1. 19 Recent Social Media Trends(Could think of that many) that will make you want to pull your hair in frustration #PissedOff #BullshitLists

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2. Bullshit Memes

#WTFdoyouwanttosay

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3. Random Personal Memes which make no sense

#BOROMIRisaLegend

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4. This

Im sorry I dont want diabetes.

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5. The dreaded comparison of legends- Maybe of epic greatness or stupidity.

#ThisComparisonbetweenindividualsofepicawesomenessorepicstupidity.

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6. Those Yo Yo Selfies with all the swag and the gold. Im Awesome \m/

#SelfiesArePathetic. #SWAG

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7. @CAD checked in @CafeGoodluck with @VBH, @NSS, @AAD. No one actually gives a shit where you are eating- other than your rectum.

#YourlifemaybeawesomebutIjustdontcare.
Because I dont care where you go with whom.

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8. Dude, I got a new awesome camera and I will show it off even though I dont know how to use it- PS- I spent my parents money.

#EveryoneisaPhotographer

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 9. Those © symbols on the most randomest, worthless photos.

#Pathetic. #Fact

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10. Plastic Emotions and nonsense internet jargon

#NotCool

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11. Unwanted Data

#BandwidthHogger

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12. @AAD,@RDV, @VSC, @AMD, @SSD, @VVK, @APA, @KSA, @XYZ, @ABC and 174 others were tagged in this post.

#Noonegaveafuck.

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13. Narcissist Depression- Sad But True

#Stoplikingyourownposts. #emotionsmakenosense.

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14. These Senti posts
 Mongo is a little Indian kid who has to walk 20 km to go to school every day. Every single time you like, share or comment on this blogpost, a National bank donates 1p for Mongo. With this generous donation that you make (simply by sitting at home), we buy a whip, and make the lazy bastard run.

#LikesCommentsAndSharecontributestoEducation

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15. Unwanted Public Respect. 

#UnwantedRespectExpressed #GloryhoggerAdmin

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16. Bogus Babajis- who give you babaji ka thullu 

Babaji is very powerful. All Bhakts share Babajis Blog on their walls and receive Babajis blessings.
All non bhakts post babajis blog link on wall of atleast 15 people in next 20 mins or else lead a forever alone life.
#Theseforwardssuck.

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17. These posts:

#ILoveMyMomButImnotsharingthisPic.

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18. Putting Random Quotes on photos of famous people and passing half baked cookies as wisdom.

##EinziegelsteinUwacha(Einzeigelstein Says)

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19. #OKnowImDoneIvebeenusingtoomanyhashtags. #Weirdblogpost #WTFisthis. #OhNo #Authorgonemad #WTFisthislist #Pissedoff #Irritated #Whomadethis #Killthemall. #Hashtags
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#TheTitleofthePostIsAlsoTheSortOfThingThatAnnoysYou-#Lists.(That is the first point in case you missed - Weird Lists)

On Rajanikants 4th Law of Motion

Title of the Paper:

On Rajankikants 4^th Law of Motion.

Authors:

Chinmay Datar 1.

Special Thanks:

Taniya Bapat 2.

Abstract:

The paper is written with a view of calculating the Rajani Radius(Rajanitrijjya) based on Rajanikants 4^th Law of Motion. The Law itself deals with the movements of superheroes such as Rajinikanth and Flash amongst others. The Law, and its following derivations should not be attempted by normal mortal human beings such as ourselves, for the force that would be exerted is beyond the biological capacity that the body is designed to handle. Superhumans (Heroes) with modified DNA and Superpowerful(and as of yet undiscovered) subatomic particles are the only things to whom the law may apply . The inspiration for this research was provided by a Taniya Bapat SMS forward, for which the author duly recognizes her inputs.

Index Terms:

Rajinikanth, Rajanitrijjya, Highspeed circular motion, 4^th Law of Motion, Persistence of vision.

Introduction:

Newton is credited to have formulated the first three laws of motion on which the whole universe is based. Well, the whole universe follows these laws except for some nutcases termed as superheroes (Rajani, Flash, Green Lantern, Superman, etc). To fit these heroes’ deeds scientifically, Rajani, the great, came up with a new Law- one that shook the earth beneath the feet of Shri Shri Isaac Newton.

