134 research outputs found
An architecture for intelligent health assessment enabled IEEE 1451 compliant smart sensors
As systems become increasingly complex and costly, potential failure mechanisms and indicators are numerous and difficult to identify, while the cost of loss is very expensive - human lives, replacement units, and impacts to national security. In order to ensure the safety and long-term reliability of vehicles, structures, and devices attention must be directed toward the assessment and management of system health. System health is the key component that links data, information, and knowledge to action. Integrated Systems Health Management (ISHM) doctrine calls for comprehensive real-time health assessment and management of systems where the distillation of raw data into information takes place within sensors and actuators. This thesis develops novel field programmable health assessment capability for sensors and actuators in ISHM. Health assessment and feature extraction algorithms are implemented on a sensor or actuator through the Embedded Routine Manager (ERM) API. Algorithms are described using Health Electronic Datasheets (HEDS) to provide more flexible run-time operation. Interfacing is accomplished through IEEE Standard 1451 for Smart Sensors and Actuators, connecting ISHM with the instrumentation network of the future. These key elements are validated using exemplar algorithms to detect noise, spike, and flat-line events onboard the ISHM enabled Methane Thruster Testbed Project (MTTP) at NASA Stennis Space Center in Mississippi
The distributed ASCI supercomputer project
The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project
Compiler Support for Sparse Tensor Computations in MLIR
Sparse tensors arise in problems in science, engineering, machine learning,
and data analytics. Programs that operate on such tensors can exploit sparsity
to reduce storage requirements and computational time. Developing and
maintaining sparse software by hand, however, is a complex and error-prone
task. Therefore, we propose treating sparsity as a property of tensors, not a
tedious implementation task, and letting a sparse compiler generate sparse code
automatically from a sparsity-agnostic definition of the computation. This
paper discusses integrating this idea into MLIR
Acute Myeloid Leukemia
Acute myeloid leukemia (AML) is the most common type of leukemia. The Cancer Genome Atlas Research Network has demonstrated the increasing genomic complexity of acute myeloid leukemia (AML). In addition, the network has facilitated our understanding of the molecular events leading to this deadly form of malignancy for which the prognosis has not improved over past decades. AML is a highly heterogeneous disease, and cytogenetics and molecular analysis of the various chromosome aberrations including deletions, duplications, aneuploidy, balanced reciprocal translocations and fusion of transcription factor genes and tyrosine kinases has led to better understanding and identification of subgroups of AML with different prognoses. Furthermore, molecular classification based on mRNA expression profiling has facilitated identification of novel subclasses and defined high-, poor-risk AML based on specific molecular signatures. However, despite increased understanding of AML genetics, the outcome for AML patients whose number is likely to rise as the population ages, has not changed significantly. Until it does, further investigation of the genomic complexity of the disease and advances in drug development are needed. In this review, leading AML clinicians and research investigators provide an up-to-date understanding of the molecular biology of the disease addressing advances in diagnosis, classification, prognostication and therapeutic strategies that may have significant promise and impact on overall patient survival
Code-Optimierung im Polyedermodell - Effizienzsteigerung von parallelen Schleifensätzen
A safe basis for automatic loop parallelization is the polyhedron model which represents the iteration domain of a loop nest as a polyhedron in . However, turning the parallel loop program in the model to efficient code meets with several obstacles, due to which performance may deteriorate seriously -- especially on distributed memory architectures. We introduce a fine-grained model of the computation performed and show how this model can be applied to create efficient code
The first ICASE/LARC industry roundtable: Session proceedings
The first 'ICASE/LaRC Industry Roundtable' was held on October 3-4, 1994, in Williamsburg, Virginia. The main purpose of the roundtable was to draw attention of ICASE/LaRC scientists to industrial research agendas. The roundtable was attended by about 200 scientists, 30% from NASA Langley; 20% from universities; 17% NASA Langley contractors (including ICASE personnel); and the remainder from federal agencies other than NASA Langley. The technical areas covered reflected the major research programs in ICASE and closely associated NASA branches. About 80% of the speakers were from industry. This report is a compilation of the session summaries prepared by the session chairmen
Polymeric Carbon Nanocomposites - Preparation, Characterization, and Properties
Excellent thermal properties of carbon nanomaterials such as carbon nanotubes and newly discovered graphene make them the filler of choice for the development of thermal management materials. Graphene has been viewed as “ unrolled single-walled carbon nanotube and as a wonder material with many superlatives to its name ” thus there is an excessive interest in developing new synthetic routes towards large scale production of high quality graphene nanosheets. In this dissertation, we report different methods that could further exfoliate the commercially available expanded graphite to nanometer sized carbon structures, “carbon nanosheets ”, for their use in highly thermal conductive polymeric nanocomposites. Initially, an overview of recent advances in the development of thermal conductive polymeric/carbon nanocomposites is provided. Then, the “ carbon nanosheets ” from the specific processes will carefully be characterized by spectroscopic techniques and the effectiveness of the processing methods is demonstrated in terms of polymeric carbon nanocomposites thermal diffusivity. While the focus of this manuscript will be on the enhancement of thermal diffusivity we will also discuss the chemical modification and functionalization of these “ carbon nanosheets ” with matrix polymer. Finally, the critical research opportunities and challenges in the development of functional graphene nanocomposites for thermal management materials will be discussed
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