Advanced instrumentation concepts for environmental control subsystems

Design, evaluation and demonstration of advanced instrumentation concepts for improving performance of manned spacecraft environmental control and life support systems were successfully completed. Concepts to aid maintenance following fault detection and isolation were defined. A computer-guided fault correction instruction program was developed and demonstrated in a packaged unit which also contains the operator/system interface

Computer- and robot-assisted Medical Intervention

Medical robotics includes assistive devices used by the physician in order to make his/her diagnostic or therapeutic practices easier and more efficient. This chapter focuses on such systems. It introduces the general field of Computer-Assisted Medical Interventions, its aims, its different components and describes the place of robots in that context. The evolutions in terms of general design and control paradigms in the development of medical robots are presented and issues specific to that application domain are discussed. A view of existing systems, on-going developments and future trends is given. A case-study is detailed. Other types of robotic help in the medical environment (such as for assisting a handicapped person, for rehabilitation of a patient or for replacement of some damaged/suppressed limbs or organs) are out of the scope of this chapter.Comment: Handbook of Automation, Shimon Nof (Ed.) (2009) 000-00

A System for Real-Time Interactive Analysis of Deep Learning Training

Performing diagnosis or exploratory analysis during the training of deep learning models is challenging but often necessary for making a sequence of decisions guided by the incremental observations. Currently available systems for this purpose are limited to monitoring only the logged data that must be specified before the training process starts. Each time a new information is desired, a cycle of stop-change-restart is required in the training process. These limitations make interactive exploration and diagnosis tasks difficult, imposing long tedious iterations during the model development. We present a new system that enables users to perform interactive queries on live processes generating real-time information that can be rendered in multiple formats on multiple surfaces in the form of several desired visualizations simultaneously. To achieve this, we model various exploratory inspection and diagnostic tasks for deep learning training processes as specifications for streams using a map-reduce paradigm with which many data scientists are already familiar. Our design achieves generality and extensibility by defining composable primitives which is a fundamentally different approach than is used by currently available systems. The open source implementation of our system is available as TensorWatch project at https://github.com/microsoft/tensorwatch.Comment: Accepted at ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2019). Code available as TensorWatch project at https://github.com/microsoft/tensorwatc

Focal Spot, Fall/Winter 2010/2011

https://digitalcommons.wustl.edu/focal_spot_archives/1115/thumbnail.jp

MISSED: an environment for mixed-signal microsystem testing and diagnosis

A tight link between design and test data is proposed for speeding up test-pattern generation and diagnosis during mixed-signal prototype verification. Test requirements are already incorporated at the behavioral level and specified with increased detail at lower hierarchical levels. A strict distinction between generic routines and implementation data makes reuse of software possible. A testability-analysis tool and test and DFT libraries support the designer to guarantee testability. Hierarchical backtrace procedures in combination with an expert system and fault libraries assist the designer during mixed-signal chip debuggin

Medical image computing and computer-aided medical interventions applied to soft tissues. Work in progress in urology

Until recently, Computer-Aided Medical Interventions (CAMI) and Medical Robotics have focused on rigid and non deformable anatomical structures. Nowadays, special attention is paid to soft tissues, raising complex issues due to their mobility and deformation. Mini-invasive digestive surgery was probably one of the first fields where soft tissues were handled through the development of simulators, tracking of anatomical structures and specific assistance robots. However, other clinical domains, for instance urology, are concerned. Indeed, laparoscopic surgery, new tumour destruction techniques (e.g. HIFU, radiofrequency, or cryoablation), increasingly early detection of cancer, and use of interventional and diagnostic imaging modalities, recently opened new challenges to the urologist and scientists involved in CAMI. This resulted in the last five years in a very significant increase of research and developments of computer-aided urology systems. In this paper, we propose a description of the main problems related to computer-aided diagnostic and therapy of soft tissues and give a survey of the different types of assistance offered to the urologist: robotization, image fusion, surgical navigation. Both research projects and operational industrial systems are discussed