The Generic Spacecraft Analyst Assistant (gensaa): a Tool for Developing Graphical Expert Systems

During numerous contacts with a satellite each day, spacecraft analysts must closely monitor real-time data. The analysts must watch for combinations of telemetry parameter values, trends, and other indications that may signify a problem or failure. As the satellites become more complex and the number of data items increases, this task is becoming increasingly difficult for humans to perform at acceptable performance levels. At NASA GSFC, fault-isolation expert systems are in operation supporting this data monitoring task. Based on the lessons learned during these initial efforts in expert system automation, a new domain-specific expert system development tool named the Generic Spacecraft Analyst Assistant (GenSAA) is being developed to facilitate the rapid development and reuse of real-time expert systems to serve as fault-isolation assistants for spacecraft analysts. Although initially domain-specific in nature, this powerful tool will readily support the development of highly graphical expert systems for data monitoring purposes throughout the space and commercial industry

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Silicon compilation

Silicon compilation is a term used for many different purposes. In this paper we define silicon compilation as a mapping from some higher level description into layout. We define the basic issues in structural and behavioral silicon compilation and some possible solutions to those issues. Finally, we define the concept of an intelligent silicon compiler in which the compiler evaluates the quality of the generated design and attempts to improve it if it is not satisfactory

The Family of MapReduce and Large Scale Data Processing Systems

In the last two decades, the continuous increase of computational power has produced an overwhelming flow of data which has called for a paradigm shift in the computing architecture and large scale data processing mechanisms. MapReduce is a simple and powerful programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. It isolates the application from the details of running a distributed program such as issues on data distribution, scheduling and fault tolerance. However, the original implementation of the MapReduce framework had some limitations that have been tackled by many research efforts in several followup works after its introduction. This article provides a comprehensive survey for a family of approaches and mechanisms of large scale data processing mechanisms that have been implemented based on the original idea of the MapReduce framework and are currently gaining a lot of momentum in both research and industrial communities. We also cover a set of introduced systems that have been implemented to provide declarative programming interfaces on top of the MapReduce framework. In addition, we review several large scale data processing systems that resemble some of the ideas of the MapReduce framework for different purposes and application scenarios. Finally, we discuss some of the future research directions for implementing the next generation of MapReduce-like solutions.Comment: arXiv admin note: text overlap with arXiv:1105.4252 by other author

An analysis of the application of AI to the development of intelligent aids for flight crew tasks

This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research

Deliverable DJRA1.2. Solutions and protocols proposal for the network control, management and monitoring in a virtualized network context

This deliverable presents several research proposals for the FEDERICA network, in different subjects, such as monitoring, routing, signalling, resource discovery, and isolation. For each topic one or more possible solutions are elaborated, explaining the background, functioning and the implications of the proposed solutions.This deliverable goes further on the research aspects within FEDERICA. First of all the architecture of the control plane for the FEDERICA infrastructure will be defined. Several possibilities could be implemented, using the basic FEDERICA infrastructure as a starting point. The focus on this document is the intra-domain aspects of the control plane and their properties. Also some inter-domain aspects are addressed. The main objective of this deliverable is to lay great stress on creating and implementing the prototype/tool for the FEDERICA slice-oriented control system using the appropriate framework. This deliverable goes deeply into the definition of the containers between entities and their syntax, preparing this tool for the future implementation of any kind of algorithm related to the control plane, for both to apply UPB policies or to configure it by hand. We opt for an open solution despite the real time limitations that we could have (for instance, opening web services connexions or applying fast recovering mechanisms). The application being developed is the central element in the control plane, and additional features must be added to this application. This control plane, from the functionality point of view, is composed by several procedures that provide a reliable application and that include some mechanisms or algorithms to be able to discover and assign resources to the user. To achieve this, several topics must be researched in order to propose new protocols for the virtual infrastructure. The topics and necessary features covered in this document include resource discovery, resource allocation, signalling, routing, isolation and monitoring. All these topics must be researched in order to find a good solution for the FEDERICA network. Some of these algorithms have started to be analyzed and will be expanded in the next deliverable. Current standardization and existing solutions have been investigated in order to find a good solution for FEDERICA. Resource discovery is an important issue within the FEDERICA network, as manual resource discovery is no option, due to scalability requirement. Furthermore, no standardization exists, so knowledge must be obtained from related work. Ideally, the proposed solutions for these topics should not only be adequate specifically for this infrastructure, but could also be applied to other virtualized networks.Postprint (published version

The Faculty Notebook, September 2015

The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost