Gaussian process models for sensor-centric robot localisation

This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment

The development of a conceptual framework for a district 4-Year Pavement Management Plan, implementation of network-level project screening process

The Texas Department of Transportation (TxDOT) is concerned about the widening gap between preservation needs and available funding. Funding levels are not adequate to meet the preservation needs of the roadway network; therefore projects listed in the 4-Year Pavement Management Plan must be ranked to determine which projects should be funded now and which can be postponed until a later year. Currently, each district uses locally developed methods to prioritize projects. These ranking methods have relied on less formal qualitative assessments based on engineers’ subjective judgment. It is important for TxDOT to have a 4-Year Pavement Management Plan that uses a transparent, rational project ranking process. The objective of this study is to develop a conceptual framework that describes the development of the 4-Year Pavement Management Plan. It can be largely divided into three Steps; 1) Network-Level project screening process, 2) Project-Level project ranking process, and 3) Economic Analysis. A rational pavement management procedure and a project ranking method accepted by districts and the TxDOT administration will maximize efficiency in budget allocations and will potentially help improve pavement condition. As a part of the implementation of the 4-Year Pavement Management Plan, the Network-Level Project Screening (NLPS) tool including the candidate project identification algorithm and the preliminary project ranking matrix was developed. The NLPS has been used by the Austin District Pavement Engineer (DPE) to evaluate PMIS (Pavement Management Information System) data and to prepare a preliminary list of candidate projects for further evaluation.

A process evaluation of a comprehensive school based injury prevention program

A process evaluation enables understanding of critical issues that can inform the improved, ongoing implementation of an intervention program. This study describes the process evaluation of a comprehensive, multi-level injury prevention program for adolescents. The program targets change in injury associated with violence, transport and alcohol risks and incorporates two primary elements: an 8-week, teacher delivered attitude and behaviour change curriculum for Grade 8 students; and a professional development program for teachers on school level methods of protection, focusing on strategies to increase students’ connectedness to school.

A sequence analytic model of entrepreneurial discovery and exploitation process

This study examined the effect that temporal order within the entrepreneurial discovery exploitation process has on the outcomes of venture creation. Consistent with sequential theories of discovery-exploitation, the general flow of venture creation was found to be directed from discovery toward exploitation in a random sample of nascent ventures. However, venture creation attempts which specifically follow this sequence derive poor outcomes. Moreover, simultaneous discovery-exploitation was the most prevalent temporal order observed, and venture attempts that proceed in this manner more likely become operational. These findings suggest that venture creation is a multi-scale phenomenon that is at once directional in time, and simultaneously driven by symbiotically coupled discovery and exploitation.

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

We apply Lazear’s jack-of-all-trades theory to investigate the effect of nascent entrepreneurs´ balanced skill set across various functional areas on the performance of nascent projects. Analyzing longitudinal data on innovative nascent projects, we find that nascent entrepreneurs with a more balanced skill set are more successful in that they progress faster in the venture creation process.

Context-aware methods for process modeling

Recent studies have started to explore context-awareness as a driver in the design of adaptable business processes. The emerging challenge of identifying and considering contextual drivers in the environment of a business process are well understood, however, typical methods used in business process modeling do not yet consider this additional contextual information in their process designs. In this chapter, we describe our research towards innovative and advanced process modeling methods that include mechanisms to incorporate relevant contextual drivers and their impacts on business processes in process design models. We report on our ongoing work with an Australian insurance provider and describe the design science we employed to develop these innovative and useful artifacts as part of a context-aware method framework. We discuss the utility of these artifacts in an application in the claims handling process at the case organization.

Vibrational spectroscopy and solubility study of the mineral stringhamite CaCuSiO4•H2O

Stringhamite CaCuSiO4·H2O is a hydrated calcium copper silicate and is commonly known as a significant ‘healing’ mineral and is potentially a semi-precious jewel. Stringhamite is a neosilicate with Cu2+ in square planar coordination. Vibrational spectroscopy has been used to characterise the molecular structure of stringhamite. The intense sharp Raman band at 956 cm−1 is assigned to the ν1 (A1g) symmetric stretching vibration. Raman bands at 980, 997, 1061 cm−1 are assigned to the ν3 (A2u, B1g) antisymmetric stretching vibrations. Splitting of the ν3 vibrational mode supports the concept that the stringhamite SiO4 tetrahedron is strongly distorted. The intense bands at 505 and 519 cm−1 and at 570 cm−1 are assigned to the ν2 and ν4 vibrational modes. The question arises as to whether the mineral stringhamite can actually function as a healing mineral. An estimation of the solubility product at pH < 5 shows that the cupric ion can be released. The copper ion is a very powerful antibiological agent and thus the mineral stringhamite may well function as a healing mineral.

