Human Factors Engineering Requirements for the International Space Station - Successes and Challenges

Advanced technology coupled with the desire to explore space has resulted in increasingly longer human space missions. Indeed, any exploration mission outside of Earth's neighborhood, in other words, beyond the moon, will necessarily be several months or even years. The International Space Station (ISS) serves as an important advancement toward executing a successful human space mission that is longer than a standard trip around the world or to the moon. The ISS, which is a permanently occupied microgravity research facility orbiting the earth, will support missions four to six months in duration. In planning for the ISS, the NASA developed an agency-wide set of human factors standards for the first time in a space exploration program. The Man-Systems Integration Standard (MSIS), NASA-STD-3000, a multi-volume set of guidelines for human-centered design in microgravity, was developed with the cooperation of human factors experts from various NASA centers, industry, academia, and other government agencies. The ISS program formed a human factors team analogous to any major engineering subsystem. This team develops and maintains the human factors requirements regarding end-to-end architecture design and performance, hardware and software design requirements, and test and verification requirements. It is also responsible for providing program integration across all of the larger scale elements, smaller scale hardware, and international partners

Embedding object-oriented design in system engineering

The Unified Modeling Language (UML) is a collection of techniques intended to document design decisions about software. This contrasts with systems engineering approaches such as for exampleStatemate and the Yourdon Systems Method (YSM), in which the design of an entire system consisting of software and hardware can be documented. The difference between the system- and the software level is reflected in differences between execution semantics as well as in methodology. In this paper, I show how the UML can be used as a system-level design technique. I give a conceptual framework for engineering design that accommodates the system- as well as the software level and show how techniques from the UML and YSM can be classified within this framework, and how this allows a coherent use of these techniques in a system engineering approach. These ideas are illustrated by a case study in which software for a compact dynamic bus station is designed. Finally, I discuss the consequences of this approach for a semantics of UML constructs that would be appropriate for system-level design

Assessing the energy implications of replacing car trips with bicycle trips in Sheffield, UK

A wide range of evidence supports policies which encourage people to cycle more and drive less, for health and environmental reasons. However, the likely energy implications of such a modal shift have remained relatively unexplored. In this paper we generate scenarios for increasing the cycling rate in Sheffield between 2010 and 2020. This is done through the novel application of a simple model, borrowed from population ecology. The analysis suggests that pro-cycling interventions result in energy savings through reduced consumption of fuel and cars, and energy costs through increased demand for food. The cumulative impact is a net reduction in primary energy consumption, the magnitude of which depends on a number of variables which are subject to uncertainty. Based on the evidence presented and analysed in this paper, we conclude that transport policy has a number of important energy implications, some of which remain unexplored. We therefore advocate the formation of closer links between energy policy and transport policy in academia and in practice; our approach provides a simple yet flexible framework for pursuing this aim in the context of modal shift

Transitioning Applications to Semantic Web Services: An Automated Formal Approach

Semantic Web Services have been recognized as a promising technology that exhibits huge commercial potential, and attract significant attention from both industry and the research community. Despite expectations being high, the industrial take-up of Semantic Web Service technologies has been slower than expected. One of the main reasons is that many systems have been developed without considering the potential of the web in integrating services and sharing resources. Without a systematic methodology and proper tool support, the migration from legacy systems to Semantic Web Service-based systems can be a very tedious and expensive process, which carries a definite risk of failure. There is an urgent need to provide strategies which allow the migration of legacy systems to Semantic Web Services platforms, and also tools to support such a strategy. In this paper we propose a methodology for transitioning these applications to Semantic Web Services by taking the advantage of rigorous mathematical methods. Our methodology allows users to migrate their applications to Semantic Web Services platform automatically or semi-automatically

ACon: A learning-based approach to deal with uncertainty in contextual requirements at runtime

Context: Runtime uncertainty such as unpredictable operational environment and failure of sensors that gather environmental data is a well-known challenge for adaptive systems. Objective: To execute requirements that depend on context correctly, the system needs up-to-date knowledge about the context relevant to such requirements. Techniques to cope with uncertainty in contextual requirements are currently underrepresented. In this paper we present ACon (Adaptation of Contextual requirements), a data-mining approach to deal with runtime uncertainty affecting contextual requirements. Method: ACon uses feedback loops to maintain up-to-date knowledge about contextual requirements based on current context information in which contextual requirements are valid at runtime. Upon detecting that contextual requirements are affected by runtime uncertainty, ACon analyses and mines contextual data, to (re-)operationalize context and therefore update the information about contextual requirements. Results: We evaluate ACon in an empirical study of an activity scheduling system used by a crew of 4 rowers in a wild and unpredictable environment using a complex monitoring infrastructure. Our study focused on evaluating the data mining part of ACon and analysed the sensor data collected onboard from 46 sensors and 90,748 measurements per sensor. Conclusion: ACon is an important step in dealing with uncertainty affecting contextual requirements at runtime while considering end-user interaction. ACon supports systems in analysing the environment to adapt contextual requirements and complements existing requirements monitoring approaches by keeping the requirements monitoring specification up-to-date. Consequently, it avoids manual analysis that is usually costly in today’s complex system environments.Peer ReviewedPostprint (author's final draft

Application of Advanced Early Warning Systems with Adaptive Protection

This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers