Sokushinbutsu (Self-Mummification) - Buddhism, 1/1000 ways to die………….

I thought this self immolation video is too emotional, (it was done to protest and bring attention to the world the prosecution of Buddhists), how WRONG AM I?????

Sokushinbutsu were Buddhist monks or priests who caused their own deaths in a way that resulted in their mummification. This practice reportedly took place almost exclusively in northern Japan around the Yamagata Prefecture. It is believed that many hundreds of monks tried, but only between 16 and 24 such mummifications have been discovered to date. The practice is not advocated or practiced today by any Buddhist sect. The practice was thought to be extinct in modern Japan, but a recent example was discovered in Tokyo in July 2010.

For 1,000 days (a little less than three years) the priests would eat a special diet consisting only of nuts and seeds, while taking part in a regimen of rigorous physical activity that stripped them of their body fat. They then ate only bark and roots for another thousand days and began drinking a poisonous tea made from the sap of the Urushi tree, normally used to lacquer bowls.

This caused vomiting and a rapid loss of bodily fluids, and most importantly, it made the body too poisonous to be eaten by maggots. Finally, a self-mummifying monk would lock himself in a stone tomb barely larger than his body, where he would not move from the lotus position. His only connection to the outside world was an air tube and a bell. Each day he rang a bell to let those outside know that he was still alive.

When the bell stopped ringing, the tube was removed and the tomb sealed. After the tomb was sealed, the other monks in the temple would wait another 1,000 days, and open the tomb to see if the mummification was successful. 

If the monk had been successfully mummified, they were immediately seen as a Buddha and put in the temple for viewing. Usually, though, there was just a decomposed body. Although they weren't viewed as a true Buddha if they weren't mummified, they were still admired and revered for their dedication and spirit.

Reading #8. A Lightweight Multistroke Recognizer for User Interface Prototypes

Comments on Others:

Youyou Wang 

Summary
           The paper describes $N recognizer, a lightweight, concise multi-stroke recognizer, which is a significant extension to the $1 uni-stroke recognizer.  The $N said to be capable of user defined complex gesture identification, customization, and operate at speeds supporting fluid interaction (not sure what it means though???). $N is an extension of $1 to overcome limitations of that version, such as uni-stroke nature, failure to recognize 1D gestures, and rotation invariance. More specifically, the $N recognizer is implemented to use with rapid prototyping as way of quickly incorporating it to user interfaces with small loc size.
           The intuitive idea behind the $N development is to support rapid prototyping applications by eliminating the need of permutations of multistroke gesture and enable to enter only a single version of the gesture and use it for recognition. This is done by creating unistroke permutations of the multistroke at the define time and then using those for comparison at the run time. The $N uses automatic differentiating using a threshold to identify 1D and 2D gestures so that 1D’s can be preserved its aspect ratio.
           The paper also describes $N limitations, such as provisions for scale and position, and not using gesture features. 

Discussion
            First the use of name $N kind a amusing, may be they took the idea of $1 literally and replace 1 by N to represent the idea of multi-stroke possibility in their algorithm recognition compared to $1 recognizers uni-stroke nature. But I guess $1 recognizer authors used that name to represent both how simple it is, less expensive (shorter implementation time and small size) and uni-stroked. But when it comes to $N, the idea comes to readers mind is this thing N times expensive to implement (that much complex) than $1 recognizer (don’t laugh, that’s how I feel).
           One of the best goal of the $N as I consider is the ability to employ recognition with minimal input support (just a single multistroke entry) compared to other available recognizers including $1.  The use of just the Euclidian distance for comparison between the candidate stroke to permutations unistroke is questionable, and in my opinion not the correct technique to do so. May be a RMSE value between the candidate and the unistroke permutation may be a good idea to verify the accuracy and may be to increase the performance.
           The $N requires separate step to do the recognition of 1D from 2D, and in my opinion this can be avoided by using size invariant algorithmic design, may be a comparison based on the basic segment structure (example: a square consists of similar lengthen 2 horizontal and 2 vertical lines, and a triangle consists of 2 slanted and 1 horizontal lines).

Find the paper here. 

Reading #7. Sketch Based Interfaces: Early Processing for Sketch Understanding

Comments on Others:

Chris Aikens

Summary
           The paper discusses a novel approach of developing an interface which feels as natural as a paper but smart enough to understand the user’s intension and identifying sketches to a geometric shape. More specifically the work is intended to provide natural sketching and have the sketches understood. Also the authors state their intension of this work by giving user a system with unrestricted capabilities, such as drawing a rectangle clock-wise or counter clock-wise or drawing it with multiple strokes and still which is able to identify by the computer, like how people perceive things in the real world, the geometric shape rather how it was drawn.  Also note that the authors specified their domain as mechanical engineering design which dives added difficulty and complexity into sketching in this domain. Therefore the paper states that preprocessing steps like finding corners, fitting both lines and curves particularly important.
           The system design consists of approximation, beautification and basic recognition in the preprocessing stage. According to the paper, approximation fits pixels to lines and curves, Beautification modifies the output from approximation to make it visually more appealing, and finally Basic Recognition do the interpretation of the strokes, like sequence of 4 lines as a rectangle or a square. Subsequent recognition into complex structures handles by some other system in the design. The approximation consist of vertex detection, which is based on Average based filtering to find extrema corresponding to vertices while avoiding those due to noise. 

