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Write RXML that enables your AACR to list the alternative VHF radio bands including the aeronautical VHF UHF band Write a stand-alone Java simulation that enables an AACR to explain why band edges are de ned differently between the ITU and other authorities Simulate AACR behavior to learn the usage patterns of VHF in an area, such as whether pilot-to-tower communications are used Postulate or use a speech recognition tool like ViaVoice 753 Write RXML that enables your AACR to know how to measure delay and Doppler spread either from known broadcast stations with controlled time and pulsed emissions or by collaborating with local AACR peers Write a standalone computer program that simulates the measurement of delay spread Write a program that simulates introspection over a SDR-SCA or OMG-SRA regarding whether a given SDR waveform has an adaptive equalizer.

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HARVEY: I wanted to talk to both of you today. From this point on, you are a team in this, and you both need to be involved. This includes you, Gini, even though you will probably not be doing any of the trading. GINI: I want to be involved. I think I have been included in most of it up to this point. Even if I heard about trades or whatever a few days late, at least I ve heard about them. ME: I do want her to be a part of all of this. I can see how that will help. HARVEY: How

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Write RXML and a stand-alone computer program that enables it to compute the number of T/2 (half-channel symbol period) taps needed to compensate for typical and extreme delay spread measured 754 Write RXML that enables your AACR to know about AM and FM aeronautical communications Write a stand-alone computer program that uses this RXML to explain to a nonexpert user why general aviation persists in using.

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<Scene/> with time of observation. There are myriad uncertainties and frame alignment challenges for a <Scene/> integration algorithm to restart a <Scene/> after it has been lost for a threshold period of time (e.g., a minute, to prevent thrashing hypothesized new scenes when GPS is aky). 11.1.1.1 Scenes and Microworlds The CRA does not specify linkages across scenes, but postulates microworlds and linkages among microworlds, with some CRA <Self/> exemplars. To preserve LCS, a new scene may be formed when a new <Sketch/> needs to be generated; for example, because the <Place/> has changed, the <Self/> has no anchor points, the <Self/> senses movement along a <Path/>, or the con guration of an <interior/> has changed through actions like rearranging the furniture. Thus, <Home/> would be a microworld with each <Room/> and separate space as a <Scene/> with an associated LCS <Sketch/>. 11.1.1.2 Time Structures Perception Into Observations and <Paths/> Perception at a speci ed time is an <Observation/>, asserted into the current <Scene/> as it is perceived. If suf cient time passes, a watchdog timer terminates reasoning over unrecognizable features linked to the <Scene/> to manage combinatorial explosion. In a sequence <Vision Time = 38394.5066235451> <Tree/> <Grass/> </Vision> and <Vision Time = 38394.5067583321> <House/> </Vision> the time tag enables the cognition system to construct a space time path with trees, grass, and a house. If the AACR knew from the in-car BlueTooth that it had just been in a car, it can construct an embryonic <Path/>: Expression 11-2 Embryonic Path From Car to House

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<Path> <Place> Car </Place> <Time t = 0> <Scene ID = <Owner s-car/>/> </Time> <Time t = 1> <Tree/> <Grass/> </Time> <Time t = 2> <House/> </Time> <Where /> </Path> The path has not yet ended, so it terminates with the concept <Where />, asserting that the end of the path is not known. Such RXML paths can be traversed in either forward or reverse directions and when something is recognized to complete a loop, the AACR knows the <Path/> along the loop. By counting the reoccurrence of such paths, the AACR learns user paths through simple reinforcement. In the primal loop <Home/> <Car/> <Work/> <Car/> <Home/>, there are many small loops, for example, from car to <Grass/>, <House/> and back. 11.1.1.3 Novelty Suggests Scene Boundary Hypotheses If the perception system detects strong <Novel/> features of a known <Class/> of <Scene/>, a new <Scene/> may be asserted as a KO for subsequent AML

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