well as the mean marker offset between skin- and shoe-mounted markers. The accuracy of placing markers on the shoe relative to the skin-mounted markers, accounting for shoe thickness, was less than 5mm for all markers studied. Further, when using the developed guidelines provided in this study, the method was deemed reliable (Intra-rater ICCs¼0.50–0.92). In conclusion, the method proposed here can reliably assess marker placement accuracy on the shoe surface relative to chosen anatomical landmarks beneath the skin.

Advanced musculoskeletal simulation as an ergonomic design method

In recent years, the advent of new tools for musculoskeletal simulation has increased the potential for significantly improving the ergonomic design process and ergonomic assessment of design. In this paper we investigate the use of one such tool, ‘The AnyBody Modeling System’, applied to solve a one-parameter and yet, complex ergonomic design problem. The aim of this paper is to investigate the potential of computer-aided musculoskeletal modelling in the ergonomic design process, in the same way as CAE technology has been applied to engineering design.

Numerical method for predicting the elastic lateral distortional buckling moment of a mono-symmetric beam with web openings

When used as floor joists, the new mono-symmetric LiteSteel beam (LSB) sections require web openings to provide access for inspections and various services. The LSBs consist of two rectangular hollow flanges connected by a slender web, and are subjected to lateral distortional buckling effects in the intermediate span range. Their member capacity design formulae developed to date are based on their elastic lateral buckling moments, and only limited research has been undertaken to predict the elastic lateral buckling moments of LSBs with web openings. This paper addresses this research gap by reporting the development of web opening modelling techniques based on an equivalent reduced web thickness concept and a numerical method for predicting the elastic buckling moments of LSBs with circular web openings. The proposed numerical method was based on a formulation of the total potential energy of LSBs with circular web openings. The accuracy of the proposed method’s use with the aforementioned modelling techniques was verified through comparison of its results with those of finite strip and finite element analyses of various LSBs.

Design of LiteSteel Beam floor joists with web opening using an equivalent web thickness method

The LiteSteel Beam (LSB) is an innovative cold-formed steel hollow flange section. When used as floor joists, the LSB sections require holes in the web to provide access for various services. In this study a detailed investigation was undertaken into the elastic lateral distortional buckling behaviour of LSBs with circular web openings subjected to a uniform moment using finite element analysis. Validated ideal finite element models were used first to study the effect of web holes on their elastic lateral distortional buckling behaviour. An equivalent web thickness method was then proposed using four different equations for the elastic buckling analyses of LSBs with web holes. It was found that two of them could be successfully used with approximate numerical models based on solid web elements with an equivalent reduced thickness to predict the elastic lateral distortional buckling moments.

Trust, reputation and the small firm : building online brand reputation for SMEs

Social media provides numerous opportunities for small businesses to promote their products and services, build brand communities and reach diverse market niches. An important factor in seizing these opportunities is developing trust and creating reputation among consumers. This qualitative study examines how a group of Australian small business managers utilize social media websites to connect to, communicate with and maintain their customer base. For the purpose of this paper we are using case studies of four companies physically based in Victoria, Australia. These businesses have a high presence in online consumer groups, being both active members of communities and representatives of their businesses. The duality of their role as participant and company representative imposes difficulties in creating reputation among community members. We have used in-depth interviews as a primary research method, additionally monitoring their activities on social media sites such as forums, social networking services, blogs and micro-blogs. We have identified practices helpful for developing trust, building reputation and create a brand image in online communities.

Learning and acting in project situations through a meta-method (MAP) a case study : contextual and situational approach for project management governance in management education

The paper introduces the underlying principles and the general features of a meta-method (MAP method) developed as part of and used in various research, education and professional development programmes at ESC Lille. This method aims at providing effective and efficient structure and process for acting and learning in various complex, uncertain and ambiguous managerial situations (projects, programmes, portfolios). The paper is developed around three main parts. First, I suggest revisiting the dominant vision of the project management knowledge field, based on the assumptions they are not addressing adequately current business and management contexts and situations, and that competencies in management of entrepreneurial activities are the sources of creation of value for organisations. Then, grounded on the former developments, I introduce the underlying concepts supporting MAP method seen as a ‘convention generator’ and how this meta method inextricably links learning and practice in addressing managerial situations. Finally, I briefly describe an example of application, illustrating with a case study how the method integrates Project Management Governance, and give few examples of use in Management Education and Professional Development.