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As the capacity of hardware systems has grown and workload consolidation has taken place, the volume of performance metrics and diagnostic data streams has outscaled the capability of people to handle these systems using traditional methods. As work of different types (such as database, batch, and Web processing), each in its own monitoring silo, runs concurrently on a single image (operating system instance), both the complexity and the business consequences of a single image failure have increased. This paper presents two techniques for generating actionable information out of the overwhelming amount of performance and diagnostic data available to human analysts. Failure scoring is used to identify high-risk failure events that may be obscured in the myriad system events. This replaces human expertise in scanning tens of thousands of records per day and results in a short, prioritized list for action by systems staff. Adaptive thresholding is used to drive predictive and descriptive machine-learning-based modeling to isolate and identify misbehaving processes and transactions. The attraction of this technique is that it does not require human intervention and can be reapplied continually, resulting in models that are not brittle. Both techniques reduce the quantity and increase the relevance of data available for programmatic and human processes. [ABSTRACT FROM AUTHOR]

Abstract. We report on the fabrication process of a scanning force microscopy (SFM) cantilever probe suitable for the investigation of ultrafast transient signals in microwave integrated circuits. High temporal resolution is achieved by integrating a laser-gated photoconductive switch within a coplanar waveguide structure onto a low-temperature GaAs cantilever. This is demonstrated by temporal and spatio-temporal measurements performed on a coplanar strip line. [ABSTRACT FROM AUTHOR]

We describe recent preliminary studies demonstrating that computational analysis of spoken and written language can provide for highly accurate diagnostics over a wide variety of psychiatric and neurologic conditions, including psychosis, drug abuse, Parkinson's, and Alzheimer's. These results are based on the mathematical formalization of psychiatric qualitative knowledge related to the characterization of the conditions (e.g., "derailment" in psychosis) and drug effects (e.g., increased intimacy/affection with the use of the recreational drug ecstasy), as well as novel linguistic feature extraction approaches. Moreover, we show novel results using publicly available text sources suggesting that 1) it is possible to define an embedding space that allows modeling of the vast language dimension into a smaller space to map and compare different conditions, and 2) computational studies of a public personality (Ronald Reagan) can likely yield novel insights into normal aging and neurodegenerative disorders. Finally, we discuss the implications for mental health (and possibly, computer science) of a systematic application of this methodology, extended to include similar readily available behavioral data such as voice and video. [ABSTRACT FROM AUTHOR]

We present an application of an active emitting cantilever probe for scanning near-field optical microscopy and scanning force microscopy. A vertical cavity surface emitting laser (VCSEL) integrated in a galliumarsenide (GaAs) cantilever serves as a light source at 980 nm emission wavelength that is below the band gap energy of the GaAs substrate material. The VCSEL of 8 μm diameter is centered with respect to the metalized GaAs tip and illuminates a small near-field aperture at its apex. Aperture fabrication is accomplished by a proper thermal metal evaporation process. Optical measurements on a Fischer projection pattern revealed an edge resolution of about 80 nm. © 2000 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Abstract. Gallium arsenide is introduced as a material for the fabrication of novel probes for scanning probe microscopy (SPM). Compared to conventional probe materials (silicon, silicon nitride), III/V semiconductors such as gallium arsenide offer exceptional material properties: a direct band gap appropriate for the fabrication of optical sensors, high electron mobility necessary for high-frequency devices, and high electrical resistance exploited to reduce electrical losses in microwave guide applications. We report on novel developments in the field of gallium arsenide cantilevers with integrated tips for SPM applications. As a result of an intensive study of the gallium arsenide etching behavior we are able to adapt the tip shape to the requirements in SPM, for example, high aspect ratio, minimized radius of curvature, and low surface roughness. These cantilevers represent the basic sensor design for both passive as well as active scanning near-field probes. As a first approach, for an active SPM probe a Schottky diode integrated in the tip apex was produced. First results on the thermal and optical characterization of Schottky diode probes are presented. High-frequency measurements of a coplanar microwave guide made of semi-insulating GaAs in comparison to silicon were carried out. Additionally, concepts for a light-emitting diode and a laser diode integrated in a tip -- a challenge for future concepts in SNOM -- are discussed. [ABSTRACT FROM AUTHOR]

This paper describes efforts to more fully exploit the synergy potential between hardware and software to improve performance on the IBM System z® platform. Although the IBM commitment to upward compatibility for System z mainframes prevents us from engaging in hardware generational tuning, software stack improvements aimed at one generation of hardware tend to increase in value for subsequent generations. This paper presents some of the software synergy efforts that were made to complement hardware design characteristics to improve performance and that will continue to be of benefit in future machine generations. Also presented is IBM z/OS® HiperDispatch management, which minimizes cache coherency penalties when dispatching work, and the new IBM System z10™ hardware instrumentation, the central processor measurement facility (CPMF), which supports software performance optimizations by providing counters and sampling and allowing the software to measure central processor activities to determine hotspots. The CPMF is nondisruptive, has low overhead, and can run in multiple logical partitions simultaneously. [ABSTRACT FROM AUTHOR]