INFO 202 Fall 08 Blog

If you watched world class gymnasts Nastia Liukin or Shawn Johnson rake in the medals at the Beijing Olympics this summer, you may have noticed a winning beam score of “16.225″ or a winning floor exercise score of “15.650.”  So why is the scoring no longer on a 0-10 scale, and what does a “16″ even mean?

Though less intuitive to the spectator, these changes to the scoring system have come about in order better evaluate performance, categorizing it more discretely based on 1) execution and 2) difficulty.  In the past, judging has been characterized by deducting execution mistakes from a routine’s “start value” which is typically a 10.0 if the gymnast fulfilled his/her difficulty requirements.  Thus no deductions = “Perfect 10.”  However, there were distortions inherently built into this old notion of perfection: if two gymnasts both met the 10.0 difficulty threshold, but one gymnast added additional difficulty into her routine, this extra difficulty could not be reflected in the gymnast’s start value, as it was impossible to exceed 10.0. 
 
By re-factoring the judging schema, the concept of a maximum difficulty level no longer exists, and daring is aptly rewarded.  Though a gymnast can still receive a perfect execution score, there is no such thing as a perfect routine, because there are always new and more difficult tricks to potentially be incorporated.  In gymnastics, perfection has become a purely relative term, and by redefining the way in which routines are classified, a different type of champion — one who is flawless and fearless — is surfacing.

Article: 
http://www.nytimes.com/2008/08/06/sports/olympics/06scoring.html?_r=2&pagewanted=all&oref=slogin&oref=slogin

Lectures in the Syllabus: 
5. Concepts and Categories
7. Controlled names and Vocabularies

Fish or Foul?
http://www.nytimes.com/2008/09/02/opinion/02dolnick.html?pagewanted=print

Recently, Kate Stoeckle and Louisa Strauss, two recent high school graduates in Manhattan, undertook a science project of DNA testing 60 seafood samples from 4 restaurants and 2 stores around the city.  The results showed that 2 of the 4 restaurants and 6 of the 10 stores sold mislabled fish.

Tasters often misclassify foods in taste tests.  Expecations for taste influence many tasters’ judgment about what they have tasted. As an example, in a taste test in which testers are asked to classify wines, testers are often led astray by white wines dyed red, failing to classify them as white

Related Buzzwords:
Semantics
Taxonomy
Categorization
Classification
Compliance
Standardization
Precision

Related Lectures:
5; Concepts and Categories
7: Controlled names and Vocabularies
14: Social/Distributed Categorization

For you sports fans, here is an article that reviews the instant replay in
the professional tennis world.  In the highest levels of tennis in grass
and hard court tournaments, these days a machine called Hawk-Eye makes the
close “in or out” decisions instead of a human umpire.  The machine uses
video footage of the shot from many angles and then creates a 3-D
simulation of the ball as it approaches and bounces off the ground.  The
computer then decides if this simulation represents an “in” or an “out”.

In the context of our Information Organization and Retrieval course, the
first question I had about the Hawk-Eye machine was: how is its definition
of “in or out” different from the the human umpire’s definition?  And what
about the stadium or TV viewer’s or player’s definition?  At the end of
the article, it describes this kind of situation and gives an example of a
controversy in this year’s Wimbledon final between Nadal and Federrer.

The technology used in Hawk-Eye also reminds me of the use of video and
digital photography in the MyLifeBits reading.  In the case of MyLifeBits,
instead of the instantaneous capture of Hawk-Eye, you are trusting a
computer with long term information capture and retrieval of your everyday
activities and to assign relevance and meaning.  There are bound to be
moments of conflict between the user perception and the computer’s maybe
too perfect representation of the facts.  How are these conflicts going to
be resolved?

I hope these questions will be answered in lectures:2.  Issues and Contexts
5.  Concepts and Categories
15. Personal Information Management
or others

P.S.
Speaking of controversy, did you see Michael Phelps’ 100 fly swim at the
Bejing Olympics last month?  You need to see the finish from several
camera angles to be convinced he won.  At least I think he won.  Here is
the link to his swim on www.nbcolympics.com so you can decide for
yourself:
http://www.nbcolympics.com/video/modules/searchable/resourcedata/2211/60/video.html

Article Citation: “Hey, Robot Ref! Are You Blind?
Should the sports world replace human umpires with computers?”
Farhad Manjoo, September 2, 2008, www.slate.com
Link to article: http://www.slate.com/id/2199136/

