Students Again

In the text below you will find completed examples of Informatics Homework. These examples include code for C Programs, assigned reading summaries, symbolic logic, boolean logic, base conversions, set theory, and more. All of these examples are consistent with what you might find in an Informatics college course.

Note: If you are having trouble viewing this page or would prefer to view this information in a document viewer Click Here!

---

Natural-Born Cyborgs: Minds, Technologies, and the Future of Human Intelligence – Chapter 2

Summary

Andy Clark begins chapter two with a story about his visit to Los Alamos National Laboratory. During his visit he notices the distinction between old and new technology. Los Alamos is a bunker designed to house huge mainframes and other big complex equipment. However, Clark notices that the lab currently houses a few high-powered laptops. After lunch, his next stop was The Black Hole. The Black Hole is a shopping outlet where people can purchase retired National Laboratory equipment. The Black Hole is “an elephant’s graveyard of Un-transparent, In-Your-Face Technology.” The point of Clark’s story was to note the contrast between two types of technologies: transparent technologies and opaque technologies. Transparent technologies are so integrated with the user that they are almost invisible in use. Opaque technologies require unnatural skills and the focus of attention remains during use. The problem with opaque technologies is the ability of the user to successfully set up and run the tool. Transparent technologies allow the user to literally see through the tool and directly confront the issue at hand.

Donald Norman, a Cognitive Scientist, views opaque versus transparent technologies as technology centered versus human centered products. For technology centered products to achieve widespread adoption by users and for the product to survive it must provide clear benefits at low cognitive and economic cost. When this is accomplished it creates a kind of symbiotic relationship with the biological user. An example of this symbiotic relationship is the wristwatch. As an agricultural society people relied on natural time (aka the Sun). As society moved into the Industrial Age new ways to keep time were developed. These new time keeping measures transformed from a town time caller to a town clock and eventually to personal time devices. Over time, the wristwatch became transparent (achieved symbiosis). Technology must change over time to become easy-to-use, access, and purchase. However, in return, elements of culture, education, and society must too change over time.

The technological and social evolution that occurred with time keeping is now happening with information itself. There are a number of researchers facilitating this transformation. Clark argues that, “Mark Weiser’s vision of ubiquitous computing is finding concrete expression in attempts to design and market what Norman calls information appliances.” Information appliances are defined by three criteria: 1) They are geared to support a specific activity; 2) They form an intercommunicating web; and 3) They are transparent technologies. An example of an information appliance is Bradley Rhode’s wearable remembrance agent (a hat-like device with an above head viewable screen for the user). The danger of transparent pseudoneural technologies is a loss of human control over a technology of which we are barely aware.

Dourish (a former colleague of Weiser) coined the term tangible computing. Tangible computing maintains key elements of invisible computation but seeks to do so without allowing the tools and technologies to become permanently invisible. The Tangible Media Group at the Massachusetts Institute of Technology Media Lab is researching and developing technologies in the manner of the tangible computing discipline. One such project is called Sensetable. The Sensetable is a tabletop display that uses electromagnetic sensing to determine a variety of physical objects which the user can move around so as to alter the information displayed. Another area being researched Augmented Reality. Augmented Reality also focuses on the idea of reinventing the interface of technological tools. The goal is to overlay the human experience of the physical world with layers of personalized digital information. Some ideas being introduced include direct optical input overlaid with computer graphics and retrofitted eyeglasses to add digital information to the everyday scene.

Clark claims that the blurring of the physical and technological has educational importance: “If we are to become complex biotechnological hybrids, a major challenge is to train young minds to think well about a world in which the physical and the informational/digital are densely and continuously interwoven.” Researchers are developing mixed reality play to address this challenge. Mixed reality play makes the virtual/informational tangible and the physical is made virtual. It is believed that mixed reality play will help alleviate opposition between the real and the virtual.

Several visions of the near future were covered in this chapter. Clark coined the term “dynamic appliances” encapsulating the inevitable convergence of these visions. Dynamic appliances are information appliances that, in use, actively work to learn about and better fit the user. It is likely that a variety of these different technologies being researched will be in our future; and “such technologies are apt for the most profound and enduring kinds of interweaving into our lives, identities, and projects, and into our constantly constructed sense of place, presence, and self.”