Rajani states in his 4^th Law: “If you run at 100 km/sec around a tree, you can see your own back” [1]

While physically, it may seem impossible that this can be true, scientifically and mathematically it is quite possible. 100km/s roughly equals 100000m/sec, which is about 0.0003333 times the speed of light, and hence, speed which can be easily achieved by fast things, such as superheroes. This rules out the problem that heroes would need to travel faster than light. Also as the speed is quite fractional and nominal compared to the speed of light "c", relativistic effects and Lorentzian transformations can be ignored.

On Persistence of Vision and field vision of a human eye:

An important concept in this derivation is that of “Persistence of Vision”. Our eyes, for a short duration, store the image that it catches on its retina. The effect lasts for a very short time, however, if a body moves at that rate, it appears to our eyes that the object is in continuum.  An application for the same is the television, where about 25 frames per second and shown so that the picture appears continuous. From here we can calculate that per frame, 1/25 second is needed for it to be stored on the retina. i.e if the eye sees something even for a minuscule period of time, due to persistence of vision our mind “reads it” for 1/25^th of a second.

The second important concept is field of vision. Looking forward, humans usually have a field vision of 95 degrees as shown in the fig below:

Calculation of the Rajanitrijjya.

(Trijjya, Sanskrit for Radius) Rajanitrijjya, literally, the Rajani radius is the maximum radius that can be used by a superhero to run in a circle to see his own back. Certain assumptions about speed and radius were made to achieve the results.

Rajani 4 says that you need to run at 100km/sec which gives a speed of 100000m/s. The velocity will be linear velocity. V=100km/s. ω would be v/r, and will depend on the radius. 

Scenario 1:

The superhero only sees forward, and has no field of vision while running:

In this case, the superhero need to be at the same spot that he started from in (1/25) of a second. Only then, will he be able to see his own back.

The distance covered by the superhero would be equal to the circumference of the circle on which he is running.

Thus, we have,

D= s*t;

2*π*r = 100,000 (m/s) *(1/25)(s)

2* π *r= 4000m;

r= 4000m/(2* π);

r= 636.66 m, which is roughly 637 m.

However this will be true only if the Superhuman only looks straight ahead.

Scenario 2:

The superhero possesses a human field of vision

The superhuman, at the end of the day is a human, and thus, possesses a field of vision, which Wikipedia states is 95 degrees.

Using this, the human may be able to see his back at a position which is not at the exact same spot on the circle from where he started running, but rather on a point much earlier to that.

A quick glance at the following circle will help answer our doubts.

 

Total field vision is 95 degrees. Assuming symmetry, and assuming the superhero is not cross-eyed (rather doubt it) field of vision per side along the line of symmetry will be: 95/2 = 47.5 degrees.

At any point on the circle, the superhero is running tangentially to the radius at that point. He thus makes an angle of 47.5 degrees with the point from where he started (A) from a point say B. this means that the angle between the furthest vision and the radius is 42.5 degrees. Reminding the reader that the circle has a constant radius (Polar r=a), an isosceles triangle will be formed, subtaining an angle of 95 degrees on the center.

Thus, the superhero would need to run a distance equal to the arc length equivalent to 265 degrees.

Thus, distance covered will be:

(265/360)*2* π *r.

This will be equal to s*t

(265/360)*2* π *r = 100000*1/25

(265/360)*2* π *r= 4000;

R= 4000 *360/(265*2* π)

r= 864.8 m.

Thus if the superhero runs at a radius of roughly 865 m from the centre of the tree, he should be able to see his back.

Now, the widest tree has a diameter of 32 m(from wiki). Thus, radius is 16m. For his own safety, let the superhero run around the tree at a distance of 20m.

Thus,

(265/360)*2* π *20 = s* (1/25)

Thus, s= 2312.5 m/s.

This equals 2.3125km/s

This is just the 1/50^th the speed at which Rajani can run. No wonder he easily sees his own back!

Superhumans having such capabilities have been discovered. The wait is for the discovery of the fundamental units that build up these superhumans. These fundamental particles, although as of now only imaginary have been assigned the term Rajanions by VERN (Vadheev Engineers Research Network)- the Research branch of IVEE.

References:

[1] SMS, received on 14^th Sept, [Taniya Bapat].

Acknowledgements:

The author would thoroughly like to thank Taniya Bapat- still a student for inducing a thought process to formulate the concept of seeing your own back while running.

All material is copyrighted to the IVEE. Any person imitating any research or stealing it (especially non-members) and using it for ridicule, will be given 50 whiplashes. The author or for that matter anyone at IVEE shall not entertain questions regarding how Rajanikant reaches speeds of 100km/s- Go ask Rajanikant himself. 