Discussion
           This paper particular grabs my interests due to its nature of regarding sketches as graphic objects and doing preprocessing before recognition to break them into basic objects (lines, curves etc). I consider this technique a sort of best way of tackling sketch recognition problems (just my personal opinion).
            The paper discusses vertex detection by the average based filtering which is on curvature graph and speed graph thresholds. I’m just wondering is there any other sophisticated ways to find the vertexes than this particular technique? In my experience, examining pixel distribution (neighboring pixels) is a hard problem; I’m interested in knowing something simple (Dr. Hammond mentioned tools to do this, am I missing something here?). Also I’m skeptical about using just the mean of the curvature data or speed data, a single higher order noise signal may ruin the whole detection process.   Also the Beautification is based on adjusting the slopes, but may be thickening the line and then skeltoning it would be a better choice, because slope adjustments may weaken the intended stroke appearance.
              In my personal opinion, the paper is lacking the required recognition design as a description which makes it more abstract to readers when it comes to the so called “higher level recognizer”.     

Find the paper here. 

Reading #6: Protractor: A Fast and Accurate Gesture Recognizer

Comments on Others:

chris aikens

Summary
            The paper describes a novel gesture recognizer using a nearest neighbor approach (I assume KNN), to recognize unknown gesture (testing sample or runtime sample) based on their features (or similarity) to the known gestures (training samples). The author states that simple, template-based recognizers are much more usable (advantageous) than its peers (sophisticated gesture recognition algorithms) in situations where personalized gesture interaction required.
           The Protractor preprocessing of gestures said to transform the 2D trajectory of the gesture to a uniform vector representation and claimed to be applicable to both invariant and orientation sensitive gesture sets with different aspect ratios. The paper further describes Protractor design which is similar to several of steps involved in the $1 recognizer including preprocessing with N=16 samples as opposed to N=64, and noise removal using the resampling. But the author sates that the Protractor does not rescale as of $1 recognizer therefore it makes it to even recognize narrow gestures such as horizontal or vertical lines.   

Discussion
           The paper discusses a simple but effective way of developing a gesture recognizer using an available feature classification algorithm, nearest neighbor. Even though claim of Protractor’s superiority compared to other gesture recognition is stated, in my opinion more performance evaluation needed to keep it in the firm ground (comparing it just to $1 recognizer is simply not enough to claim its superiority over other algorithms).   But I kind a biased and like the authors idea of comparing it to $1 recognizer, as I mentioned this as an advantage in my discussion on $1 recognizer paper. This may be a good point to consider when creating gesture recognizers, comparing it to both Protractor and $1 recognizer (both claims to be simple to implement). Also I agree that nearest neighbor algorithm is something pretty simple to implement using eucledia distance between the testing and training samples. But, based on my experience, the KNN tends to give mix set of results and it mostly depends on how you choose the feature sets for the training samples and quality of the feature set.
           The paper describes the optimal angular distance calculation which is used to compare with the nearest neighbor algorithm and use it to obtain the maximum similarity (inverse minimum cosine distance).
           The paper discusses nearest neighbor approach with K=1, but lack what will be the situation when the K value is changing (say 3, 5, 7 etc). As an example when Protractor was given 3 templates and finding assigning the highest similarity among 3 templates to the unknown one is not discusses as in the case of 5 or 7 or etc samples. With my personal experience, k=3 makes a better solution than k=1 where the comparison is happened between 3 known samples against 1 unknown sample (may be highly depends on the content area). Also missing is the description on how the performance of the Protractor when the template sample increases.

Find the paper here. 

Reading #5: Gestures without Libraries, Toolkits or Training: A $1 Recognizer for User Interface Prototypes

Comments on Others:

Wenzhe Li

Summary
           The paper states that “$1 recognizer” (I guess $1 represents how easy, cheap, and usable with less loc to program) was developed to enable novice programmers to incorporate gestures into their UI prototypes. The paper includes a detailed pseudo code, so that programmers can easily test the gesture recognizer through their interface design. The authors correctly states that the making of gesture recognition a topic of interests to experts in the field of AI, not experts in HCI with primarily works on interactive level (not completely agree!). Therefore, authors assume that this perhaps limited the opportunity to slip in gesture recognition into UI design. The paper also presents why Ad-hoc recognizers prevents applications due to limitations in defining own gestures at run time,  and when the gesture set is very large.
           The $1 recognizer is essentially limited to uni-stroke due to the authors’ interest in recognizing paths delineated by users interactively. The authors state comparatively, $1 recognizer is better because sophisticated methods like HMMs, ANNs, statistical classifiers require extensive training before practical use, and also they are difficult to program and debug. The authors describe, even the popular Rubine’s linear classifier requires advance computation before its use.
           The paper also states 8 criteria’s defined upon the recognizer to make it simple (These criteria’s also considered as goals of this methodology). The paper describes its algorithm implementation is 4 step process. As limitations, authors states that $1 algorithm is rotation, scale and position invariant (circle and oval both similar). Also gestures are not possible differentiate based on time. The paper states the testing procedure with comparison to Rubin classifier and Dynamic Time Warping (DTW).   