 
16 Aug 2008, 0430 hrs IST, Nirmala M Nagaraj,TNN

URL: http://timesofindia.indiatimes.com/Bangalore/Rural_areas_reap_benefits_of_telemedicine_/articleshow/3369847.cms

Telemedicine (the use of telecommunications to assist in the provision of medical services) is making it possible for cardiologists, neurologists or radiologists to attend to patients in rural India. For the past seven years, through video-conferencing of patients and doctors, 85,595 ECGs and 25,000 teleconsultations have been done, apart from 1,06,000 thrombosis cases by the 56 telemedicine centres in ten states. Even the postal service (Hrudaya Post) is being used where trained postal staff feed the data online (prescription, X-ray, ECG report, angiogram) for specialist consultation, a review report is sent within 24 hours, and the patient collects the report at the counter or at its doorstep (for an extra fee).

Lectures

2. Issues and Contexts.

27. MULTIMEDIA IR (12/1) – X-Rays as Multimedia retrieved by medical personnel

http://www.techcrunch.com/2008/07/29/how-to-lose-your-cuil-20-seconds-after-launch/

Stealth search start-up Cuil (pronounced “cool”) launched its product on July 29th of this year, and was promptly subject to an angry backlash from its users. The start-up – founded by three former senior Google employees – claims to have an index size of 120 billion web pages (larger than that of Google’s, they say). On the day of its launch however, Cuil’s search results were not as rewarding. For example, a search for “Dog” resulted in 280 million hits on Cuil and 498 million on Google. Of course, quantity isn’t everything, but even in relevance, Google’s results were better.

The comparison to Google is but natural, since Google defines what search means to most of us today – search results that are relevant, but also photos, news articles, video files, etc. that complete the picture. It remains to be seen whether Cuil can offer a superior ‘universal’ search package to one that we’re already used to.

Relevant lectures: 21/22

This Pew Research Center article, entitled “America’s Four Middle Classes,” has little explicitly to do with IR technology. However, it does feature a new model for the categorization of the “American Middle Class,” which I think is a useful example for a discussion of the ways in which redefining data categories can provide new insights and sweep away widely held myths. This report describes how social survey data was used by researchers to segment people who self-identify as “Middle Class” into four new categories that describe financial stability – namely Top of the Class, Satisfied Middle, Struggling Middle, and Anxious Middle. The report demonstrates how within the self-identified category of “Middle Class,” there is a great variation in financial status, from relative economic comfort to the potential for financial hardship. I was personally drawn to this report because it demonstrates that simple recategorization of data can possibly lead to sweeping changes in social perceptions.

Here is an excerpt from the article: Life is considerably tougher for the Struggling Middle, a group disproportionately composed of women and minorities. In fact, many members of the Struggling Middle have more in common with the lower class than they do with those in the other three groups and actually have a lower median family income than Americans who put themselves on the lowest rungs of the social ladder. About one-in-six self-identified middle class Americans fall into the Struggling Middle.

Rest of article here. Full, 19-page PDF report of this project available here.

Relevant lectures: 5. CONCEPTS & CATEGORIES (9/15)

“A Social Network for Your Doctor, Pharmacist, and Insurer”
Washington Post, August 15, 2008
http://www.washingtonpost.com/wp-dyn/content/article/2008/08/15/AR2008081503269.html

Trends in social networking are extending themselves beyond more traditional social realms and are making their way into the doctor patient relationship.  WellNet Healthcare is launching a beta version of Point to Point Healthcare, a “social network” for patients, their doctors, and other members of their health care team.   Microsoft, Google, and insurance companies are also investing resources towards increasing the popularity of online medical records.

“Imagine a virtual health clinic: Your lung doctor and heart specialist can pull up your online medical profile and chat, via instant messenger, about your medications. You schedule checkups online, create a wellness journal or even rate your general practitioner. ”

This virtual health clinic sounds intriguing and certainly better than a waiting room.  Consolidated and readily available medical records and fast feedback between patients, doctors, pharmacies, and insurance companies can potentially lead to more efficient and less expensive health care.  Well Net already provides data about patients and their use of their health care plans to employers so that employers can evaluate their health plan offerings.  This new online network may provide additional information that allows companies to better prioritize aspects of health care plans important to employees.  Point to Point Healthcare and similar technologies might also encourage individuals to be more proactive participants in their personal health care by better and more frequent interaction with health care providers.

However, despite the potential increase in efficiency and patient access to information, this medical social network raises some potential issues.
First, doctors generally like IT that is easy to use and increases efficiency or decreases work.  When technology requires a training and adjustment period, it can potentially lead to a short term degradation in patient care and higher stress levels for doctors as illustrated in the reading “Electronic Health Records: Just around the Corner?” .  Patients using the site may not be tech savvy either, so the site must be easy to use in order to ensure quality information.

