Managing large collections of business process models - Current techniques and challenges

Nowadays, business process management is an important approach for managing organizations from an operational perspective. As a consequence, it is common to see organizations develop collections of hundreds or even thousands of business process models. Such large collections of process models bring new challenges and provide new opportunities, as the knowledge that they encapsulate requires to be properly managed. Therefore, a variety of techniques for managing large collections of business process models is being developed. The goal of this paper is to provide an overview of the management techniques that currently exist, as well as the open research challenges that they pose.

A framework for analysing system intelligence of the building control system: a study of the integrated building management system

The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.

Stability of hydrotalcites formed from Bayer refinery environmental control processes

Bauxite refinery residues (red mud) are derived from the Bayer process by the digestion of crushed bauxite in concentrated sodium hydroxide at elevated temperatures and pressures. This slurry residue, if untreated, is unsuitable for discharge directly into the environment and is usually stored in tailing dams. The liquid portion has the potential for discharge, but requires pre-treatment before this can occur. The seawater neutralisation treatment facilitates a significant reduction in pH and dissolved metal concentrations, through the precipitation of hydrotalcite-like compounds and some other Mg, Ca, and Al hydroxide and carbonate minerals. The hydrotalcite-like compounds, precipitated during seawater neutralisation, also remove a range of transition metals, oxy-anions and other anionic species through a combination of intercalation and adsorption reactions: smaller anions are intercalated into the hydrotalcite matrix, while larger molecules are adsorbed on the particle surfaces. A phenomenon known as ‘reversion’ can occur if the seawater neutralisation process is not properly controlled. Reversion causes an increase in the pH and dissolved impurity levels of the neutralised effluent, rendering it unsuitable for discharge. It is believed that slow dissolution of components of the red mud residue and compounds formed during the neutralisation process are responsible for reversion. This investigation looked at characterising natural hydrotalcite (Mg6Al2(OH)16(CO3)∙4H2O) and ‘Bayer’ hydrotalcite (synthesised using the seawater neutralisation process) using a variety of techniques including X-ray diffraction, infrared and Raman spectroscopy, and thermogravimetric analysis. This investigation showed that Bayer hydrotalcite is comprised of a mixture of 3:1 and 4:1 hydrotalcite structures and exhibited similar chemical characteristic to the 4:1 synthetic hydrotalcite. Hydrotalcite formed from the seawater neutralisation of Bauxite refinery residues has been found not to cause reversion. Other components in red mud were investigated to determine the cause of reversion and this investigation found three components that contributed to reversion: 1) tricalcium aluminate, 2) hydrocalumite and 3) calcium hydroxide. Increasing the amount of magnesium in the neutralisation process has been found to be successful in reducing reversion.

Fast detection of exact clones in business process model repositories

As organizations reach higher levels of business process management maturity, they often find themselves maintaining very large process model repositories, representing valuable knowledge about their operations. A common practice within these repositories is to create new process models, or extend existing ones, by copying and merging fragments from other models. We contend that if these duplicate fragments, a.k.a. ex- act clones, can be identified and factored out as shared subprocesses, the repository’s maintainability can be greatly improved. With this purpose in mind, we propose an indexing structure to support fast detection of clones in process model repositories. Moreover, we show how this index can be used to efficiently query a process model repository for fragments. This index, called RPSDAG, is based on a novel combination of a method for process model decomposition (namely the Refined Process Structure Tree), with established graph canonization and string matching techniques. We evaluated the RPSDAG with large process model repositories from industrial practice. The experiments show that a significant number of non-trivial clones can be efficiently found in such repositories, and that fragment queries can be handled efficiently.

Factors of process model comprehension : findings from a series of experiments

In order to make good decisions about the design of information systems, an essential skill is to understand process models of the business domain the system is intended to support. Yet, little knowledge to date has been established about the factors that affect how model users comprehend the content of process models. In this study, we use theories of semiotics and cognitive load to theorize how model and personal factors influence how model viewers comprehend the syntactical information of process models. We then report on a four-part series of experiments, in which we examined these factors. Our results show that additional semantical information impedes syntax comprehension, and that theoretical knowledge eases syntax comprehension. Modeling experience further contributes positively to comprehension efficiency, measured as the ratio of correct answers to the time taken to provide answers. We discuss implications for practice and research.

Sensor fault-tolerant observer applied in satellite attitude control

The observing failure and feedback instability might happen when the partial sensors of a satellite attitude control system (SACS) go wrong. A fault diagnosis and isolation (FDI) method based on a fault observer is introduced to detect and isolate the fault sensor at first. Based on the FDI result, the object system state-space equation is transformed and divided into a corresponsive triangular canonical form to decouple the normal subsystem from the fault subsystem. And then the KX fault-tolerant observers of the system in different modes are designed and embedded into online monitoring. The outputs of all KX fault-tolerant observers are selected by the control switch process. That can make sense that the SACS is part-observed and in stable when the partial sensors break down. Simulation results demonstrate the effectiveness and superiority of the proposed method.