Discussion
              This paper explains a simple gesture recognizer which can be easily program and plugged in to a UI design and support gestures through the UI. The authors believe that perhaps the area of interests of HCI experts makes it limited for the UI designs to be incorporated with gesture recognition. In my opinion, I’m not completely agreed to that, may be limitations on the existing technology hinder the opportunities to do more research on HMM, ANN etc. and to apply that knowledge to UI usability and development research.
           I’m not sure why authors state that HMMs require extensive sample training and complex coding and debugging. With my personal experience on developing HMM based eye movement detection algorithm, I feel authors bit mislead just by the content before applying it to real world applications (HMM is reasonably fast with online applications though it require some sort of a training before hand). Also, I’m just wondering the use of N=64 for the resampling. May be using a digitization (select the path and make adjacent pixels 1 or zero depends on the next pixel and direction)
           Overall, the paper presents easy to read/understand concept on simple gesture recognizer, and I believe is a plus for gesture/sketch recognition community to implement it and compare it with their own algorithms (Because authors suggests that their work is comparatively competitive in terms of results in previously used complex algorithms, Rubine and DTW).

Find the paper here.

Reading #4: Sketchpad: A Man-Made Graphical Communication System

Comments on Others:

Wenzhe Li

Summary
         This paper describes earliest (more importantly, first), man-machine-interaction (MMI) technology called “Sketchpad” by Ivan E. Sutherland (According to Dr. Hammond, Sutherland was recognized as the father of the sketch recognition). The sketch pad was capable of drawing sketches according the movement of a light pen (for position trace) and using a push button to say a specific function (turn on and off switches) to execute. This way the sketchpad system said to be eliminated typed statements (so far we are still using typing, but its’ OK the paper dates back to 1964 with the original idea) in favor of line drawings.
            The authors demonstrated its intended use of light pen with a novel idea of using pseudo pen location to detect where the intended location that the pen needs to be aiming at. The paper explains its displays are using straight line segments, circle arcs and single points as the basic (or fundamental) design symbols for its sketchpad displays. The authors also discusses the use of display abstraction to support in drawing properties, like similar length, similar size etc using constrains. 

Discussion

             The sketchpad is an important finding for the sketch recognition domain (I mean the idea of sketch/gesture recognition),   and I believe it makes totally a new era of human computer interaction. How important this area of research going to be for our day today life or to the near future, readers can look at your own pocket (touch phones, touch pads, touch media players etc). For the moment we are using some sort of gesture input for these devices, and we can expect whole new way of interactions (May be you can look at “Microsoft's Vision of the Future” video just to get a clue).
           It is an interesting idea of having a pseudo pen location for segments where a light pen is aiming at. But as of my opinion, when it comes to heavily multi-stroked gestures/sketches, the system tends to fail due to cross-mapping of pseudo pen location (it is possible to map the pen location to a wrong place due to multi-strokes already sketched on). I’m not clear how the authors solved this problem in their related work (any thoughts???).
           Most of the future works of the paper are in successful outcomes (in my personal opinion), and the concept of sketching using an input device is outdated (for the purpose of creating an electrical circuit or complex drawing etc.), there are already number of software products to do all these drawing stuff (like smartdraw).   

Find the paper here. 

Reading #3: “Those Look Similar!” Issues in Automating Gesture Design Advice

Comments on others:

Wenzhe Li

Summary

            This paper describes an interface design tool that uses unsolicited advice to help designers of pen-based user interfaces to create pen gestures which are dissimilar. The tool said to be designed such a way that it warns designers when their gestures will be perceived to be similar and advise how to make their gestures less similar. The authors state their gesture design tool “quill” which will advises designers on how to improve their gestures. To detect when people will perceive gestures as similar, quill said to be equipped with experimentally-derived model of human-perceived gesture similarity. This paper states its similarity experiment with outcomes of 99.8% for not similar gestures and 22.4% for similar ones with a gesture pair to perceive as similar or not. The paper also discusses interface and implementation challenges on quill.

Discussion

             The paper discusses an interesting topic of helping interface designers to create less similar gestures with the pen based user interfaces. The paper states cut and paste as gestures with similar abstract operations which often confuse designers when assigning gestures. I’m not sure how true the statement is, may be authors wants to compare cut and copy, not cut and paste!!!
           With that much lower accuracy rate for identifying two similar gestures (22.4%), it is hard to understood that quill is so much accurate or powerful enough to predict when two gestures are similar (in my opinion the similarity experiment result accuracy is not even in the mid rage which is unacceptable). Also I feel the readers may want more detailed explanation on similarity experiment (as the backbone of the quill, by the way that’s what provide intelligence to quail) to get a fair idea of how the quill works.
           The paper discusses difficulties in providing advice, specially at what time, as soon or later. But the authors state that they found that the unsolicited advice is the best way though there are difficulties with the timing in situations like brainstorming. May be the solution is too simple to think (or stupid), but why don’t we create a condition for brainstorming (may be user can press a brainstorm button to stop advice, or stop advice button!! Genius or what).

