$1,000,000,000 or more

Given pathetic higher education in India, many worthy Indian students leave for US, Europe, and even Russia or Mauritius. This means they spend a lot of their money on education in other countries. This amount has been estimated to be $10 bn.

In the post I will point out another substantial loss to India, the total time wasted by students leaving India. This amounts to another $1 bn - $10 bn. How? Here is my calculation, try your own.

Let us consider a student preparing to go abroad. In that process, the student devotes most of his time to prepare for GRE, visa application, searching for university departments, application to different labs/professors for funding. Typically this means, the student would sacrifice about 1 year on the process, rather than doing something creative in India. In turn, our country is less productive.

Further, the student, typically BE or MSc, is employable in some industry in India. Even a BPO job would earn up to Rs. 3,00,000 in one year. Hence, the student is foregoing the salary and that much of productivity is lost. The amount is generally higher, for most students will be productive than being in a BPO.

If 1,50,000 students leave India each year for studies abroad, we can compute the total loss in productivity using the above two numbers (highlighted in bold).


TOTAL= (No of students) x (time lost) x (salary earned OR productivity)

= 1,50,000 x 1 yr x 3,00,000

= 45 billion Rupees

= $ 1 bn

There we are, India poorer by $1 bn, just because students are less productive in the time before leaving for abroad. The numbers used (time lost) and (producivity) are variables, and I have used intelligent guesses. Productivity is from average salary by a fresh graduate from our college. (Time lost) is average 1 - 2 years from my own experience.

IITs and Higher Education

On the day before yesterday (11 June) I came across a "LEADER ARTICLE" titled 'How Not To Build New IITs'. You can read the entire things on Sl(T)imes of India site. What's wrong with that? Plenty, which prompted this blog entry. This entry was also published as a comment, FINALLY.

Being an IITian, a lot better analysis was expected from Mr. Ganguly. He starts off by saying, "Being in IIT used to be part of the elan of belonging to a Fabian elite". Such a logic would suggest that IITs were meant to create an elite class. He later claims that, "Your place in social hierarchy at IITs was determined by one thing alone--- your GPA".

No, we do not want our higher education institutes to foster a sense of elitism. We all are citizens with equal rights and differing abilities, some are better at higher studies, others at something else. IITs are supposed to provide high-class education. Perhaps Nehru, and other planners had given up hopes of improving other universities at international level. It is a sorry situation, where most of Indians can not obtain international-class higher education in India. By reducing options (of other university colleges), IITs were made the elite. The reality, however, is that they never were of international class. No IIT ever ranked close to Harvard. So, claiming IITs of being elite schools is wrong in factual sense, as well as ethical.

As for Grade Point Average (GPA) being the sole indicator as one's ability to live life, Mr Ganguly is very wrong again. Perhaps someone like Mr. Gates or Mr Jobs, two most influential persons from the Silicon Valley, may not obtain GPA of even 5.0. That does not speak of their ability to innovate, enthuse and lead a team of technicians. From my own experience as a teacher (at a top-ranked engineering school) I can certainly say that GPA is a poor indicator of a person's understanding, and a narrow outlook at a student's ability.

However, the biggest failure of the article is that, Mr. Ganguly fails to see the larger picture about Indian higher-education system. Given the lack of world-class education, many Indians migrate abroad and never return. Despite (arguably) 80% of IITs deciding to stay in India after graduation, many others leave India, especially those who do not enter IITs. These include even my own students.

Demand for higher education institutions outstrips supply. By limiting the supply, our government has created a situation of scarcity and then played its own politics. Mr. Ganguly has chosen to focus only on this narrow point of reservation politics, which is unfortunate, for he has missed the larger issue at stake.

A logical solution for the problem is to just increase the supply of higher education institutes. If the government can not do so, it should allow private players to do it WITHOUT stringent (and silly) government regulations and interference. The present government has refused to relax its draconian rules and regulations: about who teaches, how much he/she gets paid, what are the syllabi, what are fees, etc. One is not even touching the issue of bribery to obtain licenses, so common in education department.

Mr. Ganguly, and other readers are referred to informative articles by Dr. Atanu Dey (refer to his blog ). However, We must thank Mr Ganguly for raising the issue of higher education in India, it is a worthy issue. We can only hope that more discussion leads to awareness about basic issues at hand.

Interference Mitigation

Vaishnavi worked on Median-based interference identification and removal. The basic idea is to treat the time-freq map of a given baseline as a 2-D array. See the above diagram for such an example, where the red arrow indicates one interference location.

We then take a small section of this 2-D array (say 32x32 matrix), where the 3rd axis is the intensity (or amplitude). We compute the median and standard deviation of the section (32x32 matrix). We then put some criterion of (median+7*sigma) for genuine data.

Amplitude > (median + 7*sigma) is treated as interference. This appears to identify interference quite reasonably. Check the following image, where black pixel indicates interference. Compare that with the top image, where most of the interference is identified.

There is some data loss due to over-correction. Even so, total data flagged is about 15%, which is quite good.

Interference Removal from Time-Frequency Data

We start with a flat time-frequency data, much like shown in the image on the left. This is VLA data (one baseline) observed at 325 MHz. The arrows indicate high-level and low-level interference in the data.

The most striking quality of interference, is that it is mostly confined to high 'spatial' frequencies. Here, I refer to spatial grey-level variation frequencies.

There are two approaches to remove / isolate such an interference:

1. To take an FT of the image itself.
2. Remove the high-frequency features (those belonging to fast-changing features.
3. For all pixels, use a large (21x21 pixel) filter to compute mean, median and rms of grey levels.
4. If the pixel value is greater than (mean+5*sigma) or (median + 5 sigma), then one can safely substitute median for the pixel value.
5. One could compute rms over the entire image to avoid being dominated by local features.

2008: Plans and Actions

Order not so crucial, but wish list is quite doable, right?

1. Get SAX paper out of the door.
2. Finish analysing MHD cube, how many chimneys will i lose due to sensitivity and resolution limits? Can we count holes in HI for a large number of MHD simulations?
3. B0809+74, what is the circulation time?
4. B0834+06, what is the problem with the circulation time at 35 MHz? How does the polar pattern look at higher frequencies?
   
5. 2-antenna interference on 3/4 major sources: from amplitude/ phase calibration of fringes, can we tell the sizes of sources with fringes observed?
   
6. Can we make crude images with even 10 different u-v tracks with a 2-antenna telescope?
7. Can we use the Moon for occultation studies?
8. Astrophysics - II course.
9. Meditate in Leh.
10. Maha working towards her higher studies abroad.