People wishing to promote fun side of Science and Math can contact IVEE chairmen- Chinmay Datar or Sumedh Dhabu to obtain and a lease to use the vadheev proofs.

Digital Counter Paradox

Title of paper:

On Chinmay Datars Digital Counter Paradox

Authors: Chinmay Datar 1

Special thanks: Sumedh Dhabu 2 Shreyas Bhaban 3.

Abstact:

A reverse thought experiment generated out of the idea to mathematically model a situation of a couple moving into a locked house and generating an offspring and leaving the house only for another person to enter the house.

Index terms:                                                                                                           

Digital Counters, Flummoxations.

Introduction:

Completing work related assignments is kind of boring. Especially if its an assignment that does not make you think out of the box. IT assignments are mostly of such non-creative types. I guess they strive to stifle your imagination and creativity. My new job, though interesting, is making me lose my creativity to a certain extent. To not go completely mad, I try to come up with mathematical formulations and spoofs, to keep thinking and not get engrossed in the world of IT.(I have no idea why its called technology here). Ive come up with some very interesting theories- one about complex numbers has already been shared.. Today, early in the morning, when I have nothing to do, I was thinking of a thought experiment. The experiment is leaving me flummoxed. Why me, it has even left the Grab-all and gobble scientist Shreyas Bhaban (who works not coz he loves his work, math and science, but coz he wants to grab all the money around) dumbstruck.

Assume a room where there is a single door for entry and exit. The room has no other possible entry or exit points.Just the one entrance/exit. Whats inside the room is unknown, so basically its a black box. On outside of the door, there is a digital counter which can count anything real from -infinity to +infinity. Whenever anything enters the room, the counter is automatically incremented by one. When anything leaves the room, the counter is decremented by 1. All elements are counted individually. Elements enter the room when the door is opened at 2n-1 opening and elements exit when door is opened at 2n opeing.( n =1 to infinity)

Although the inside of the room is unknown, what we do know is that the room performs a simple operation of square rooting anything inside at even numbered door opening.

Let us assume that we push the number "1" in the room. The counter will increment to show that there is 1 entity in the room. Now when we open the door again, it will be the 2nd opening, so the square root rule will be applied on "1". This will result in two results: +1 and -1. as it is the 2nd opening, the elements inside will exit. As two elements will come out, the counter will decrement twice, and show -1 as the number of entities inside. Now if we open the door again for a 3rd time, and force "1" inside again, the counter will increment by 1, and show the number of entities inside as "0". Practically this is not possible as we ourselves have pushed "1" inside the door, and definitely know that physically there is an entity that exists inside. 

So, now, a paradox has been generated about the number on entities inside the room. Mathematically, the counter reads zero, but practically, we know it should read 1. This paradox has been labeled the Digital Counter Paradox or DC paradox.

The paradox has been generated for exclusive use for IVEE. Any reproduction will be charged with 50 whiplashes and brain-washing. The paradox is created to confuse people. People attempting to solve the same with mass-energy-momentum conservation or any other methods shall be deemed too nerdy to be vadheev and be permanently disqualified to visit IVEE blogs and posts.

The Dud Social Networking Experiment

These holidays have been damn frustrating! Considering that they are the last ones ill be having with my college buddies, makes them even worse. Time, especially the afternoon, combined with the heat crawls at a snails pace. Quite astonishingly, there is nothing worthwhile to do! In this emptiness and boredom, a way out is to do stupid experiments. One such bored of the holidays experiment was based on the hypothesis that was drawn from observing social networking sites for long enough.

The hypothesis is that Girls get unnecessary attention on such social networking sites. A girl does anything, and there are hundreds of comments for even the silliest of things. Guys do something awesome, and there is hardly in discussion about that. Not all girls fall in that category, but most do. I wanted to test the hypothesis, already knowing what the results were to be. However, I slightly modified the theme, that me, and a girl would upload the same photo, and see the results depending on the number of comments/likes for the picture.

