228,077 research outputs found

    Reliability, Safety and Error Recovery for Advanced Control Software

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    For long-duration automated operation of regenerative life support systems in space environments, there is a need for advanced integration and control systems that are significantly more reliable and safe, and that support error recovery and minimization of operational failures. This presentation outlines some challenges of hazardous space environments and complex system interactions that can lead to system accidents. It discusses approaches to hazard analysis and error recovery for control software and challenges of supporting effective intervention by safety software and the crew

    Automation of closed environments in space for human comfort and safety

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    The development of Environmental Control and Life Support Systems (ECLSS) for Space Station Freedom, future colonization of the Moon, and Mars missions presents new challenges for present technologies. ECLSS that operate during long-duration missions must be semi-autonomous to allow crew members environmental control without constant supervision. A control system for the ECLSS must address these issues as well as being reliable. The Kansas State University Advanced Design Team is in the process of researching and designing controls for the automation of the ECLSS for Space Station Freedom and beyond. The ECLSS for Freedom is composed of six subsystems. The temperature and humidity control (THC) subsystem maintains the cabin temperature and humidity at a comfortable level. The atmosphere control and supply (ACS) subsystem insures proper cabin pressure and partial pressures of oxygen and nitrogen. To protect the space station from fire damage, the fire detection and suppression (FDS) subsystem provides fire-sensing alarms and extinguishers. The waste management (WM) subsystem compacts solid wastes for return to Earth, and collects urine for water recovery. The atmosphere revitalization (AR) subsystem removes CO2 and other dangerous contaminants from the air. The water recovery and management (WRM) subsystem collects and filters condensate from the cabin to replenish potable water supplies, and processes urine and other waste waters to replenish hygiene water supplies. These subsystems are not fully automated at this time. Furthermore, the control of these subsystems is not presently integrated; they are largely independent of one another. A fully integrated and automated ECLSS would increase astronauts' productivity and contribute to their safety and comfort

    Automation of closed environments in space for human comfort and safety

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    The Environmental Control and Life Support System (ECLSS) for the Space Station Freedom and future colonization of the Moon and Mars presents new challenges for present technologies. Current plans call for a crew of 8 to live in a safe, shirt-sleeve environment for 90 days without ground support. Because of these requirements, all life support systems must be self-sufficient and reliable. The ECLSS is composed of six subsystems. The temperature and humidity control (THC) subsystem maintains the cabin temperature and humidity at a comfortable level. The atmosphere control and supply (ACS) subsystem insures proper cabin pressure and partial pressures of oxygen and nitrogen. To protect the space station from fire damage, the fire detection and suppression (FDS) subsystem provides fire sensing alarms and extinguishers. The waste management (WM) subsystem compacts solid wastes for return to Earth, and collects urine for water recovery. Because it is impractical, if not impossible, to supply the station with enough fresh air and water for the duration of the space station's extended mission, these elements are recycled. The atmosphere revitalization (AR) subsystem removes CO2 and other dangerous contaminants from the air. The water recovery and management (WRM) subsystem collects and filters condensate from the cabin to replenish potable water supplies, and processes urine and other waste waters to replenish hygiene water supplies. These subsystems are not fully automated at this time. Furthermore, the control of these subsystems is not presently integrated; they are largely independent of one another. A fully integrated and automated ECLSS would increase astronauts' productivity and contribute to their safety and comfort. The Kansas State University Advanced Design Team is in the process of researching and designing controls for the automation of the ECLSS for Space Station Freedom and beyond. The approach chosen to solve this problem is to divide the design into three phases. The first phase is to research the ECLSS as a whole system and then concentrate efforts on the automation of a single subsystem. The AR subsystem was chosen for our focus. During the second phase, the system control process will then be applied to the AR subsystem

    A Smartphone-Based Support Group for Alcoholism: Effects of Giving and Receiving Emotional Support on Coping Self-Efficacy and Risky Drinking

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    The purpose of this study was to investigate the nature and effects of exchanging emotional support via a smartphone-based support group for patients with alcohol dependence. Of the 349 patients who met the Diagnostic and Statistical Manual of Mental Disorders (4th ed.) criteria for alcohol dependence, 153 patients participated in the discussion group within the Addiction-Comprehensive Health Enhancement Support System, a smartphone application aimed at reducing relapse. This was developed to prevent problem drinking by offering individuals in recovery for alcohol dependence automated 24/7 recovery support services and frequent assessment of their symptom status as part of their addiction care. The results showed that receiving emotional support from health care providers improved coping self-efficacy. Giving emotional support and receiving emotional support from health care providers acted as a buffer, protecting patients from the harmful effects of emotional distress on risky drinking. Clinicians and researchers should use the features of smartphone-based support groups to reach out to alcoholic patients in need and encourage them to participate in the exchange of emotional support with others

    Process control and recovery in the Link Monitor and Control Operator Assistant

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    This paper describes our approach to providing process control and recovery functions in the Link Monitor and Control Operator Assistant (LMCOA). The focus of the LMCOA is to provide semi-automated monitor and control to support station operations in the Deep Space Network. The LMCOA will be demonstrated with precalibration operations for Very Long Baseline Interferometry on a 70-meter antenna. Precalibration, the task of setting up the equipment to support a communications link with a spacecraft, is a manual, time consuming and error-prone process. One problem with the current system is that it does not provide explicit feedback about the effects of control actions. The LMCOA uses a Temporal Dependency Network (TDN) to represent an end-to-end sequence of operational procedures and a Situation Manager (SM) module to provide process control, diagnosis, and recovery functions. The TDN is a directed network representing precedence, parallelism, precondition, and postcondition constraints. The SM maintains an internal model of the expected and actual states of the subsystems in order to determine if each control action executed successfully and to provide feedback to the user. The LMCOA is implemented on a NeXT workstation using Objective C, Interface Builder and the C Language Integrated Production System

    Cloud Storage and Bioinformatics in a private cloud deployment: Lessons for Data Intensive research

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    This paper describes service portability for a private cloud deployment, including a detailed case study about Cloud Storage and bioinformatics services developed as part of the Cloud Computing Adoption Framework (CCAF). Our Cloud Storage design and deployment is based on Storage Area Network (SAN) technologies, details of which include functionalities, technical implementation, architecture and user support. Experiments for data services (backup automation, data recovery and data migration) are performed and results confirm backup automation is completed swiftly and is reliable for data-intensive research. The data recovery result confirms that execution time is in proportion to quantity of recovered data, but the failure rate increases in an exponential manner. The data migration result confirms execution time is in proportion to disk volume of migrated data, but again the failure rate increases in an exponential manner. In addition, benefits of CCAF are illustrated using several bioinformatics examples such as tumour modelling, brain imaging, insulin molecules and simulations for medical training. Our Cloud Storage solution described here offers cost reduction, time-saving and user friendliness

    Adaptive Process Management in Cyber-Physical Domains

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    The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time
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