A multi-layered risk estimation routine for strategic planning and operations for the maritime industry

Maritime regulators and port authorities require the ability to predict risk exposure for strategic planning aspects to optimize asset allocation, mitigate and prevent incidents. This article builds on previous work to develop the strategic planning component and introduces the concept of a multilayered risk estimation framework (MLREF) for strategic planning and operations. The framework accounts for most of the risk factors such as ship specific risk, vessel traffic densities and met ocean conditions and allows the integration of the effect of risk control option and a location specific spatial rate ratio to allow for micro level risk assessments. Both, the macro (eg. covering larger geographic areas or EEZ) and micro level application (eg. passage way, particular route of interest) of MLREF was tested via a pilot study for the Australian region using a comprehensive and unique combination of dataset. The underlying routine towards the development of a strategic planning tool was developed and tested in R. Applications of the layers for the operational part such as an automated alert system and sources of uncertainties for risk assessments in general are described and discussed along with future developments and improvements

A multi-layered risk exposure assessment approach for the shipping industry

__Abstract__ Shipping activity has increased worldwide and maritime administrations are trying to enhance risk mitigation strategies by using proactive approaches. We present and discuss a conceptual framework to minimize potential harm based on a multi-layered approach which can be implemented in either real time for operational purposes or in prediction mode for medium or longer term strategic planning purposes. We introduce the concept of total risk exposure which integrates risk at the individual ship level with vessel traffic densities and location specific parameters such as weather and oceanographic conditions, geographical features or environmental sensitivities. A comprehensive and robust method to estimate and predict risk exposure can be beneficial to maritime administrations to enhance mitigation strategies and understand uncertainties. We further provide a proof of concept based on 53 million observations of vessel positions and individual risk profiles of 8,900 individual ships. We present examples on how endpoints can be visualized for two integrated risk layers – ship specific risk and vessel traffic densities. We further identify and discuss uncertainties and present our ideas on how other risk layers could be integrated in the future

The Media Inequality, Uncanny Mountain, and the Singularity is Far from Near: Iwaa and Sophia Robot versus a Real Human Being

Design of Artificial Intelligence and robotics habitually assumes that adding more humanlike features improves the user experience, mainly kept in check by suspicion of uncanny effects. Three strands of theorizing are brought together for the first time and empirically put to the test: Media Equation (and in its wake, Computers Are Social Actors), Uncanny Valley theory, and as an extreme of human-likeness assumptions, the Singularity. We measured the user experience of real-life visitors of a number of seminars who were checked in either by Smart Dynamics' Iwaa, Hanson's Sophia robot, Sophia's on-screen avatar, or a human assistant. Results showed that human-likeness was not in appearance or behavior but in attributed qualities of being alive. Media Equation, Singularity, and Uncanny hypotheses were not confirmed. We discuss the imprecision in theorizing about human-likeness and rather opt for machines that 'function adequately.

Drawing out critical conversations in the management classroom

Arts-based methods are of increasing interest to management educators and this activity can be used to support a community of inquiry in the virtual classroom. The activity commences by asking students to draw (using no words!) a managerial or workplace experience. Students then explain their drawing to a peer. The educator-led debrief focuses on disclosing the subjectivity of experience and then triggering a reflection of the cohort’s narratives against management theory. This thirty-minute activity, designed to initiate discussion of challenging aspects of management practice, cultivates social presence in the management classroom and reveals the subjectivity of organizational life

A 'lived experienced’ tool for managing and building project delivery capability

This paper discusses a new, integrated tool-set for project managing. This tool-set is a response to calls for project managers to be able to apply new project managing thinking ‘in practice’. The tool-set integrates the project-space model and the Syllk model. Together, they bring visibility to enablers and constraints to project delivery capability, and these learnings can then be integrated into the organisation’s systems to build in a tailored manner ongoing project management capability. Specifically, the tool-set highlights the hindrances to project delivery and what capabilities need to be ‘wired’ into an organisation to remove them. This tool-set integrates into future organisational initiatives the learnings from concrete ‘lived experiences’ of project managing

On the evolution of decoys in plant immune systems

The Guard-Guardee model for plant immunity describes how resistance proteins (guards) in host cells monitor host target proteins (guardees) that are manipulated by pathogen effector proteins. A recently suggested extension of this model includes decoys, which are duplicated copies of guardee proteins, and which have the sole function to attract the effector and, when modified by the effector, trigger the plant immune response. Here we present a proof-of-principle model for the functioning of decoys in plant immunity, quantitatively developing this experimentally-derived concept. Our model links the basic cellular chemistry to the outcomes of pathogen infection and resulting fitness costs for the host. In particular, the model allows identification of conditions under which it is optimal for decoys to act as triggers for the plant immune response, and of conditions under which it is optimal for decoys to act as sinks that bind the pathogen effectors but do not trigger an immune response.Comment: 15 pages, 6 figure

A critical evaluation of spectrum-based fault localization techniques on a large-scale software system

In the past, spectrum-based fault localization (SBFL) techniques have been developed to pinpoint a fault location in a program given a set of failing and successful test executions. Most of the algorithms use similarity coefficients and have only been evaluated on established but small benchmark programs from the Software-artifact Infrastructure Repository (SIR). In this paper, we evaluate the feasibility of applying 33 state-of-the-art SBFL techniques to a large real-world project, namely ASPECTJ. From an initial set of 350 faulty version from the iBugs repository of ASPECTJ we manually classified 88 bugs where SBFL techniques are suitable. Notably, only 11 bugs of these bugs can be found after examining the 1000 most suspicious lines and on average 250 source code files need to be inspected per bug. Based on these results, the study showcases the limitations of current SBFL techniques on a larger program

Patient-relevant health outcomes for von Willebrand disease, platelet function disorders, and rare bleeding disorders:a Delphi study

Background: To assess patient value, it is essential to regularly measure health outcomes that matter to patients. It is currently unknown which health outcomes are important for patients with autosomal inherited bleeding disorders. Objectives: This study aimed to assess which health outcomes are important for patients with autosomal inherited bleeding disorders, consisting of von Willebrand disease, platelet function disorders, and rare bleeding disorders, as seen from the patients’, caregivers’, and healthcare professionals’ perspectives. Methods: Two panels, one consisting of patients and caregivers, and one consisting of healthcare professionals participated in a Delphi process. A list of 146 health outcomes was identified from the literature. During 3 rounds, both panels rated the importance of health outcomes on a 5-point Likert scale. A health outcome was considered important by a panel if it received a median score of 5 with an IQR of ≤1. Results: In total, 13 patients, 10 caregivers, and 19 healthcare professionals participated in the Delphi study. Both panels reached consensus on the importance of health outcomes related to bleeding episodes, life-threatening complications, and the intensity and impact of menstruation. Patients and caregivers additionally reached consensus on the importance of health outcomes related to menstruation and the impact of the bleeding disorder on their daily lives. Healthcare professionals reached consensus on the importance of health outcomes related to treatment, joint health, and pain. Conclusion: In this study, health outcomes were identified that should be considered when implementing value-based health care in the care of patients with autosomal inherited bleeding disorders.</p

Predicting traffic and risk exposure in the maritime industry

Maritime regulators, port authorities, and industry require the ability to predict risk exposure of shipping activities at a micro and macro level to optimize asset allocation and to mitigate and prevent incidents. This article introduces the concept of a strategic planning tool by making use of the multi-layered risk estimation framework (MLREF), which accounts for ship specific risk, vessel traffic densities, and meets ocean conditions at the macro level. This article’s main contribution is to provide a traffic and risk exposure prediction routine that allows the traffic forecast to be distributed across the shipping route network to allow for predicting scenarios at the macro level (e.g., covering larger geographic areas) and micro level (e.g., passage way, particular route of interest). In addition, the micro level is introduced by providing a theoretical idea to integrate location specific spatial rate ratios along with the effect of the risk control option to perform sensitivity analysis of risk exposure prediction scenarios. Aspects of the risk exposure estimation routine were tested via a pilot study for the Australian region using a comprehensive and unique combination of datasets. Sources of uncertainties for risk assessments are described in general and discussed along with the potential for future developments and improvements