International Solar-Terrestrial Program Data Processing Consortium

The present conception of the data processing scheme is described including the Main Processing Units (MPU) and Satellite Processing Units (SPU) which will acquire the data for the instruments presently planned in the International Solar Terrestrial Physics (ISTP) Project

Mission description and in-flight operations of ERBE instruments on ERBS and NOAA 9 spacecraft, November 1984 - January 1986

Instruments of the Earth Radiation Budget Experiment (ERBE) are operating on three different Earth orbiting spacecrafts: the Earth Radiation Budget Satellite (ERBS), NOAA-9, and NOAA-10. An overview is presented of the ERBE mission, in-orbit environments, and instrument design and operational features. An overview of science data processing and validation procedures is also presented. In-flight operations are described for the ERBE instruments aboard the ERBS and NOAA-9. Calibration and other operational procedures are described, and operational and instrument housekeeping data are presented and discussed

Flexible data input layer architecture (FDILA) for quick-response decision making tools in volatile manufacturing systems

This paper proposes the foundation for a flexible data input management system as a vital part of a generic solution for quick-response decision making. Lack of a comprehensive data input layer between data acquisition and processing systems has been realized and thought of. The proposed FDILA is applicable to a wide variety of volatile manufacturing environments. It provides a generic platform that enables systems designers to define any number of data entry points and types regardless of their make and specifications in a standard fashion. This is achieved by providing a variable definition layer immediately on top of the data acquisition layer and before data pre-processing layer. For proof of concept, National Instruments’ Labview data acquisition software is used to simulate a typical shop floor data acquisition system. The extracted data can then be fed into a data mining module that builds cost modeling functions involving the plant’s Key Performance Factors

Cherenkov Telescope Array Data Management

Very High Energy gamma-ray astronomy with the Cherenkov Telescope Array (CTA) is evolving towards the model of a public observatory. Handling, processing and archiving the large amount of data generated by the CTA instruments and delivering scientific products are some of the challenges in designing the CTA Data Management. The participation of scientists from within CTA Consortium and from the greater worldwide scientific community necessitates a sophisticated scientific analysis system capable of providing unified and efficient user access to data, software and computing resources. Data Management is designed to respond to three main issues: (i) the treatment and flow of data from remote telescopes; (ii) "big-data" archiving and processing; (iii) and open data access. In this communication the overall technical design of the CTA Data Management, current major developments and prototypes are presented.Comment: 8 pages, 2 figures, In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

Towards a breakthrough in nutrient recycling : State-of-the-art and recommendations for developing policy instruments in Finland

The report has been complemented on 11.9.2018This report describes the state-of-the-art in phosphorus and nitrogen recycling in Finland and looks at basic data on the volumes and geographical distribution of biomasses and their nutrients. Based on this data, the report makes proposals for measures aiming to promote nutrient recycling. This report was prepared collaboratively by experts at the institutions making up the Finnish Partnership for Research on Natural Resources and the Environment (LYNET) to underpin a national action plan on nutrient recycling. Of all sectors in Finland, agriculture is the largest user and recycler of phosphorus and nitrogen. Different biomasses contain an annual total of approximately 26,000 t of recyclable phosphorus, which exceeds the fertilisation needs of grasslands and cereal crops in the entire area of Finland. The volume of nitrogen contained in biomasses is approximately 95,000 t. Still, approx. 11,000 t of phosphorus and 152,000 t of nitrogen are annually used in Finland as conventional inorganic fertilisers. There is a regional imbalance between manure production and crop nutrient requirements. The breakthrough in nutrient recycling means increased implementation of manure processing, thus making manure nutrients easier to transport and reducing the use of conventional inorganic fertilisers. At minimum 20% of the entire volume of manure generated in Finland will require advanced processing to enable long-distance transport of the manure phosphorus to areas in need of it. This requires separation of water. The highest demand for advanced processing is experienced in the regions of Ostrobothnia (approx. 60% at minimum), South Ostrobothnia and Satakunta (approx. 30 %) and Southwest Finland (13%). In the agricultural sector, fertilisation is currently guided by a wide array of different policy instruments, which make up an incoherent and unstructured whole. The instruments cause considerable amounts of regulatory burden, but appear to do little to promote sustainable nutrient recycling. This report proposes a total reform of the policy instruments to boost the recycling of nutrients. All legal standards related to fertilisation should be merged into a single statute, for example by developing the Nitrate Decree. At the same time, the current policy that controls nutrient use via the EU agri-environmental scheme should be abandoned, and the role of the environmental permit for livestock installations and its relationship with general regulatory instruments be clarified. A field plot specific nutrient database should be created to support guidance. The knowledge base of nutrient recycling should be developed by creating and maintaining a comprehensive data system on the quantities, properties and locations of nutrient-rich biomasses and ashes and their current processing methods. The report also proposes setting regional processing targets for livestock manure. Key objectives should include reducing excessive fertilisation in crop production. The goal of normative guidance should be nutrient use according to the crop needs.201

Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry

Deep learning has achieved spectacular performance in image and speech recognition and synthesis. It outperforms other machine learning algorithms in problems where large amounts of data are available. In the area of measurement technology, instruments based on the photonic time stretch have established record real-time measurement throughput in spectroscopy, optical coherence tomography, and imaging flow cytometry. These extreme-throughput instruments generate approximately 1 Tbit/s of continuous measurement data and have led to the discovery of rare phenomena in nonlinear and complex systems as well as new types of biomedical instruments. Owing to the abundance of data they generate, time-stretch instruments are a natural fit to deep learning classification. Previously we had shown that high-throughput label-free cell classification with high accuracy can be achieved through a combination of time-stretch microscopy, image processing and feature extraction, followed by deep learning for finding cancer cells in the blood. Such a technology holds promise for early detection of primary cancer or metastasis. Here we describe a new deep learning pipeline, which entirely avoids the slow and computationally costly signal processing and feature extraction steps by a convolutional neural network that directly operates on the measured signals. The improvement in computational efficiency enables low-latency inference and makes this pipeline suitable for cell sorting via deep learning. Our neural network takes less than a few milliseconds to classify the cells, fast enough to provide a decision to a cell sorter for real-time separation of individual target cells. We demonstrate the applicability of our new method in the classification of OT-II white blood cells and SW-480 epithelial cancer cells with more than 95% accuracy in a label-free fashion

Applications of ISES for instrument science

It is often the case that some instruments being used for geophysical measurements cannot measure some parameters that are important for processing the data obtained using the instrument. However, the parameters of interest may be measured by other instruments and these data made available to the operators of the first instrument. Processing the data immediately after it is acquired is useful in directing the operation of the same or different instrument or in providing a quick look data set to users on the ground. The four applications which are considered are: the decision to acquire data due to some important occurrence detected by Eos instruments; the decision not to acquire data at a scheduled time and/or location; the decision to acquire additional data to improve data quality; and combining data from several sources to enhance data quality. General examples are presented, which may or may not apply directly to Eos instruments on the various platforms

The Design and Operation of The Keck Observatory Archive

The Infrared Processing and Analysis Center (IPAC) and the W. M. Keck Observatory (WMKO) operate an archive for the Keck Observatory. At the end of 2013, KOA completed the ingestion of data from all eight active observatory instruments. KOA will continue to ingest all newly obtained observations, at an anticipated volume of 4 TB per year. The data are transmitted electronically from WMKO to IPAC for storage and curation. Access to data is governed by a data use policy, and approximately two-thirds of the data in the archive are public.Comment: 12 pages, 4 figs, 4 tables. Presented at Software and Cyberinfrastructure for Astronomy III, SPIE Astronomical Telescopes + Instrumentation 2014. June 2014, Montreal, Canad