Secondly, some patients might not be interested in managing their health care information to this extent .  They may choose to remain disengaged and continue to consider the management of their health care data as a service provided by doctors and insurance companies.  Additionally, despite the fact that the program is only in beta and isn’t required, the potential diversity of users should be considered up front.  A large portion of the population, particularly senior citizens, the portion of the population seeking the most medical care, aren’t comfortable or even aware of social networking sites.

Privacy is also an issue.  Point to Point Healthcare and other online records systems will need to meet privacy guidelines set out by HIPAA.  As pointed out in the Washington Post article, the ramifications around the theft of personal health information are greater than identity and financial information theft, both of which are painful, but resolvable.  Private health information is either private or it isn’t.  The damage can’t be undone.

I think there is a lot of interesting potential in a service that links patients, doctors, and the rest of their health care team, but only if it can provide the privacy patients are entitled to and lets doctors do what they do best, treat patients.

Relevant Lectures: 2. Issues and Context, 15. Personal Information Management,  19. User Interfaces, Social/Distributed Categorization

http://arstechnica.com/news.ars/post/20080902-p2p-traffic-drops-as-streaming-video-grows-in-popularity.html

(ArsTechnica, September 2, 2008)

For the first time since the birth of peer-to-peer file transfers, such internet traffic seems to be declining.  In it’s place, it appears that streaming content from online providers like Hulu, YouTube, and the BBC iPlayer is growing rapidly as a major source of internet traffic. Presumably, people who would otherwise download television shows and movies from peer-to-peer sources are choosing these newer streaming video sites.

The upside of this for content providers is that such streaming video is often commercially sponsored and directly controlled by the copyright holders. For users, streaming video has the benefit of quicker start times, availability from any computer, and perhaps most importantly, being legal. The downside, of course, is that streaming videos can be taken down from a website at any time.

Regardless of the transmission method, internet service providers still need to contend with the rapid grown in internet traffic.

Relevant Lecture: 27. Multimedia IR

Buzzwords: Web 2.0, Tag

http://news.cnet.com/8301-13580_3-10026577-39.html
(CNET News, September 2, 2008)

Google has announced a new way to automatically tag photos containing human faces. This feature is called “name tag” and suggests proper tags for a picture once you tell it who is who.

Those who have used the iTunes after organizing their songs with tags may understand how tagging makes it easier to find and play songs. In spite of the convenience that tagging delivers, what makes users reluctant to put tags on their contents in various forms was the tedious nature of tagging work. In this sense, the Google’s new feature could be one of breakthroughs to turn untagged contents into tagged ones.

According to the article, once you’ve started identifying people in your pictures, you can tag about 200 persons in more than 100 pictures just in mere 15 minutes. Imagine how convenient it will be if you can retrieve a proper set of pictures from your huge picture storage by just putting in the name of the person you are looking for.

Despite some erroneous suggestions are made by this feature from time to time, I think that this attempt shows a new possibility how people can organize contents by tags more easily in the future.

Relevant lectures:

8. Classification
15. Personal Information Management
18. Metadata for Multimedia
27. Multimedia IR

http://www.pcworld.com/article/129917/ibm_researchers_take_on_video_surveillance_privacy.html

Video surveillance is increasingly common in America and other parts of the world. While cameras may be monitored in real time, they generally record video which can be reviewed later. This article covers two issues relating to video surveillance: privacy and retrieval.

The fact that cameras can monitor and record the actions of law-abiding people, in public, raises privacy concerns. To protect privacy IBM wants to blur the faces of ‘innocent bystanders’ [1].  The challenge is incorporating this into a product whose primary purpose is recording details of people suspected of wrongdoing. The two possibilies discussed in the article are 1) to automatically identify suspicious behavior and retain intact video only in those cases or 2) to store both the degraded and intact video and have separate access controls during retrieval.

The second part of the article discusses the information retrieval capabilities of current systems. These systems can automatically add metadata to the recorded video. During indexing, the system adds tags describing the colors and size of objects in the scene. Few details are provided about how queries are handled. The one example given is investigators, looking for a suspect wearing red, searching for the word “Red” to retrieve all video containing that color. 

Lecture:

  MULTIMEDIA IR
  METADATA FOR MULTIMEDIA

[1] Google recently began blurring faces in Street View:
http://news.cnet.com/8301-10784_3-9943140-7.html