Information: The New Language of Science – Chapter 1 and 4 Summary

Information is like electric rain, meaning that information surrounds people in every environment. Of this information that surrounds us, some is accessible and some is not (e.g. military transmission). The underlying zeroes and ones (binary language) parallel our universe. They form the foundation for information to carry meaning.

Due to the exponential growth model, our information universe has exploded. Marshall McLuhan pioneered the idea that information was a commodity. This pioneering notion facilitated International Business Machines (IBM) realization that they were in the business of information and not office equipment. Thus, IBM was destined to pave way for the information age.

Due to the limits of growth theory, some people believe the progression of information technology will come to resemble economists Thomas Malthus’ S-curve. Furthermore, many believe the limits on information technology as dictated by physical law will be reached in the 2020s. As technology transforms we become further engulfed with information. Scientists and engineers are leading this transformation. At Massachusetts Institute of Technology (MIT) the Oxygen project was launched. The goal of Oxygen is to make “computation as ubiquitous as the air we breathe.” To accomplish this MIT envisions a world with computers built into everything. On the west coast the University of California, Berkeley founded the Endeavour project. This project is aimed at “creating an ocean of data that will envelop people like fish in the sea.”

So, what are the limits to technology and information? First, the impact of information is not universal. Half of the world is still stricken with poverty and health issues. Second, the real cost of technology has yet to be realized. It has been suggested that a two gram microchip consumes many times its weight in chemicals, fuel, and water. It is still undetermined when these hidden costs will become unreasonable. Lastly, human frailty may contribute to the limitations. Murray Gell-Mann best states the mechanics of the human frailty limitation: “finding meaning in a flood of data, and wisdom in an ocean of information” which may lead to “a cybership without a human steersman [becoming] a vessel out of control.”

In addition to artificial information, natural information engulfs us. This is contributed through the tools of our biological being (e.g. brain, eyes, ears, etc.). If information, artificial and natural, is essential to the world around us, why does it not play a bigger role in describing the material world? Well, Information is a rather vague, ill-defined concept. This spawns a number of questions. One such question is: How can we measure information?

Claude Shannon, the founder of information theory, invented a way to measure information. To measure information he tied messages to binary language: “to find the information content of any message, translate the message into binary code of the computer and count the digits of the resulting string of zeroes and ones.” This technique is called bit counting and the result was named Shannon information. The power of bits is astonishing. For example, a game of twenty questions produces a lot of information. The secret is to divide the possible answers into two equal parts. With good strategy, twenty answers yield twenty bits. The twenty bits result in a single choice among 1,048,576 equally probable possibilities.

The trouble with Shannon’s discovery is that it says nothing about the intended meaning of the message. Shannon’s bit counting strategy is quantitative rather than qualitative. Francois Jacob, a Nobel Prize winner, espoused that asking general questions led to very limited answers and asking limited questions turned out to provide more and more general answers. Shannon’s approach produced some limited questions that led to general answers. Some of these answers included that binary is the least expensive way to handle information and that digital processing is more efficient than analogue.

It seems that bit counting is a starting point for information problems. It is a powerful tool promising to be the key to higher levels of meaning in the study of information. On the other hand, will information, studied at any level, be of use in physics?

1. (20 pts – 5 pts each) Determine whether each of the following is a valid argument

or not.

a. All human beings are mortal. John is a human being. Therefore John is mortal.

VALID

b. If it rained today, my car got wet. My car got wet. Therefore it rained today.

INVALID

c. All horses are green. All green things are plastic. Therefore, all horses are plastic.

VALID

d. All cats are mammals. Some mammals have fur. Therefore some cats have fur.

INVALID

2. (15 pts – 5 pts each) Determine whether each of the following is an inductive or a

deductive argument.

a. Mary has observed 100,000 crows in the wild and all of those craws were

black. Therefore, all crows in the wild are black.

INDUCTIVE

b. All horses are green. All green things are plastic. Therefore, all horses are plastic.

DEDUCTIVE

c. 90% of all high school teachers are underpaid. Jonathan is a high school

teacher. Therefore Jonathan is probably underpaid.