Find the paper here.

Reading #2: Specifying Gestures by Example (Rubine)

Comments on others:

Yue Li

Summary:

This paper describes possibility of creating automatic gesture recognizers from example gestures by removing the need for hand coding. The GRANDMA (Gesture Recognizers Automated in a Novel Direct Manipulation Architecture) toolkit developed for rapidly adding gestures to direct manipulation interfaces and trainable single stroke gesture recognizer used by GRANDMA are also explained. The paper also describes powerful combination of gesturing and direct manipulation in the two-phase interaction technique. The author suggests the requirement of 15 training samples (or examples) per gesture class which is selected empirically. The author explains a simple preprocessing applied towards the inputs by removing time stamped coordinates which are 3 pixels apart from the previous input point. Furthermore, the author describes the feature set was empirically determined to work well on a number of different gesture sets. The gesture feature classification is handled by a linear classifier over the features. In addition Eager recognition to recognize gestures as soon as they are unambiguous and Multi Finger recognition are also discussed.

 

Discussion

  According to the author, the GRANDMA took kit is essentially a single stroke based gesture system and states that this allows shorter timeouts to be used and therefore avoids segmentation problem. Still the author states the possibility of both timeouts and mouse button release, and this makes readers wonder that if button release action is a possibility then why its so hard to incorporate the multi-stroke gesture recognition to the GRANDMA toolkit. In my opinion, it is voluble for users to show that even the multi-stroke gesture recognition is possible through the GRANDMA toolkit though it is faster (or less problematic and simple) to use only single-stroked gesture recognition.
          The author suggests than 15 training samples are enough per gesture class and this essentially makes readers wonder that the use of terminology in the GRANDMA, "Automation". Author refers it as the possibility of automatic gesture recognition vs. need for hand coding, and in my opinion if the recognizer still requires some sort of manual input (gestures) for the system to be functional (just my opinion).
         The elimination of jiggle is another point to consider, the author states a simple preprocessing to remove input apart from 3 pixels from the previous input. In my opinion this may hinder the users intension as well as the actual input gesture. I believe a strong preprocessing; something like a binarization and then skeltonation would be much more appealing. The use of specific features set need to be independently verified, may be a sensitivity analysis and ranking order based on the analysis would be a better choice. Its quite nice if there’s some results from different gesture classifications, something like KNN compared to linear classifier.

Find the paper here.

Reading #1: Gesture Recognition

Comments on others:
Francisco Vides  
Jianjie (JJ) Zhang

Summary:
             This paper starts with providing fundamental difference between the sketch and a gesture and the usefulness of gesture recognition to recognize a sketch. In contrast, the author states to avoid use of gesture based techniques in sketching due to possible constraining users from brainstorming and design. Furthermore, the author states that gesture recognitions work well in concert as editing or action commands in a sketch recognition system.
           Furthermore, author discusses mainly the work of Dean Rubine’s gesture recognition method used for sketches in 1991, Long’s method which extended Rubine’s features to 22 and Wobbrock’s $1 recognizer. Author distinguish the Dean Rubine’s work as first and most recognized gesture recognition method for sketches with 13 stroke features and a linear classifier to feature classification. Author describes Christopher Long’s work on gesture recognition called the system Quill in 1996, which is similar to Rubine’s but slightly modified to have less reliance on time. Furthermore, the author states Jacob Wobbrock’s work on implementing a simple template matcher in 2007 that recognizes gestures slightly better than the feature based method. It is called the $1 recognizer because is it easy to implement.

Discussion:
            The author presented a number of methods for performing gesture recognition in a single roof survey. Much of the authors’ concentration is on Rubine’s work, giving a clear meaning and importance of each of the feature set than the Rubine’s paper (I feel Rubin’s paper bit complicated to understand than the authors explanation, I guess that’s what authors’ intension was in writing this as a survey paper).  
              In my opinion I would like to see the features mapped to a common ground with a same value scaled to its characteristics. Say, something like a fuzziness 0-1. If it is a line, how slanted, how straight etc. And also some sort of a sensitive analysis to see which features makes the recognition accuracy better, may be a ranking order of the identified features may be a good idea.

Find the paper here.

About me...............

E-mail address : UKSJayarathna(AT)gmail(DOT)com

Graduate standing : First year PhD (MS from Texas State University-San Marcos)

Why are you taking this class? My undergraduate research background is “Offline Character Recognition”, so I feel comfortable taking a course similar to my research interests. Also I hope the course content will give me some interesting clues to some of my pet research ideas. 

What experience do you bring to this class?
This is my 6^th year in the HCI research field, and I’m specifically interested on “Biologically inspired mathematical models”. I want to apply some of AI techniques to sketch recognition, say Fuzzy Logic. Any ideas people?  