Fortunately, my trusted accomplice for this act was none other than my extremely nerdy and awesome friend Siddhi Soman. Siddhi, to those who do not know, is an extremely hyper-energetic person who excels at whatever she does- be it academics, badminton, rowing, having a row, brawl- you name it, she is good at it. No wonder she was the Best outgoing person from college. She is also an extremely terrifying person, and many a times has given me nightmares ( by chasing me around the college and slicing my head open by smashing rowing oars on my head in my dreams) . At 5 feet 2, Siddhi, is an awesome model who if in the right mood gives off awesome emotions for the camera. I had clicked a super picture of hers last year after the college dinner when she was doing her normal nautanki. The picture is awesome actually! its one of the better portrait shots that I've clicked. So it was with this picture that I decided to experiment.

The picture is a black and white portrait style photo of Siddhi expressing a typical Filmy dialogue "Nahiiii" ,and its one of my favourite ones. I had uploaded the pic on Facebook for my new album Life in B&W a couple of days ago, and received scant appreciation for an awesome photo. So, I persuaded Siddhi to upload it on her wall. And Lo behold! in a mere 24 hours, the photo on Siddhis wall had more likes and comments than what I had on mine! Its a matter of jealousy when someone gets into the limelight for things you do isn't it! I am not that bothered, as I get enough publicity through other means anyway, but a person of faint heart ought to get jealous. Anyway, I'm putting up the picture here as well. Its right below this text.

Stupid experiments usually have stupid conclusions. In my case, the experiments have vadheev conclusions. Linking any observation to anything is a prime ace I have up my sleeve to create lots and lots of noise. This time, even though the topic of discussion was well proven, just to have a new outlook, I attempted something else, which unfortunately by my standards is rather dull.  

Anyway, I came to the following conclusions after carrying out this act of nautanki:

1) Siddhi is an awesome subject for taking not just nautanki photographs, but normal photos too.

2) Girls do not usually like or comment on awesome clicks of other girls if posted on a boys profile.They get super jealous that its not their Photo.

3) Girls go hyper if the same thing is posted by the girl who is in the picture. "Awwww howww cute re!" etc etc

4) Boys go ballistic over the portraits. "You look awesome blah blah blah(General observation, not applicable to Siddhi. :P)

5) Compared to other girls, Siddhi has received less number of hits. This is probably because she is a good girl.(ya right!) I was more inclined on describing her as a hopeless aspiring model, but she is not. If I say so, my head gets sliced in two.

6) Social Networking sites are pro female.(rather grudgingly accepted)

7) Like it or not, girls receive free, fukat, unnecessary, pointless attention on Social Networking sites. 

8) Im better off writing posts which spoof engineering and mathematical terms rather than experimenting on stupid social networking.

Now, Ive lost the confidence in social networking experiments. Dont know why I carried this depressing experiment in first place. Maybe, by using Siddhi as a bait, im trying to enhance my publicity on social networking sites. :P (Not that I need it, but its fun, and Id have done it anyway- Im not someone who is shy of carrying out a PS :))

Never mind, if this post becomes a hit, then I give half the plaudits to Siddhi for helping me conduct a stupid experiment. If it bombs, its entirely her fault and I have nothing to do with it. But going forth with my cocky and arrogant self confidence, I have all faith that this will be a hit, and Siddhi will get a shot at fame that, unlike most other girls, is atleast earned! 

K-means Clustering

One of the biggest advantages of being an engineer is that we can apply concepts that we have learnt in our syllabus to virtually any problem in the world, and try to come up with new and innovative ideas to deal with these problems. We see a number of examples of engineers coming up with bizarre applications. Why refer to other engineers. Me and Anant Devi have already come up with Datar-Devi Approximations for Exams. A cousin of mine, by profession a computer geek, by passion a world class singer came up with another of such fantastic research of the relation between the frequency of your arm swing while walking and your velocity. Amazing stuff. Really, there are no boundaries for us engineers. All we need to do is think a little bit out of the box. Today, I shall be discussing one of the more important algorithms that we have in signal processing (esp speech processing)-the K-means algorithm and its application to one of the major headache for all college guys- the right girl.

Now, engineers, or for that matter most of the guys are hopeless when it comes to selecting the right girl for them. They just fall in love without thinking! (I know Ill be called a hypocrite- I too have been down this path on multiple occasions. MadB will be the one who will accuse me first, but yeah, who takes her seriously when she accuses!) And then they end up fighting with the girl over petty issues, and then act like crybabies.  What guys need is patience. This post is dedicated to all guys who are eternally confused as to what they will do with their love life and provide with insight of finding the best possible partners.

