High efficiency ground data transmission

It is demonstrated that state-of-the-art communications technology can be implemented and reliably operated on a global basis to increase the transmission rates and efficiencies on circuits with bandwidths greater than the typical speech channel. Optimization is affected by optimum clock recovery procedures, multilevel pulse amplitude modulation, single sideband amplitude modulation, transversal filter equalizers, data scrambling, and active compensation for phase instability

Radiated microwave power transmission system efficiency measurements

The measured and calculated results from determining the operating efficiencies of a laboratory version of a system for transporting electric power from one point to another via a wireless free space radiated microwave beam are reported. The system's overall end-to-end efficiency as well as intermediated conversion efficiencies were measured. The maximum achieved end-to-end dc-to-ac system efficiency was 54.18% with a probable error of + or - 0.94%. The dc-to-RF conversion efficiency was measured to be 68.87% + or - 1.0% and the RF-to-dc conversion efficiency was 78.67 + or - 1.1%. Under these conditions a dc power of 495.62 + or - 3.57 W was received with a free space transmitter antenna receiver antenna separation of 170.2 cm (67 in)

Sense of agency, associative learning, and schizotypy

Despite the fact that the role of learning is recognised in empirical and theoretical work on sense of agency (SoA), the nature of this learning has, rather surprisingly, received little attention. In the present study we consider the contribution of associative mechanisms to SoA. SoA can be measured quantitatively as a temporal linkage between voluntary actions and their external effects. Using an outcome blocking procedure, it was shown that training action-outcome associations under conditions of increased surprise augmented this temporal linkage. Moreover, these effects of surprise were correlated with schizotypy scores, suggesting that individual differences in higher level experiences are related to associative learning and to its impact on SoA. These results are discussed in terms of models of SoA, and our understanding of disrupted SoA in certain disorders

A computer vision approach to classification of birds in flight from video sequences

Bird populations are an important bio-indicator; so collecting reliable data is useful for ecologists helping conserve and manage fragile ecosystems. However, existing manual monitoring methods are labour-intensive, time-consuming, and error-prone. The aim of our work is to develop a reliable system, capable of automatically classifying individual bird species in flight from videos. This is challenging, but appropriate for use in the field, since there is often a requirement to identify in flight, rather than when stationary. We present our work in progress, which uses combined appearance and motion features to classify and present experimental results across seven species using Normal Bayes classifier with majority voting and achieving a classification rate of 86%

Wing and body motion during flight initiation in Drosophila revealed by automated visual tracking

The fruit fly Drosophila melanogaster is a widely used model organism in studies of genetics, developmental biology and biomechanics. One limitation for exploiting Drosophila as a model system for behavioral neurobiology is that measuring body kinematics during behavior is labor intensive and subjective. In order to quantify flight kinematics during different types of maneuvers, we have developed a visual tracking system that estimates the posture of the fly from multiple calibrated cameras. An accurate geometric fly model is designed using unit quaternions to capture complex body and wing rotations, which are automatically fitted to the images in each time frame. Our approach works across a range of flight behaviors, while also being robust to common environmental clutter. The tracking system is used in this paper to compare wing and body motion during both voluntary and escape take-offs. Using our automated algorithms, we are able to measure stroke amplitude, geometric angle of attack and other parameters important to a mechanistic understanding of flapping flight. When compared with manual tracking methods, the algorithm estimates body position within 4.4±1.3% of the body length, while body orientation is measured within 6.5±1.9 deg. (roll), 3.2±1.3 deg. (pitch) and 3.4±1.6 deg. (yaw) on average across six videos. Similarly, stroke amplitude and deviation are estimated within 3.3 deg. and 2.1 deg., while angle of attack is typically measured within 8.8 deg. comparing against a human digitizer. Using our automated tracker, we analyzed a total of eight voluntary and two escape take-offs. These sequences show that Drosophila melanogaster do not utilize clap and fling during take-off and are able to modify their wing kinematics from one wingstroke to the next. Our approach should enable biomechanists and ethologists to process much larger datasets than possible at present and, therefore, accelerate insight into the mechanisms of free-flight maneuvers of flying insects

Accuracy of discharge determinations

June 1967.Includes bibliographical references (pages 51-54)

Alien Registration- Dickinson, Harvey W. (Houlton, Aroostook County)

https://digitalmaine.com/alien_docs/36133/thumbnail.jp