What do you expect to be doing in 10 years?
Doing research on anything I like (hopefully something related to my PhD) (ii) working with graduate students (iii) teaching classes (I love teaching) (iv) applying for grants (v) flying around to work with other researchers and to give talks on my research

What do you think will be the next biggest technological advancement in computer science?
I’m expecting eye tracking technology (not the biggest though) to kicks in within next couple of month’s/year’s time. At least the notebook guys are having trouble with finding ways to keep their toys expensive (fingerprinting is already there, and some sort of voice/face recognition systems too),  so we have something realistic like in “Minority Report”.

What was your favorite course when you were an undergraduate?
“Remote Sensing & Geographic Information Systems (GIS)”, I ended up getting A+ for it.

What is your favorite movie and why?
“The Man from Earth”. I like movies which makes you to go back see what they are saying is true and end up feeling amazed how they organize and blend real world facts into the movie. Something like Da Vinci Code, and National Treasure.  May be I'm a bit biased to the "The Man from Earth", its producer Eric D. Wilkinson personally commented and thanked on my blog post about his movie.

If you could travel back in time, who would you like to meet and why?
This is kind a common answer I guess. But I desperately need to thank my Dad for everything he did for me.    

Give some interesting fact about yourself
Read my Bio here.

Love is so deep.........

This is another chain-mail may be, but touching. So, I thought to share with my fellow bloggers....

I was walking around in a Target store, when I saw the lady in the cashier hand this little boy some money back.
The boy couldn't have been more than 8 or 9 years old.
The Cashier said, 'I'm sorry, but you don't have enough money to buy this doll.'
Then the little boy turned to the old woman next to him: ''Nanny,
are you sure I don't have enough money?''

The old lady replied: ''You know that you don't have enough money to buy this doll, my dear.''
Then she asked him to stay there for just 5 minutes while she went to look around for a cheaper one. She left quickly
The little boy was still holding the doll in his hand.

Finally, I walked toward him and I asked him who he wished to give this doll to
'It's the doll that my sister loved most and wanted so much for Christmas.She was sure that Santa Claus would bring it to her.'
I replied to him that maybe Santa Claus would bring it to her after all, and not to worry.

But he replied to me sadly. 'No, Santa Claus can't bring it to her where she is now. I have to give the doll to my mummy so that she can give it to my sister when she goes there.'
His eyes were so sad while saying this. 'My Sister has gone to be with God. Daddy says that Mummy is going to see God very soon too, so I thought that she could take the doll with her to give it to my sister .''

My heart nearly stopped.
The little boy looked up at me and said: 'I told daddy to tell mummy not to go yet. I need her to wait until I come back from the shops.'
Then he showed me a very nice photo of himself. He was laughing. He then told me 'I want mummy to take my picture with her so she won't forget me.'
'I love my mummy and I wish she didn't have to leave me, but daddy says that she has to go to be with my little sister.'

Then he looked again at the doll with sad eyes, very quietly.
I quickly reached for my wallet and said to the boy. 'Suppose we check again, just in case you do have enough money for the doll!''
'OK' he said, 'I hope I do have enough.' I added some of my money to his without him seeing and we started to count it. There was enough for the doll and even some spare money.

The little boy said: 'Thank you God for giving me enough money!'
Then he looked at me and added, 'I asked last night before I went to sleep for God to make sure I had enough money to buy this doll, so that mummy could give it to my sister . He heard me!''
'I also wanted to have enough money to buy a white rose for my mummy, but I didn't dare to ask God for too much.. But He gave me enough to buy the doll and a white rose.''

'My mummy loves white roses.'
As I saw the old lady returning, I left with my basket as to not cause a scene.
I finished my shopping in a totally different state of mind from when I started.
I couldn't get the little boy out of my mind. 
Then I remembered a local news paper article two days ago, which mentioned a drunk man in a truck, who hit a car occupied by a young woman and a little girl. The little girl died right away, and the mother was left in a critical
state. The family had to decide whether to remove the life-sustaining machine, because the young woman would not be able to recover from the coma.

Was this the family of the little boy?
Two days after this encounter with the little boy, I read in the news paper that the young woman had passed away.
I couldn't stop myself as I bought a bunch of white roses and I went to the funeral home where the body of the young woman was for people to see and make last wishes before her burial.
She was there, in her coffin, holding a beautiful white rose in her hand with the photo of the little boy and the doll placed over her chest.

I left the place, teary-eyed, feeling that my life had been changed for ever.. The love that the little boy had for his mother and his sister is still, to this day, hard to imagine.
And in a fraction of a second, a drunk driver had taken all this away from him.

Don't drink and drive....... .

Sri Lankans who forward emails (Must read)

Click on the image to view it with better resolution.............

You Can If You Think You Can!

You Can If You Think You Can!
If you think you are beaten, you are,

If you think you dare not, you don't.

If you like to win, but you think you can't,

It is almost certain you won't.
If you think you'll lose, you're lost,

For out in the world we find,

Success begins with a fellow's will.

It's all in the state of mind.

If you think you are outclassed, you are,

You've got to think high to rise,

You've got to be sure of yourself before

You can ever win a prize.

Life's battles don't always go

To the stronger or faster man.

But soon or late the man who wins,

Is the man who thinks he can.

