Aircraft collision avoidance using spherical visual predictive control and single point features

This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

The engagement of small to medium enterprises for managing waste in building retrofit projects

The market of building retrofits is increasingly more intensified as existing buildings are aging. The building retrofit projects involve existing buildings which impose constraints on stakeholders throughout the project process. They are also risky, complex, less predictable and difficult to be well planned with on-site waste becoming one of the critical issues. Small and Medium Enterprises (SMEs) carry out most of the work in retrofit projects as subcontractors, but they often do not have adequate resources to deal with the specific technical challenges and project risks related to waste. This paper first discusses the requirements of waste management in building retrofit projects considering specific project characteristics and work natures, and highlights the importance of involving SMEs in waste planning and management through an appropriate way. By utilizing semi-structured interviews, this research develops a process model for SMEs to be applied in waste management. A collaboration scenario is also developed for collaborative waste planning and management by SMEs as subcontractors and large companies as main contractors. Findings from the paper will promote coordination of project delivery and waste management in building retrofit projects, and improve the involvement and performance of SMEs in dealing with waste problems.

How to guarantee compliance between workflows and product lifecycles?

Product Lifecycle Management (PLM) systems are widely used in the manufacturing industry. A core feature of such systems is to provide support for versioning of product data. As workflow functionality is increasingly used in PLM systems, the possibility emerges that the versioning transitions for product objects as encapsulated in process models do not comply with the valid version control policies mandated in the objects’ actual lifecycles. In this paper we propose a solution to tackle the (non-)compliance issues between processes and object version control policies. We formally define the notion of compliance between these two artifacts in product lifecycle management and then develop a compliance checking method which employs a well-established workflow analysis technique. This forms the basis of a tool which offers automated support to the proposed approach. By applying the approach to a collection of real-life specifications in a main PLM system, we demonstrate the practical applicability of our solution to the field.

Causal behavioural profiles : efficient computation, applications, and evaluation

Analysis of behavioural consistency is an important aspect of software engineering. In process and service management, consistency verification of behavioural models has manifold applications. For instance, a business process model used as system specification and a corresponding workflow model used as implementation have to be consistent. Another example would be the analysis to what degree a process log of executed business operations is consistent with the corresponding normative process model. Typically, existing notions of behaviour equivalence, such as bisimulation and trace equivalence, are applied as consistency notions. Still, these notions are exponential in computation and yield a Boolean result. In many cases, however, a quantification of behavioural deviation is needed along with concepts to isolate the source of deviation. In this article, we propose causal behavioural profiles as the basis for a consistency notion. These profiles capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities of a process model. Consistency based on these profiles is weaker than trace equivalence, but can be computed efficiently for a broad class of models. In this article, we introduce techniques for the computation of causal behavioural profiles using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets. We also elaborate on the findings of applying our technique to three industry model collections.

Efficient computation of causal behavioural profiles using structural decomposition

Identification of behavioural contradictions is an important aspect of software engineering, in particular for checking the consistency between a business process model used as system specification and a corresponding workflow model used as implementation. In this paper, we propose causal behavioural profiles as the basis for a consistency notion, which capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities. Existing notions of behavioural equivalence, such as bisimulation and trace equivalence, might also be applied as consistency notions. Still, they are exponential in computation. Our novel concept of causal behavioural profiles provides a weaker behavioural consistency notion that can be computed efficiently using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets.

Dimensions of business processes quality (QoBP)

Conceptual modeling is an important tool for understanding and revealing weaknesses of business processes. Yet, the current practice in reengineering projects often considers simply the as-is process model as a brain-storming tool. This approach heavily relies on the intuition of the participants and misses a clear description of the quality requirements. Against this background, we identify four generic quality categories of business process quality, and populate them with quality requirements from related research. We refer to the resulting framework as the Quality of Business Process (QoBP) framework. Furthermore, we present the findings from applying the QoBP framework in a case study with a major Australian bank, showing that it helps to systematically fill the white space between as-is and to-be process modeling.

Depression and belongingness in general and workplace contexts : a cross-lagged longitudinal investigation

Belongingness has been linked to depression. Prior studies have been cross-sectional with few addressing distinct belongingness contexts. This study used structural equation modelling to investigate cross-lagged longitudinal relationships between general belonging, workplace belonging and depressive symptoms in a community sample of 221 working adults measured at two time points three months apart. Measures were: Sense of Belonging Instrument-Psychological (SOBI-P); Psychological Sense of Organizational Membership (PSOM); Depression Anxiety Stress Scales (DASS-21); Kessler Psychological Distress Scale (K10). General belonging was predicted more strongly by depressive symptoms than by baseline general belonging, suggesting that depressive symptoms not only linger but also influence future belongingness cognitions. Neither general nor workplace belonging longitudinally predicted depressive symptoms, however cross-sectional correlations were substantial. The concurrent path between general belongingness and depressive symptoms was strong. Results are consistent with daily process studies suggesting that reduced belongingness precipitates a rapid increase in depressive symptoms which influence longer term belongingness cognitions. Congruent with interpersonal descriptions of depression such as the social-cognitive interpersonal process model, results further suggest that belongingness cognitions are the proximal antecedent of a depressive response. Practitioners should monitor both a general sense of belonging as well as perceived relational value cues in specific contexts.