Let me introduce you to our quirky and extremely challenging to implement in matlab friend of ours, The K-means algorithm, which I will use to address your woes. To the unwary and uneducated, K-Means is a clustering algorithm that we commonly use for vector quantization. A given n dimensional ( n corresponding to various parameters) vectors when quantized into a data of say n bits is mapped to its nearest encoded bitstream which gives minimum mean squared error ( the message to which it is encoded is called the centroid) . One problem is- how do you assign the centroid. Well, it is simple. Its nothing but a mean of all the vectors in that cluster. So, dynamically, the centroid will keep on changing until all entities converge to a single point.
Mathematically, the K-means algorithm will be given by


Given a set of observations (x₁, x₂, …, x_n), where each observation is a d-dimensional real vector, k-means clustering aims to partition the n observations into k sets (k ≤ n) S = {S₁, S₂, …, S_k} so as to minimize the within-cluster sum of squares (WCSS):

where μ_i is the mean of points in S_i.

[wikipedia.]

Pictorally, this can be represented as:

• 

  1) k initial "means" (in this casek=3) are randomly selected from the data set (shown in color).
 
• 

  2) k clusters are created by associating every observation with the nearest mean. The partitions here represent theVoronoi diagram generated by the means.
 
• 

  3) The centroid of each of the kclusters becomes the new means.
 
• 

  4) Steps 2 and 3 are repeated until convergence has been reached.

Now, coming back to the notion of the application of K-means for the problem to be addressed. Here, in k-means we have a n dimensional vector. Let these n dimensions be all the points you will look for in the girl. (My vector, is 20 dimensional.) as shown in the figure above, make three categories- Girls who you like.
Girls who you do not like. and Girls who you think are OK. Each girl will have her own unique n dimensional vector. Assign a self defined centroid for all three of them.

As you grow older through your engineering years you come across a number of girls, not necessarily in your college, who you may have considered as your potential ideal match, or as your worst possible match. This will give you quite a bit of database for statistical analysis. When you see a girl in either category, observe them for a few days, and adjust their vectors, and keep them updating. after a sufficient amount of time, the vectors will have reached a saturation point and will not alter. this is when you apply the k-means.

now, it is highly unlikely that we will get a girl who coincides with our self defined centroids. If that happens to be your case, you are one hell of a lucky ba***d. But for people like me, who have some impossible conditional vector entries, this is almost impossible. Also, it is highly improbable that you will have a girl with some qualities from girl B who has some desirable qualities and girl C who has other desirable qualities. Lets face it- its unlikely. So, the best solution is to find the "vector" which will give you the least mean squared error at the output of the K-means. The girl corresponding to that vector is the one you go for!

Just to conclude:

If you like a girl, you have to wait for some time to be absolutely sure that she is the one that is perfect for you. Observe. Make mental notes of all the small things she does. (ofcourse this advise is only for those who are looking long term.. those interested in short term can jump ships whenever they want!). Make a mental note of what you want your ideal girl to be like beforehand. Ive received a lot of flack for my ideal girl, who can be found here, but nevertheless, do it.  Jot down all the points you want in all of them, and get ready to run the K-means algorithm.It works!!

(Personally, I dont recommend this approach- I havent done it for myself, and probably will not do it. Im more of a hopeless old school- fall in love arbitrarily kind of person to try this out. I am not suffering that much, and I am happy with the things as of now. No need for me then! This analogy was made purely to showcase the versatility that an engineer can adopt to make even the simplest of the things mathematical and complex. )

Mathematics of an Exam

Guess what. I am nearly done with another set of exams. No matter how much you try to shoulder arms at them, they make you go on the back foot and defend. Now that Im done with the theory exams, I am freely able to punch my practicals through the covers! No worries. My timing in the practical viva is as immaculate and as elegant as those of Sachin Tendulkar on the field. (Forgive me for a cricket like opening, but im watching India thrash NZ by Innings and some runs, so the effect rubs off..)

Now then, coming back to the point, as this was my 7th semester in the college, I have given a total of 14 exams plus a number of 10 mark tests. A large enough sample size has been generated through the experience of me and my friends to draw out the following conclusions about the time near to exam. These will be known as the Datar-Devi Approximations, after its researchers, Datar and Devi.


To start of with. Let 'T' be the time left for an exam. This is usually about 2-3 days for a typical COEP paper, for which one can actually study. For simplicity we shall assume that T is a rectangular distribution. from -T to 0.
However, we never start studying at the start of the rectangular function. Studying is a statistically boring process. We usually start our studies at an arbitrary time instant H, after -T. Again, this will be a rectangular distribution over T.