~ C. W. Longenecker ~

Male Vs Female at ATM

A new sign in the Bank Lobby reads:

'Please note that this Bank is installing newDrive-through ATM machines enabling customers to withdraw cash without leaving their vehicles.

Customers using this new facility are requested to use the procedures outlined below when accessing their accounts.

After months of careful research, MALE & FEMALE Procedures have been developed. Please follow the appropriate steps for your gender.'

**************************
MALE PROCEDURE:
1. Drive up to the cashmachine.
2. Put down your car window.
3. Insert card into machineand enter PIN.
4. Enter amount of cashrequired and withdraw.
5. Retrieve card, cash andreceipt.
6. Put window up.
7. Drive off.

**************************
FEMALE PROCEDURE:

What is really funny is that most of this part is the Truth.!!!!

1. Drive up to cash machine.
2. Reverse and back up the required amount to align car window with the machine.
3. Set hand brake, put the window down.
4. Find handbag, remove all contents on to passenger seat to locate card.
5. Tell person on cell phone you will call them back and hang up.
6. Attempt to insert card into machine.
7. Open car door to allow easier access to machine due to its excessive distance from thecar.
8. Insert card.
9. Re-insert card the right way.
10. Dig through handbag to find diary with your PIN written on the inside back page.
11. Enter PIN.
12. Press cancel and re-enter correct PIN.
13. Enter amount of cash required.
14. Check makeup in rear view mirror.
15. Retrieve cash and receipt.
16. Empty handbag again to locate wallet and place cash inside.
17. Write debit amount in check register and place receipt in back of chequebook.
18. Re-check makeup.
19. Drive forward 2 feet.
20. Reverse back to cash machine.
21. Retrieve card.
22. Re-empty handbag, locate card holder, and place card into the slot provided!
23. Give dirty look to irate male driver waiting behind you.
24. Restart stalled engine and pull off.
25. Redial person on cell phone.
26. Drive for 2 to 3 miles.
27. Release hand brake.

Mobile Fun - Everything Mobile (web review)

When I saw the index page of the Mobile Fun web page, I thought OK, something is out of touch here, something makes the page bit odd? I guess the first two items which are on sale, the thumbnail of those icons are too big! I know those should be different from what on the bottom of the Latest products, but I feel they should be in similar size, and may be using different method to show out them as on sale? May be placing all of them in the same size and then use the on sale icon already in the page to make them special? May be a cool animation to pop them up several times when the page loads for the first time?

Another quick thought on the same on sale items. I thought those items are rotating, I mean they are changing every time someone refresh the page or log in. Seems to me those are just static continent? I guess only those 2 items, jabra bluetooth headsets, and other types of headsets on sale, plus nano Bluetooth dongle on sale are the only items in this category. If you just have few, why you want to pop them to show? It makes the site bit cheap.

I know there is a big demand for Bluetooth Headphones, bluetooth car kit and all those small gadgets. But most the people want to see, and like to see, some featured mobile phoned you have. This will give you a better view on the site and the items on the Mobile Fun page (just a thought). In my opinion, mobile gadgets are in second consideration, and first priority is for Mobile Phones, at least as a customer, thats what I’m looking for. First buy a mobile phone and then buy other gadget stuff. Why don’t you move all the featured mobile phones up on the list and then show the other accessories?

Another quick thought on the layout of the index page. There are lots of information on the left side panel, currently Mobile Fun page is listing all the Mobile accessories, and Sim free mobile phones with showing all available brand names. Personally its OK for me to have them in a drop down box and its easy to go through the phones that way. You are categorizing phones bases on the popularity I guess. But why don’t you have a drop down list and then put them in alphabetical order of the brand name? This makes easy for customers to find the item or the brand they want. And this will help Mobile Fun web to save some space on the side panel and use it for some other task.

“The Man from Earth” – truly a remarkable movie………………..

Update (12/18/2011): I just watched the movie for the 10th time, and still enjoying it. And also I noticed my post is coming up higher in Google search and also, the Producer of the movie Eric D. Wilkinson had left a comment in this blog post :) suprise, suprise. Yes, as he mentioned, please buy a copy from Amazon, watch it and spread the word. This is truly a one of a kind movie. 

I just spend astonishing hour on watching this master piece. I’m thrilled and no words to say. Never saw a movie like this (except Da Vinci Code and National Treasure, both brilliant in their own way…..). This is the first time I watched a movie which plays in the same location without actions packed and tack ticks…….I liked how it speaks about Buddhism and how Christianity emerged from Buddhism……. 

Here’s a comment from its official page…….
...every so often you will see a film or hear a story that will take your breath away and leave you wondering...this is one of those stories. That said it is probably not for everyone. If you don't want your believes challenged you should probably stay away from this one. The film is all about the characters and their dialog, it is what makes or breaks the film, and I must say they did an excellent job, it kept me on the edge of my seat the whole time, wanting to hear more. All this topped with great acting makes this a film really worth seeing.

It goes to show that you can make great films these days without explosions and killings...so simple yet so effective. Great movie!

The story plot from the Wiki……………….