Beyond tasks and gateways: discovering BPMN models with subprocesses, boundary events and activity markers

Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.

Analysis and modelling of the hydraulic conductivity in aquitards : application to the Galilee Basin and the Great Artesian Basin, Australia

In large sedimentary basins with layers of different rocks, the groundwater flow between aquifers depends on the hydraulic conductivity (K) of the separating low-permeable rocks, or aquitards. Three methods were developed to evaluate K in aquitards for areas with limited field data: • Coherence and harmonic analysis: estimates the regional-scale K based on water-level fluctuations in adjacent aquifers. • Cokriging and Bayes' rule: infers K from downhole geophysical logs. • Fluvial process model: reproduces the lithology architecture of sediment formations which can be converted to K. These proposed methods enable good estimates of K and better planning of further drillholes.

Communicating engagement in corporate social responsibility : a meta-level construal of engagement

Organizations are increasingly seeking stakeholder support through engagement to demonstrate their corporate social responsibility (CSR) credentials. These credentials are in turn used to support claims of legitimacy for organizational operations. This paper uses a process model of antecedents, implementation, and consequences to study the connection between engagement and CSR. CSR reports show organizations perceive engagement in CSR as both communication and activities between organizations and their stakeholders; and as a second, meta-level of communication about that engagement with stakeholders beyond those directly involved, thereby broadening the scope of organizational claims to legitimacy. Understanding what engagement is and how and why it is carried out in CSR provides a framework for understanding engagement in public relations.

Risk management and high reliability : a case study of Australian airport management

This thesis investigated risk management and organisational reliability in airports from the perspective of complex sociotechnical systems (CSSs). Two research studies were undertaken, the first focusing on the processes by which disruptive events occur, are detected and responded to; the second exploring the presence of organisational reliability traits within airports. A key result of the studies was the development of new approach: the Critical Incident Disturbance Process model that detailed a means to understand and analyse how disruptions in complex CSSs might be influenced by vulnerability reduction and enhanced risk management. Further, this thesis identified and defined the concept of 'compartmentalised reliability' in complex sociotechnical systems, extending existing knowledge of high reliability theory.

The perspectives of older drivers on the impact of feedback on their driving behaviours : a qualitative study

Self-regulation is a coping strategy that allows older drivers to drive safely for longer. Self-regulation depends largely on the ability of drivers to evaluate their own driving. Therefore the success of self-regulation, in terms of driving safety, is influenced by the ability of older drivers to have insight into their declining driving performance. In addition, previous studies suggest that providing feedback to older adults regarding their driving skills may lead them to change their driving behaviour. However, little is currently known about the impact of feedback on older drivers’ self-awareness and their subsequent driving regulatory behaviour. This study explored the process of self-regulation and driving cessation among older drivers using the PAPM as a framework. It also investigated older adults’ perceptions and opinions about receiving feedback in regards to their driving abilities. Qualitative focus groups with 27 participants aged 70 years or more were conducted. Thematic analysis resulted in the development of five main themes; the meaning of driving, changes in driving pattern, feedback, the planning process, and solutions. The analysis also resulted in an initial model of driving self-regulation among older drivers that is informed by the current research and the Precaution Adoption Process Model as the theoretical framework. It identifies a number of social, personal, and environmental factors that can either facilitate or hinder people’s transition between stages of change. The findings from this study suggest that further elaboration of the PAPM is needed to take into account the role of insight and feedback on the process of self-regulation among older drivers.

Special issue on best papers from the "BPM 2012" workshops

Business Process Management (BPM) (Dumas et al. 2013) investigates how organizations function and can be improved on the basis of their business processes. The starting point for BPM is that organizational performance is a function of process performance. Thus, BPM proposes a set of methods, techniques and tools to discover, analyze, implement, monitor and control business processes, with the ultimate goal of improving these processes. Most importantly, BPM is not just an organizational management discipline. BPM also studies how technology, and particularly information technology, can effectively support the process improvement effort. In the past two decades the field of BPM has been the focus of extensive research, which spans an increasingly growing scope and advances technology in various directions. The main international forum for state-of-the-art research in this field is the International Conference on Business Process Management, or “BPM” for short—an annual meeting of the aca ...

Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging

Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

Non-parametric consistency test for multiple-sensing-modality data fusion

Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.