Real-Time Concurrent Processes

2000 ◽  
Author(s):  
Steve Vestal
Keyword(s):  
Real Time ◽  
Concurrent Processes

Modeling Big Data Analytics with a Real-Time Executable Specification Language

2015 ◽  
pp. 289-312
Author(s):  
Amir A. Khwaja
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Exception Handling ◽  
Specification Language ◽  
Big Data Processing ◽  
Business Decisions ◽  
Concurrent Processes

Big data explosion has already happened and the situation is only going to exacerbate with such a high number of data sources and high-end technology prevalent everywhere, generating data at a frantic pace. One of the most important aspects of big data is being able to capture, process, and analyze data as it is happening in real-time to allow real-time business decisions. Alternate approaches must be investigated especially consisting of highly parallel and real-time computations for big data processing. The chapter presents RealSpec real-time specification language that may be used for the modeling of big data analytics due to the inherent language features needed for real-time big data processing such as concurrent processes, multi-threading, resource modeling, timing constraints, and exception handling. The chapter provides an overview of RealSpec and applies the language to a detailed big data event recognition case study to demonstrate language applicability to big data framework and analytics modeling.

Modeling Big Data Analytics with a Real-Time Executable Specification Language

Big Data ◽  
2016 ◽  
pp. 418-440
Author(s):  
Amir A. Khwaja
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Exception Handling ◽  
Specification Language ◽  
Big Data Processing ◽  
Business Decisions ◽  
Concurrent Processes

Big data explosion has already happened and the situation is only going to exacerbate with such a high number of data sources and high-end technology prevalent everywhere, generating data at a frantic pace. One of the most important aspects of big data is being able to capture, process, and analyze data as it is happening in real-time to allow real-time business decisions. Alternate approaches must be investigated especially consisting of highly parallel and real-time computations for big data processing. The chapter presents RealSpec real-time specification language that may be used for the modeling of big data analytics due to the inherent language features needed for real-time big data processing such as concurrent processes, multi-threading, resource modeling, timing constraints, and exception handling. The chapter provides an overview of RealSpec and applies the language to a detailed big data event recognition case study to demonstrate language applicability to big data framework and analytics modeling.

Some Recent Results in Quiescent Prominence Spectrometry

1979 ◽  
Vol 44 ◽  
pp. 41-47
Author(s):  
Donald A. Landman
Keyword(s):  
Real Time ◽  
Computer System ◽  
Spectral Response ◽  
Absolute Intensity ◽  
Solar Observatory ◽  
Target Size ◽  
Small Target ◽  
Signal Averaging ◽  
Quiescent Prominence

This paper describes some recent results of our quiescent prominence spectrometry program at the Mees Solar Observatory on Haleakala. The observations were made with the 25 cm coronagraph/coudé spectrograph system using a silicon vidicon detector. This detector consists of 500 contiguous channels covering approximately 6 or 80 Å, depending on the grating used. The instrument is interfaced to the Observatory’s PDP 11/45 computer system, and has the important advantages of wide spectral response, linearity and signal-averaging with real-time display. Its principal drawback is the relatively small target size. For the present work, the aperture was about 3″ × 5″. Absolute intensity calibrations were made by measuring quiet regions near sun center.

Video real-time imaging of artificial membranes during freeze-drying by cryo-electron microscopy

1988 ◽  
Vol 46 ◽  
pp. 16-17
Author(s):  
Alan S. Rudolph ◽  
Ronald R. Price
Keyword(s):  
Real Time ◽  
Self Assembly ◽  
Freeze Drying ◽  
Video Capture ◽  
Drying Process ◽  
Artificial Membranes ◽  
The Past ◽  
Cryo Electron Microscopy ◽  
Spherical Structures ◽  
Capture Techniques

We have employed cryoelectron microscopy to visualize events that occur during the freeze-drying of artificial membranes by employing real time video capture techniques. Artificial membranes or liposomes which are spherical structures within internal aqueous space are stabilized by water which provides the driving force for spontaneous self-assembly of these structures. Previous assays of damage to these structures which are induced by freeze drying reveal that the two principal deleterious events that occur are 1) fusion of liposomes and 2) leakage of contents trapped within the liposome [1]. In the past the only way to access these events was to examine the liposomes following the dehydration event. This technique allows the event to be monitored in real time as the liposomes destabilize and as water is sublimed at cryo temperatures in the vacuum of the microscope. The method by which liposomes are compromised by freeze-drying are largely unknown. This technique has shown that cryo-protectants such as glycerol and carbohydrates are able to maintain liposomal structure throughout the drying process.

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