PNG

Summary

Portable Network Graphics (PNG, officially pronounced pɪŋ , colloquially pronounced ˌpiːɛnˈdʒiː ) is a raster-graphics file that supports lossless data compression. PNG was developed as an improved, non-patented replacement for Graphics Interchange Format (GIF)—unofficially, the initials PNG stood for the recursive acronym "PNG's not GIF". PNG supports palette-based images (with palettes of 24-bit RGB or 32-bit RGBA colors), grayscale images (with or without an alpha channel for transparency), and full-color non-palette-based RGB or RGBA images. The PNG working group designed the format for transferring images on the Internet, not for professional-quality print graphics; therefore, non-RGB color spaces such as CMYK are not supported. A PNG file contains a single image in an extensible structure of chunks, encoding the basic pixels and other information such as textual comments and integrity checks documented in RFC 2083. PNG files have the ".png" and the "image/png" MIME medi

Official source

https://en.wikipedia.org/wiki/PNG

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An Automated, yet Interactive and Portable DB designer

Anastasia Ailamaki, Ioannis Alagiannis, Debabrata Dash

Tuning tools attempt to configure a database to achieve optimal performance for a given workload. Selecting an optimal set of physical structures is computationally hard since it involves searching a vast space of possible configurations. Commercial DBMSs offer tools that can address this problem. The usefulness of such tools, however, is limited by their dependence on greedy heuristics, the need for a-priori (offline) knowledge of the workload, and lack of an optimal materialization schedule to get the best out of suggested design features. Moreover, the open source DBMSs do not provide any automated tuning tools. This demonstration introduces a comprehensive physical designer for the PostgreSQL open source DBMS. The tool suggests design features for both offline and online workloads. It provides close to optimal suggestions for indexes for a given workload by modeling the problem as a combinatorial optimization problem and solving it by sophisticated and mature solvers. It also determines the interaction between indexes to suggest an effective materialization strategy for the selected indexes. The tool is interactive as it allows the database administrator (DBA) to suggest a set of candidate features and shows their benefits and interactions visually. For the demonstration we use large realworld scientific datasets and query workloads.

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Compact High-Performance Continuous-Wave Double-Resonance Rubidium Standard With 1.4 x 10(-13) tau(-1/2) Stability

Francesco Merli, Anja Skrivervik Favre, Camillo Stefanucci

We present our studies on a compact high-performance continuous wave (CW) double-resonance (DR) rubidium frequency standard in view of future portable applications. Our clock exhibits a short-term stability of 1.4 x 10(-13) tau(-1/2), consistent with the short-term noise budget for an optimized DR signal. The metrological studies on the medium- to long-term stability of our Rb standard with measured stabilities are presented. The dependence of microwave power shift on light intensity, and the possibility to suppress the microwave power shift is demonstrated. The instabilities arising from the vapor cell geometric effect are evaluated, and are found to act on two different time scales (fast and slow stem effects). The resulting medium-to long-term stability limit is around 5.5 x 10(-14). Further required improvements, particularly focusing on medium-to long-term clock performance, are discussed.

Institute of Electrical and Electronics Engineers2014

Reliably detecting focal seizures without secondary generalization during daily life activities, chronically, using convenient portable or wearable devices, would offer patients with active epilepsy a number of potential benefits, such as providing more reliable seizure count to optimize treatment and seizure forecasting, and triggering alarms to promote safeguarding interventions. However, no generic solution is currently available to reach these objectives. A number of biosignals are sensitive to specific forms of focal seizures, in particular heart rate and its variability for seizures affecting the neurovegetative system, and accelerometry for those responsible for prominent motor activity. However, most studies demonstrate high rates of false detection or poor sensitivity, with only a minority of patients benefiting from acceptable levels of accuracy. To tackle this challenging issue, several lines of technological progress are envisioned, including multimodal biosensing with cross‐modal analytics, a combination of embedded and distributed self‐aware machine learning, and ultra–low‐power design to enable appropriate autonomy of such sophisticated portable solutions.

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