INDUCTIVE

3. (15 pts – 5 pts each) Determine whether each of the following is a simple or a

compound sentence.

a. Mary and John went to France.

COMPOUND

b. Susan loves cats and dogs.

COMPOUND

c. The lion on the mountain started to chase the rabbit behind the tree.

SIMPLE

4. (20 pts) Using a truth table show that p ? [( p ? q) ? q] is a tautology (A

tautology in logic is a statement that is always TRUE).

5. (30 pts, 6 pts each) Compute the truth values of the following, given that A, B,

and C are true (1) and X, Y, and Z are false (0).

Assignment # 8

1. Ascending Order: 6, 8, 10, 12, 14, 15, 16, 20, 24, 25, 32, 34, 42, 56, 57, 62, 73, 75, 80, 90

2. Minimum = 6, Maximum = 90

3. Median of Population:

• n = 20
• 20 / 2 = 10
• (20 / 2) + 1 = 11
• The values of positions 10 and 11 of the population are 25 and 32.
• (25 + 32) / 2 = 28.5

4. Arithmetic Mean of the Population:

• 6 + 8 + 10 + 12 + 14 + 15 + 16 + 20 + 24 + 25 + 32 + 34 + 42 + 56 + 57 + 62 + 73 + 75 + 80 + 90 = 751
• 751 / 20 = 37.55

5. Truncated Mean (20% discard rate):

• n = 20, 20% of 20 = 4
• 6, 8, 10, 12, 14, 15, 16, 20, 24, 25, 32, 34, 42, 56, 57, 62, 73, 75, 80, 90
• 14 + 15 + 16 + 20 + 24 + 25 + 32 + 34 + 42 + 56 + 57 + 62 = 397
• 397 / 12 = 33.083333…

6. Winsorized Mean of the Population (25% discard rate):

• n = 20, 25% of 20 = 5
• 6, 8, 10, 12, 14, 15, 16, 20, 24, 25, 32, 34, 42, 56, 57, 62, 73, 75, 80, 90
• 15, 15, 15, 15, 15, 15, 16, 20, 24, 25, 32, 34, 42, 56, 57, 57, 57, 57, 57, 57
• 15 + 15 + 15 + 15 + 15 + 15 + 16 + 20 + 24 + 25 + 32 + 34 + 42 + 56 + 57 + 57 + 57 + 57 +
• 57 + 57 = 681
• 681 / 20 = 34.05

7. Variance and Standard Deviation of a sample:

• Chosen sample: 8, 10, 12, 14, 16

• Calculate sample variance:
  • 8 + 10 + 12 + 14 + 16 = 50
  • 50 / 5 = 10
  • [(10 – 8)2 + (10 – 10)2 + (12 – 10)2 + (14 – 10)2 +(16 – 10)2] / n – 1 = 22 + 02 + 22 +
  • 42 + 62 / 5 – 1
  • 4 + 0 + 4 + 16 + 36 / 4 = 15

o Calculate sample standard deviation:

• _ ?15 ? 3.87

8. Variance and Standard Deviation of a population:

• Chosen population (Same as chosen sample of question #7): 8, 10, 12, 14, 16
• Calculate population variance:
  • 8 + 10 + 12 + 14 + 16 = 50
  • 50 / 5 = 10
  • [(10 – 8)2 + (10 – 10)2 + (12 – 10)2 + (14 – 10)2 +(16 – 10)2] / 5 = 22 + 02 + 22 + 42 +
  • 62 / 5
  • 4 + 0 + 4 + 16 + 36 / 5 = 12
• Calculate population standard deviation:
  • ?12 ? 3.46

9. Calculate the geometric mean of 4, 5, 10:

• (4 x 5 x 10)1/3 = (200)1/3 ? 5.84

10. Calculate the harmonic mean of 8, 24, 40, 80:

• = [(4) / ((1/8) + (1/24) + (1/40) + (1/80))]
• = [(4) / (30/240) + (10/240) + (6/240) + 3/240)]
• = [(4) / (49/240)]
• = [(4/1) x (240/49)
• = 960 / 49
• ? 19.59