Roller Coaster Physics

  • a point mass moving on a spline
  • frictionless with gravity
  • energy conservation law applies

EK+EP=12mv2+mgh=mghmaxE_K + E_P = \frac{1}{2} m \| v \|^2 + mgh = mgh_{max}

We can always compute the magnitude of the velocity of any given point!

v=2g(hmaxh)\| v \| = \sqrt{2g(h_{max}-h)}

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Congestion

Too many sources are sending too much data too fast for network to handle!

Manifestations: long delays (queueing in router buffers), packet loss (buffer overflow at routers)

Different from flow control! Flow control is needed when one sender is too fast for one receiver.
Congestion control is needed when too many senders are sending too fast.

Congestion scenario 1: Two hosts

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Subdivision Curves

Subdivide polygonal mesh into larger number of polygons.
Control points eventually converge to underlying smooth curve!

Binary Curve Subdivision

Binary Curve Subdivision

We'll divide curve into left segment and right segment.

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TCP

  • Point-to-point: One sender and one receiver
  • Reliable, in-order byte stream: No need to message boundaries
  • Full duplex data: Bi-directional data flow in same connection. i.e. client and server can send the data at the same time.
  • MSS (Maximum Segment Size)
  • Cumulative ACKs: only ACK consecutive packets
  • Connection-oriented: Handshaking needed
  • Flow control with receiver window size (to not overwhelm receiver)
  • Congestion control to avoid overflowing network

TCP segment header

  • source, destination port number
  • sequence number: first byte's sequence number (we assign sequence number per each byte)
  • acknowledgement number: sequence number of next expected byte (ACK n, other host's sequence number)
  • length: only 4 bits!!
  • receiver window size: max 65536, can be increased in options
  • options: e.g. increase length of receiver window, congestion control, tcp options, ...
  • checksum

TCP timeout

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The Human Information Processor (HIP) Model

Combines several cognitive psychology concepts into a simplified, unified framework.
It's a simplified approximation of human information processing for computer scientists.

View human mind as an information processing system.
Each system has memory and processor.

  • Memory has capacity, decay time, code type (physical, acoustic, visual, ...).
  • Processor operates on a fixed cycle time. (Perceptual processor cycle τP\tau_P, Cognitive processor cycle τC\tau_C, Motor processor cycle τM\tau_M)

Human Performance

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Models of the Human

Descriptive models help us think more clearly about human behavior.
Model helps us design better systems that match how people actually think and act.

There are many models of the human, but we begin with two useful models,
Newell's Time Scale of Human Action, and Human Factors Model.

Newell's Time Scale of Human Action

Human actions happen at different time scales.

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Motivation

Implementing curves and surfaces with lots of points is inefficient.
We want higher-level representation of curves and surfaces.
Specifically, we would like to find a smooth curve/surface with a minimal number of control points.

Parametric Geometry

p(t)=(x(t),y(t))p(t) = (x(t), y(t))

p(u,v)=(x(u,v),y(u,v),z(u,v))p(u, v) = (x(u, v), y(u, v), z(u, v))

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Reliable data transfer

Sender and receiver use reliable data transfer protocol to unreliable channel.
Unreliable channel may lose, corrupt, or reorder data.
Sender and receiver do not know the state of each other. e.g. Was a message received?

Assumes transport layer is reliable!
i.e. data <-> packet is reliable

rdt (Reliable data transfer) protocol

  • rdt_send(): Application call it to send data.
  • udt_send(): Called by rdt to transfer packet over unreliable channel to receiver
  • rdt_rcv(): Called when packet arrives on receiver side of unreliable channel
  • deliver_data(): Called by rdt to deliver data to application.
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Geometry in graphics

Scene is an assembly of one or more objects.
An object contains transformation, geometry, material, and lighting.

Implicit representations

Pros:

  • Description can be very compact
  • Easy to determine if a point is inside or outside
  • Other queries may also be easy (e.g. distance to surface)
  • Simple shapes have exact description and no sampling error
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