Now, as it is statistically observed, attention span is dependent on H. let Asp be the attention span.

 

This will give you the attention span that you will get, depending on when you start studying. This is a critical factor for getting good marks. ideally, toppers have H close to T.

The second important point that is under consideration is Number of calls you make asking your friends "How much timepass you have done?" this can be denoted by N(h). Number of calls before exam are way more that those on ordinary days.
N(h)=e^2kh.. k= Phony constant. the derivations for above terms are extremely complex and is beyond the scope of timepass. So, it has been left to the Chinese to come up with the proofs for the same.

The third important factor is time you end up swearing at and cursing your Professors. Now, as the trend is, we curse our profs as being useless and incompetent much more during exam period than normal.This analysis is extremely interesting, and thus, has been discussed below. Now, not all professors are bad. some are actually superb. so lets have a sample size of N professors.
Let us consider r activities- such as teaching, setting papers, fluency in speech etc.
let 'p' be the probability that the teacher is good.
so, (1-p) is the probability that the teacher is rubbish.
then, assuming a binomial model and taking average over given number considered, we can say that the swearing coefficient is






The fourth point considered in this treatise is based on pure statistics. The point is know as Chinmays attraction law. "As exam time nears, in D Days, your feelings towards an arbitrary girl goes on increasing to the exponent".Here, γ(gamma) is the attraction probability. γ is dependent on several factors such as the nature of the person, the college where he is studying etc. If γ is the attraction probability, then, the attraction coefficient can be given by  




However, in colleges like COEP, as there are very few good looking girls, and the fact that the college is filled with nerds, γ is negligible. So taking a Taylor series expansion, and ignoring higher order terms of γ ,
we can say,

The next important point is concentration span. You tend to concentrate very little while studying. breaks are frequent. Let B be the number of drinks/snacks break you take in between a span of 3 hours- a statistically important variable as all papers are 3 hours long. Then, concentration span, CSmax will be:
CSmax= 3hours/B.
Usually this value is quite low, owing to the statistically high value of B (12-15 in normal cases).
The analysis of B is also again very complex, and has been left to the Chinese.
One thing we know for certain is that CSmax is inversely proportional to t, the time before exam.

The next factor is the ratio of useful study to time spent on Facebook. This is called as the phace inverse ratio.

Now, PIR= (T.i.m.e.o.n.a.b.o.o.k/T.i.m.e.o.n.f.a.c.e.b.o.o.k.).
cancel the common terms in the equation, we get,
PIR=(1/face)

It has been statistically proven by the likes of our peers Shriram Kardile and Sahil Patwardhan, that time spent on Facebook is roughly 5 times the time spent on reading a book.
so, it can be concluded that PIR=(1/5)
(from their publications Facebook is more fun that studies. Kardile,Patwardhan and Datar.)

Ok, so I  guess these many factors are enough to formulate the time remaining for the exam T.
We can conclude, that T, the time to exam is directly proportional to:
1)Attention span
2)Swearing time
3)number of calls
4)coefficient of attraction
and is inversely proportional to
1) Concentration span.

Thus, we can mathematically conclude:

Introducing the constant of proportionality, the PIR to the equation to get rid of the proportionality sign and substituting the values for respective coefficients, we get

  Thus, finally we have arrived at the examination formula.

Original research carried out by:
Chinmay A Datar
Anant M Devi.
Helping Hands:
Sumedh Dhabu
Virendra Kakade
Abhishek Ambede.

References:
Probability and Random Processes
-Stark and Wood. (3rd years, see, its not that bad a book. has many useful applications afterall)
Why facebook is better than book
-Sahil Patwardhan, Ajinkya Rao
Facebook to book ratios
-Shriram Kardile.

We thank all our friends for supporting us throughout the research, and are hopeful that our efforts will be awarded at the IEEE conference of vadheevpana.
-P.S- mathematical errors have been deliberately introduced to hide original equations and research.
-Authors.

Say NO!!

These holidays have been extremely frustrating. There is hardly anything going on. I am spending almost all my time at home playing or sleeping. Its infact so frustrating, that i am having online conversations about anything and everything.

One such conversation, with Rujuta, bore some quite funny results.Rujuta, to those who dont know, is my abrrevations teacher, and teaches me SMS language on chat.However, I guess she was also very bored. Thats why, deviating from our normal "bhankas" chat, we started discussing various scenarios about the possibility of me going on non-existant and imaginary dates, and started taking the micky out of it.