The movie begins with Professor John Oldman (David Lee Smith) packing his belongings onto his truck preparing to move to a new home. His colleagues show up to give him an unexpected farewell party: Harry (John Billingsley, a biologist); Edith (Ellen Crawford, a fellow professor and devout Christian); Dan (Tony Todd, an anthropologist); and Sandy (Annika Peterson), a historian who is in love with John. Edith spots in John's belongings next to his truck an unknown Van Gogh painting of John's with the note "To my friend, Jacques Borne" on the back written in French. Once inside, his friends persistently ask John why he is leaving.

Another friend, Art Jenkins (William Katt), an archeologist, and his student Linda Murphy (Alexis Thorpe), arrive and John's friends continue to pressure him for the reason for his departure. John poses the question, "What if a man, from the Upper Paleolithic survived until the present day?" They assume that John is working on a science fiction story and play along with the discussion. As the film progresses, John slowly reveals that he is the "caveman" under discussion when he mentions that he was given a chance to sail with Christopher Columbus in the 15th century. The revelation starts off with John's recollection of the terrain of prehistoric Earth and John's origins, which happens to be roughly 14,000 years ago. John reveals that he was once Jacques Borne, a friend of Van Gogh's, and he is now "moving on" since some people have noticed his lack of aging.

As they take a break from the discussion, Art – who is concerned about John's sanity – telephones another friend, Dr. Will Gruber (Richard Riehle), an elderly psychologist, explaining the odd situation and asks him to come over right away. In the meantime, Sandy confesses to John that she loves him, but John tells her they can never be together because of his immortality. John resumes his story by stating that he was once a Sumerian for 2000 years, then a Babylonian under Hammurabi, and finally a disciple of Gautama Buddha. Dr. Gruber arrives, at which point Dan mentions that John's tale is as impossible to be disproved as it is to be verified, a response to the many attempts to poke holes in John's story by his colleagues. The discussion takes a turn into the biological and physical condition of John and the topic of death. Gruber propels the discussion deeper into the topic of death and tension rises as Gruber interrogates John on that subject. The tension culminates with Gruber pointing a gun at John. After the drama ends with the departure of Gruber, Harry reveals that Gruber's wife has died the day before and the profession of John's immortality had hit Gruber very hard. Art and Edith are upset with John's story, while Harry, Dan, Sandy, and Linda appear to be more sympathetic.

John also mentions that he is not a follower of a particular religion, and he doesn't believe in an omnipotent God. John's audience is shocked when he reveals how he survived the crucifixion when he was Jesus by "blocking the pain", a technique he learned in India. He explains the origin of the Resurrection, Moses, and other events and people in the Bible. Tempers and emotions rise as Edith pressures John to recant his story, which offends her deep-rooted faith in the Bible. Dr. Gruber returns to the scene and apologizes to John for his "infantile behavior". As John continues to pack his belongings onto the truck, his colleagues begin to talk about the possibility of John being mentally ill or high on drugs.


The discussions of John being Jesus, Christianity, and the Bible continue and Edith, unable to take John's tale anymore, breaks down crying. Emotions in the room run high. Gruber takes charge of the situation and sternly demands that John end his "high tale" and give closure to the story; he threatens John with the possibility of locking him up for observation. John apologizes to everyone and, as he doesn't want to further upset any of his friends, he tells them that all he just told them is just a story.

As each of John's friends leave, John apologizes to Harry and Edith, while Art and Linda leave without many parting words. When it is Dan's turn to say goodbye, it is hinted that Dan believes John's story. After everyone but Dr. Gruber and Sandy has left, Dr. Gruber overhears John relating to Sandy some of the other pseudonyms he has used over the years. One used over 60 years ago was the name of Gruber's father, a chemistry professor from Harvard, who had left the family. Gruber, shocked and over-excited, suffers a heart attack and dies. After Gruber's body is taken away, the movie ends with Sandy walking towards John (sitting in his truck); at the last minute he changes his mind to spend some part of his life with her.

Cricket without Cricket........awsome video......

Another awesome video!

This is what I like about Sri Lankan Cricket…….simple, fun and no aggression at all……..People, Players, and everybody around enjoying the movement. If we lose the match, that’s not the end of the world,

we never throw stones at cricketers homes,

we never throw stuff to the ground (including bottles, trash, bill boards….) when the other team is winning,

we never lit things and try to burn the anger due to a lost…….

we used to say “those buggers lost……what to do……they are not good now……….may be next match……..”. That’s all………..that’s what we called Island Cricket………

Cheers Sri Lankan Cricket……………..

We found the next unorthodox cricketer…….guess who?

We got all sort of unorthodox cricket players at international level (Sri Lanka). Recently, we found the final quite unorthodoxy with the fielding too.

Here’s a remarkable piece of fielding by Angelo Mathews, a definite six, or may be a four, but finally it was unimaginable react and stop by young cricketer. Great job…………thumbs up, Sri Lankan cricket…………..

It’s not fair, if we forget all other unconventional Sri Lankan players……..

Sanath Jayasuriya
Master blaster…….remember what happen to Indian bowler Manoj Prabhakar ……..?

Lasith Malinga
One and only one with 4 wickets………..and the hair cut too..

Muttiah Muralitharan
Best bowler ever……….