Conflict or consensus : an investigation of stakeholder concerns during the participation process of major infrastructure and construction projects in Hong Kong

Public participate in the planning and design of major public infrastructure and construction (PIC) projects is crucial to their success, as the interests of different stakeholders can be systematically captured and built into the finalised scheme. However, public participation may not always yield a mutually acceptable solution, especially when the interests of stakeholders are diverse and conflicting. Confrontations and disputes can arise unless the concerns or needs of the community are carefully analysed and addressed. The aim of the paper is to propose a systematic method of analysing stakeholder concerns relating to PIC projects by examining the degree of consensus and/or conflict involved. The results of a questionnaire survey and a series of interviews with different entities are provided, which indicate the existence of a significant divergence of views among stakeholder groups and that conflicts arise when there is a mismatch between peoples’ perception concerning money and happiness on the one hand and development and damages on the other. Policy and decision-makers should strive to resolve at least the majority of conflicts that arise throughout the lifecycle of major PIC projects so as to maximise their chance of success.

Improvisation in interactive music systems

This project investigates machine listening and improvisation in interactive music systems with the goal of improvising musically appropriate accompaniment to an audio stream in real-time. The input audio may be from a live musical ensemble, or playback of a recording for use by a DJ. I present a collection of robust techniques for machine listening in the context of Western popular dance music genres, and strategies of improvisation to allow for intuitive and musically salient interaction in live performance. The findings are embodied in a computational agent – the Jambot – capable of real-time musical improvisation in an ensemble setting. Conceptually the agent’s functionality is split into three domains: reception, analysis and generation. The project has resulted in novel techniques for addressing a range of issues in each of these domains. In the reception domain I present a novel suite of onset detection algorithms for real-time detection and classification of percussive onsets. This suite achieves reasonable discrimination between the kick, snare and hi-hat attacks of a standard drum-kit, with sufficiently low-latency to allow perceptually simultaneous triggering of accompaniment notes. The onset detection algorithms are designed to operate in the context of complex polyphonic audio. In the analysis domain I present novel beat-tracking and metre-induction algorithms that operate in real-time and are responsive to change in a live setting. I also present a novel analytic model of rhythm, based on musically salient features. This model informs the generation process, affording intuitive parametric control and allowing for the creation of a broad range of interesting rhythms. In the generation domain I present a novel improvisatory architecture drawing on theories of music perception, which provides a mechanism for the real-time generation of complementary accompaniment in an ensemble setting. All of these innovations have been combined into a computational agent – the Jambot, which is capable of producing improvised percussive musical accompaniment to an audio stream in real-time. I situate the architectural philosophy of the Jambot within contemporary debate regarding the nature of cognition and artificial intelligence, and argue for an approach to algorithmic improvisation that privileges the minimisation of cognitive dissonance in human-computer interaction. This thesis contains extensive written discussions of the Jambot and its component algorithms, along with some comparative analyses of aspects of its operation and aesthetic evaluations of its output. The accompanying CD contains the Jambot software, along with video documentation of experiments and performances conducted during the project.

Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes

Exploiting wind-energy is one possible way to ex- tend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

Reducing Actuator Switchings for Motion Control of Autonomous Underwater Vehicles

A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle. Indeed, due to the vehicles' design and the actuation modes usually under consideration for underwater plateforms the number of actuator switchings must be kept to a small value to insure feasibility and precision. This is the main objective of the algorithm presented in this paper. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six-degrees-of freedom and one is minimally actuated with control motions in the vertical plane only.

Morphological design control for large-scale city development : a new proposal

Whereas many good examples can be found of the study of urban morphology informing the design of new residential areas in Europe, it is much more difficult to find examples relating to other land uses and outside of Europe. This paper addresses a particular issue, the control and coordination of large and complex development schemes within cities, and, in doing so, considers commercial and mixed-use schemes outside of Europe. It is argued that urban morphology has much to offer for both the design of such development and its implementation over time. Firstly, lessons are drawn from the work of Krier and Rossi in Berlin, the form-based guidance developed in Chelmsford, UK, and the redesign and coordination of the Melrose Arch project in Johannesburg, SA. A recent development at Boggo Road in Brisbane, Australia, is then subjected to a more detailed examination. It is argued that the scheme has been unsatisfactory in terms of both design and implementation. An alternative framework based on historical morphological studies is proposed that would overcome these deficiencies. It is proposed that this points the way to a general approach that could be incorporated within the planning process internationally.

A tutorial on visual servo control

This article provides a tutorial introduction to visual servo control of robotic manipulators. Since the topic spans many disciplines our goal is limited to providing a basic conceptual framework. We begin by reviewing the prerequisite topics from robotics and computer vision, including a brief review of coordinate transformations, velocity representation, and a description of the geometric aspects of the image formation process. We then present a taxonomy of visual servo control systems. The two major classes of systems, position-based and image-based systems, are then discussed in detail. Since any visual servo system must be capable of tracking image features in a sequence of images, we also include an overview of feature-based and correlation-based methods for tracking. We conclude the tutorial with a number of observations on the current directions of the research field of visual servo control.

Do balanced skills help nascent entrepreneurs to make progress in the venture creation process?

We analyze longitudinal data on innovative start-up projects and apply Lazear’s jack-of-all-trades theory to investigate the effect of nascent entrepreneurs’ balanced skills on their progress in the venture creation process. Our results suggest that those nascent entrepreneurs who exhibit a sufficiently broad set of skills undertake more gestation activities towards an operational new venture. This supports the notion that a balanced skill set is an important determinant of entrepreneurial market entry.

See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.

Control and application of minimally-actuated underwater vehicles

Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats. With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.