One such scenario was that if that imaginary girl asked me out.( as in proper asked me out.) How would I react? Well, obviously i was dumbfounded. If such a situation would actually occur, i think i would end up laughing. But then, she wanted a serious answer! So out of nowhere, i came up with " I will tell tomorrow"; which is really confusing. See, I thought I was telling that to the imaginary girl, whereas Rujuta thought that that was the answer to the question how would i react!! When they say, confusion creates laughter, they mean it. We were laughing over this for the next dont know how long!!

Well, at night, i made up my answer to reject the imaginary girl. But then I had to make up some way to say No!! you know- just confuse the girl, let the no parachute down instead of accelerating..so the next day we were discussing various ways of saying "No", and are actually still discussing them, and coming up with new, witty rejections, for the benifit of mankind. (See, rujuta, I am sharing credits! :P")

Here are a few that were my personal favourites.

1) Look at the girl... then look over your shoulder to an extremely pretty girl... then look back to the girl,and acting all surprized say " Oh.. sorry... am i in your way??"

2) say.. " I am sorry that i have to say No, as I really feel about your safety after this . Actually i would have said yes, but then your parents would have put you in the Mental Hospital!"

3) " If you are asking me out, You must either be Mad, Crazy, or totally whacked up. I only go out with NORMAL girls!"

4) "My dear, lets get the alcohol out of your system and then talk.... do you want to start puking??"

5)" you know, my mother is really scared of Ghosts. I dont want to give her a hear attack by going out with one"

6) " I am on a perilous path to enlightenment, which spreads to people who you love, and I am in no mood to SHARE"

7) "You are so hot, that if i even stand next to you, Ill vapourize, leaving you single again, and sad... so why take the chance of you getting sad?!"

8) then there is the classic one... " I am already set up somewhere else!"

There will be more, when we come up with them. till then laugh on!!
by the way, this post is meant as humour. I do not think that anyone should actually use them, unless you want to get hammered by a chappal.:P

THE Ideal girl.

Recently, i updated my profile on one social networking site. It had various questions like Activities, Interests, blah blah blah.But what was interesting was that it had a section "Ideal Match". just to be sarcastic i wrote that it would be 7-1 thrashing of Roma by Manchester United. But then, it got me thinking. Who was my ideal match?? What would be her specification/ qualifications?? After deep pondering, I came up with the list of things that my so called "Ideal Match" should have. Here is the list:

1) She should have an IQ above 130. But at the same time, her IQ should not be above 140. it becomes too nerdier above that.

2) She should have a good taste in music, and she should be a fan of Hindustani sangeet(shastriya sangeet).

3) She should be able to sing, so that if time arises, we could raise funds by arranging music concerts.( I am potent at playing many musical instruments. ;))

4) She should NOT be a shopaholic, but conservative in matters of purchase.

5) She should dislike all alchoholic drinks and related dope.

6) She should HATE Shamrock Khan.

7) She should agree with me on the point that Romantic Hindi movies are crap, and watching them is a waste of time and money.

8) She should not nag me to go to bed early or at 10.30, and should not have a problem with me waking up at 5.45

9) She should have long hair.

10) She should appreciate Sarcasm.

11) She should not be scared of stupid things like cockroaches, lizards and cats.

12) she should be able to make Phansachi bhaji, sol kadhi, aloo chi bhaji, kelyacha partun and other typical koknasthi dishes.

13) She should not have arguments with me if i go to play or watch football.

14) She should be able to make a variety of cuisines, notably Italian.

15) She should have a good sense of humour, and should be able to pass on the spot comments of any nature on anyone in the vicinity.

16) She should be a good teacher, and should teach me all the things she is good at.

17) She should be able to laugh if someone makes fun of her.

18) She should have a decent figure, and decent look.

19) She should not be a show-off, but at the same time should be able to do loads of maaz.

Last, but the most important one:

20) She herself, or any of her very close relatives MUST be a dentist, so that i can get all my tooth works( mostly root canals and ceramic teeth) done for free.


NOW, everyone will know why I am single, and why will i always be single!!
Since, i do not intend to stay single for eternity, any girl who falls for me, will be considered as an "ideal match" if she passes half(10/20) of the above checkpoints.
please note that numbers 1,9, 12,18 are compulsory. girls having number 20 on their resumes ticked will be given special consideration. [:)]

thanks for reading all my nonsense.