Ajantha Mendis
Variation in bowling………….

Tillakaratne Dilshan, Roshan Mahanama
Outstanding fielding (still Jonty Rhodes is the #01)

Asanka Gurusinghe
Slowest batting……(we used to hate this guy….)

Not sure we can put Angelo to this list yet……but hopefully he will for sure, later on…………

Nanotube chip could store data for a billion years....

Time for a terabytes, probably petabytes pen drive!

Researchers have demonstrated a form of archive memory using carbon nanotubes that can theoretically store a trillion bits of data per square inch for a billion years.

The technology could easily be incorporated into today's silicon processing systems and it could be available in the next two years, a lead researcher said.

The scientists at the U.S. Department of Energy's Lawrence Berkeley National Laboratory and the University of California said the new technology can potentially pack thousands of times more data into one square inch of space than today's chips.

"We've developed a new mechanism for digital memory storage that consists of a crystalline iron nanoparticle shuttle enclosed within the hollow of a multiwalled carbon nanotube," said physicist Alex Zettl, who led this research.

No more Kwai Chang Caine (Kung Fu) , Actor David Carradine found hanged in his luxury hotel room in Bangkok

Actor David Carradine, star of the 1970s TV series "Kung Fu" who also had a wide-ranging career in the movies, has been found dead in the Thai capital, Bangkok. A news report said he was found hanged in his hotel room and was believed to have committed suicide.

A spokesman for the U.S. Embassy, Michael Turner, confirmed the death of the 72-year-old actor. He said the embassy was informed by Thai authorities that Carradine died either late Wednesday or early Thursday, but he could not provide further details out of consideration for his family.

The Web site of the Thai newspaper The Nation cited unidentified police sources as saying Carradine was found Thursday hanged in his luxury hotel room.

It said Carradine was in Bangkok to shoot a movie and had been staying at the hotel since Tuesday.
The newspaper said Carradine could not be contacted after he failed to appear for a meal with the rest of the film crew on Wednesday, and that his body was found by a hotel maid at 10 a.m. Thursday morning. The name of the movie was not immediately available.

It said a preliminary police investigation found that he had hanged himself with a cord used with the room's curtains. It cited police as saying he had been dead at least 12 hours and there was no sign that he had been assaulted.

A police officer at Bangkok's Lumpini precinct station would not confirm the identity of the dead man, but said the luxury Swissotel Nai Lert Park hotel had reported that a male guest killed himself there.
Carradine was a leading member of a venerable Hollywood acting family that included his father, character actor John Carradine, and brother Keith.

In all, he appeared in more than 100 feature films with such directors as Martin Scorsese, Ingmar Bergman and Hal Ashby. One of his prominent early film roles was as singer Woody Guthrie in Ashby's 1976 biopic "Bound for Glory."

But he was best known for his role as Kwai Chang Caine, a Shaolin priest traveling the 1800s American frontier West in the TV series "Kung Fu," which aired in 1972-75.He reprised the role in a mid-1980s TV movie and played Caine's grandson in the 1990s syndicated series "Kung Fu: The Legend Continues."He returned to the top in recent years as the title character in Quentin Tarantino's two-part saga "Kill Bill."The character, the worldly father figure of a pack of crack assassins, was a shadowy presence in 2003's "Kill Bill — Vol. 1." In that film, one of Bill's former assassins (Uma Thurman) begins a vengeful rampage against her old associates.In "Kill Bill — Vol. 2," released in 2004, Thurman's character comes face to face again with Bill himself. The role brought Carradine a Golden Globe nomination as best supporting actor.

Bill was a complete contrast to his TV character Kwai Chang Caine, the soft-spoken refugee from a Shaolin monastery, serenely spreading wisdom and battling bad guys in the Old West. He left after three seasons, saying the show had started to repeat itself.
After "Kung Fu," Carradine starred in the 1975 cult flick "Death Race 2000." He starred with Liv Ullmann in Bergman's "The Serpent's Egg" in 1977 and with his brothers in the 1980 Western "The Long Riders."But after the early 1980s, he spent two decades doing mostly low-budget films. Tarantino's films changed that. "All I've ever needed since I more or less retired from studio films a couple of decades ago ... is just to be in one," Carradine told The Associated Press in 2004.
"There isn't anything that Anthony Hopkins or Clint Eastwood or Sean Connery or any of those old guys are doing that I couldn't do," he said. "All that was ever required was somebody with Quentin's courage to take and put me in the spotlight." One thing remained a constant after "Kung Fu": Carradine's interest in Oriental herbs, exercise and philosophy. He wrote a personal memoir called "Spirit of Shaolin" and continued to make instructional videos on tai chi and other martial arts.
In the 2004 interview, Carradine talked candidly about his past boozing and narcotics use, but said he had put all that behind him and stuck to coffee and cigarettes. "I didn't like the way I looked, for one thing. You're kind of out of control emotionally when you drink that much. I was quicker to anger."

"You're probably witnessing the last time I will ever answer those questions," Carradine said. "Because this is a regeneration. It is a renaissance. It is the start of a new career for me.

"It's time to do nothing but look forward."