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As an emerging approach to space situational awareness and space imaging, the practical use of an event-based camera (EBC) in space imaging for precise source analysis is still in its infancy. The nature of event-based space imaging and data collection needs to be further explored to develop more effective event-based space imaging systems and advance the capabilities of event-based tracking systems with improved target measurement models. Moreover, for event measurements to be meaningful, a framework must be investigated for EBC calibration to project events from pixel array coordinates in the image plane to coordinates in a target resident space object’s reference frame. In this paper, the traditional techniques of conventional astronomy are reconsidered to properly utilise the EBC for space imaging and space situational awareness. This paper presents the techniques and systems used for calibrating an EBC for reliable and accurate measurement acquisition. These techniques are vital in building event-based space imaging systems capable of real-world space situational awareness tasks. By calibrating sources detected using the EBC, the spatiotemporal characteristics of detected sources or “event sources” can be related to the photometric characteristics of the underlying astrophysical objects. Finally, these characteristics are analysed to establish a foundation for principled processing and observing techniques which appropriately exploit the capabilities of the EBC.

A revolutionary type of imaging device, known as a silicon retina or event-based sensor, has recently been developed and is gaining in popularity in the field of artificial vision systems. These devices are inspired by a biological retina and operate in a significantly different way to traditional CCD-based imaging sensors. While a CCD produces frames of pixel intensities, an event-based sensor produces a continuous stream of events, each of which is generated when a pixel detects a change in log light intensity. These pixels operate asynchronously and independently, producing an event-based output with high temporal resolution. There are also no fixed exposure times, allowing these devices to offer a very high dynamic range independently for each pixel. Additionally, these devices offer high-speed, low power operation and a sparse spatio-temporal output. As a consequence, the data from these sensors must be interpreted in a significantly different way to traditional imaging sensors and this paper explores the advantages this technology provides for space imaging. The applicability and capabilities of event-based sensors for SSA applications are demonstrated through telescope field trials. Trial results have confirmed that the devices are capable of observing resident space objects from LEO through to GEO orbital regimes. Significantly, observations of RSOs were made during both day-time and night-time (terminator) conditions without modification to the camera or optics. The event based sensor’s ability to image stars and satellites during day-time hours offers a dramatic capability increase for terrestrial optical sensors. This paper shows the field testing and validation of two different architectures of event-based imaging sensors. An event-based sensor’s asynchronous output has an intrinsically low data-rate. In addition to low-bandwidth communications requirements, the low weight, low-power and high-speed make them ideally suitable to meeting the demanding challenges required by space-based SSA systems. Results from these experiments and the systems developed highlight the applicability of event-based sensors to ground and space-based SSA tasks.

As the interest in event-based vision sensors for mobile and aerial applications grows, there is an increasing need for high-speed and highly robust algorithms for performing visual tasks using event-based data. As event rate and network structure have a direct impact on the power consumed by such systems, it is important to explore the efficiency of the event-based encoding used by these sensors. The work presented in this paper represents the first study solely focused on the effects of both spatial and temporal downsampling on event-based vision data and makes use of a variety of data sets chosen to fully explore and characterize the nature of downsampling operations. The results show that both spatial downsampling and temporal downsampling produce improved classification accuracy and, additionally, a lower overall data rate. A finding is particularly relevant for bandwidth and power constrained systems. For a given network containing 1000 hidden layer neurons, the spatially downsampled systems achieved a best case accuracy of 89.38% on N-MNIST as opposed to 81.03% with no downsampling at the same hidden layer size. On the N-Caltech101 data set, the downsampled system achieved a best case accuracy of 18.25%, compared with 7.43% achieved with no downsampling. The results show that downsampling is an important preprocessing technique in event-based visual processing, especially for applications sensitive to power consumption and transmission bandwidth. [ABSTRACT FROM AUTHOR]

In a competitive market the design and operating decisions of the competing firms influence their own and their competitors' profitability. Game theory suggests ways in which the competitors' intentions can be allowed for Its use is illustrated with reference to a simple chemical plant example.In the first part of the paper the decision making problem for competing firms is cast into a Lagrange multiplier formulation for constrained optimization. This gives new insight into the conventional micro-economic formulations, enables more comprehensive results to be obtained for the Russell and Bogaert problem (1980) and resolves some apparent discrepancies. The treatment also illustrates how a two-level decision problem can be solved in a competitive environment where, as is very commonly found, design decisions are irrevocable once the plant has been built but operating conditions can be adjusted to match the current situation.The second part of the paper treats the case in which the two participating firms agree to co-operate to their mutual benefit. However, the way in which the benefits of this co-operation are divided between the participants is determined by the pressure each can exert on the other by potentially threatening behaviour. Numerical results are presented for the earlier example for various scenarios and compared with the results obtained for purely competitive activity in the first part of the paper

The Toxic Substances Control Act (TSCA) has started to have a significant impact on the chemical industry. This act gives the Environmental Protection Agency (EPA) far-reaching authority to regulate the manufacture, processing, use, and disposal of chemicals perceived to be dangerous to the health of mankind and/or to the environment. According to the current list of chemical substances for testing for health and environmental effects [15], benzene-based chemicals are exposed to intense scrutiny and decisions made regarding such chemicals would have serious effects on growth and development of certain sectors of the chemical industry.

In the United States economy, intermediate petrochemicals rarely find direct consumer use; rather, they serve as raw materials for the manufacture of synthetic fibers, plastics, and resins; synthetic rubber, and thousands of other products. The demand for these end products drives the growth of the intermediate chemicals industry and shapes future technology. It is clear that petrochemical technology assessment requires both an understanding of the technology and of the function the technology is to serve in the economy.