Whelanite Ca5Cu2(OH)2CO3,Si6O17•4H2O – A vibrational spectroscopic study

Whelanite Ca5Cu2(OH)2CO3,Si6O17•4H2O is a hydrated hydroxy mixed anion compound with both silicate and carbonate anions in the formula. The structural characterisation of the mineral whelanite remains incomplete. Whelanite is probably a neosilicate with Cu2+ in square planar coordination. Two Raman bands at 1070 and 1094 cm-1 are assigned to the ν1 symmetric stretching modes of the CO32- units. The observation of two symmetric stretching modes supports the concept of two non-equivalent CO32- units in the whelanite structure. The intense sharp Raman band at 1006 cm-1 is assigned to the ν1 (A1g) symmetric stretching vibration of the Si6O17 units. The splitting of the ν3 vibrational mode offers support to the concept that the SiO4 tetrahedron in whelanite is strongly distorted. A very intense Raman band observed at 666 cm-1 with a shoulder at 697 cm-1 is assigned to the ν4 vibrational modes. Intense Raman bands at 3534, 3556, 3550 and 3595 cm-1 are assigned to the stretching vibrations of the OH units. Low intensity Raman bands at 2910, 3187 and 3453 cm-1 are assigned to water stretching modes. Thus, vibrational spectroscopy has been used to characterise the molecular structure of whelanite. Whelanite is a mineral that could be conceived as a healing mineral

A vibrational spectroscopic study of planchéite Cu8Si8O22(OH)4•H2O

Planchéite Cu8Si8O22(OH)4•H2O is a hydrated copper hydroxy silicate. The objective of this work is to use Raman and infrared spectroscopy to determine the molecular structure of planchéite. Raman bands of planchéite at around 1048, 1081 and 1127 are described as the ν1 –SiO3 symmetric stretching vibrations; Raman bands at 828, 906 are attributed to the ν3 –SiO3 antisymmetric stretching vibrations. The Raman band at 699 cm-1 is assigned to the ν4 bending modes of the -SiO3 units. The intense Raman band at 3479 cm-1 is ascribed to the stretching vibration of the OH units. The Raman band at 3250 cm-1 is evidence for water in the structure. A comparison of the spectra of planchéite with that of shattuckite and chrysocolla.

Research process management

Though the value of a process-centred view for the understanding and (re-)design of corporations has been widely accepted, our understanding of the research process in Information Systems (IS) remains superficial. A process-centred view on IS research considers the conduct of a research project as a sequence of activities involving resources, data and research artifacts. As such, it helps to reflect on more effective ways to conduct IS research, to consolidate and compare diverse practices and to complement the focus on research methodologies with research project practices. This paper takes a first step towards the discipline of ‘Research Process Management’ by exploring the features of research processes and by presenting a preliminary approach for research process design that can facilitate modelling IS research. The case study method and the design science research method are used as examples to demonstrate the potential of such reference research process models.

The internetalisation of information, knowledge and interaction components of the firm’s internationalisation process

Transcending traditional national borders, the Internet is an evolving technology that has opened up many new international market opportunities. However, ambiguity remains, with limited research and understanding of how the Internet influences the firm’s internationalisation process components. As a consequence, there has been a call for further investigation of the phenomenon. Thus, the purpose of this study was to investigate the Internet’s impact on the internationalisation process components, specifically, information availability, information usage, interactive communication and international market growth. Analysis was undertaken using structural equation modelling. Findings highlight the mediating impact of the Internet on information and knowledge transference in the internationalisation process. Contributions of the study test conceptualisations and give statistical validation of interrelationships, while illuminating the Internet’s impact on firm internationalisation.

A Bayesian‐Markov process for reliability prediction

Accurate reliability prediction for large-scale, long lived engineering is a crucial foundation for effective asset risk management and optimal maintenance decision making. However, a lack of failure data for assets that fail infrequently, and changing operational conditions over long periods of time, make accurate reliability prediction for such assets very challenging. To address this issue, we present a Bayesian-Marko best approach to reliability prediction using prior knowledge and condition monitoring data. In this approach, the Bayesian theory is used to incorporate prior information about failure probabilities and current information about asset health to make statistical inferences, while Markov chains are used to update and predict the health of assets based on condition monitoring data. The prior information can be supplied by domain experts, extracted from previous comparable cases or derived from basic engineering principles. Our approach differs from existing hybrid Bayesian models which are normally used to update the parameter estimation of a given distribution such as the Weibull-Bayesian distribution or the transition probabilities of a Markov chain. Instead, our new approach can be used to update predictions of failure probabilities when failure data are sparse or nonexistent, as is often the case for large-scale long-lived engineering assets.

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.

Approximate clone detection in repositories of business process models

Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.

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.