One use of the transformation matrices is to describe geometric transformations. So, for example, let's say I have a point in R2, and I want to consider the geometric transformation Mx, which will be the reflection of my point across the x-axis. So remember, if I have a point with coordinates x, y, the coordinates tell me how to get to the point from the origin. We'll go x units horizontally, and then y units vertically. Now what happens when we reflect this point across the x-axis? Well, the actual vertical distance is still y, but this time because we're going down instead of up, our coordinates are going to be x negative y. So our new x-coordinate is x, the same thing we started with, and our new y-coordinate is negative 1 times y. And because we want to write the coefficient matrix, we'll have to write x as 1x plus 0y, and a new y-coordinate will be 0x plus negative 1y. And so keeping only the coefficients, we'll get our transformation matrix. Or we can take another transformation. Again, let's take a point in R2, and this time we'll consider the transformation R90 degrees, which will be the rotation of our point about the origin through an angle of 90 degrees counterclockwise. So as before, we'll have our point P with coordinates x, the horizontal distance, and y, the vertical distance. And then we'll spin our point right round, 90 degrees. And as before, the lengths themselves have remained unchanged. But this time our horizontal distance will be negative y, and our vertical distance will be x, so our coordinates will be negative y, x. And so, algebraically, our transformation is going to give us a new x-coordinate of negative y, and a new y-coordinate of x. And again, because we want to be consistent, we need to write this as 0x plus negative 1y, and 1x plus 0y. And the coefficients of these formulas give us our transformation matrix R90. Once we have these transformation matrices, we can perform a sequence of geometric transformations. Suppose I have a sequence of geometric transformations and the corresponding transformation matrices. If I perform these transformations in sequence, I'm going to indicate that sequence of transformations in the following way. And it's important to note here that the first transformation that we perform, T1, is the rightmost transformation. The second transformation, T2, will be on the left, and so on. So for example, MxR90 degrees is going to be the transformation where first I rotate by 90 degrees counterclockwise, and then I reflect across the x-axis. On the other hand, R90Mx is going to be the transformation where first I reflect across the x-axis, and then I rotate 90 degrees counterclockwise. And because this is still a geometric transformation, we can write down the transformation matrix corresponding to this composition of geometric transformations. So let's see how that might work. So let's take a look at R90 degrees Mx. That's a reflection across the x-axis first, followed by a 90-degree counterclockwise rotation. So as before, we'll have our point xy with horizontal and vertical distances. We'll reflect across the x-axis first, and then rotate 90 degrees counterclockwise. So as before, all of our actual lengths have remained unchanged. However, our directions for getting to the point will be a little bit different. So this time, we have to go a vertical distance of x and a horizontal distance of y. And so our coordinates are going to be horizontal distance y, vertical distance x. So our new x-coordinate will be y, which we'll write down as 0x plus 1y. And our new y-coordinate will be x, which we'll write down as 1x plus 0y. And so we'll use the coefficients of these formulas to get our transformation matrix. What about Mx R90 degrees? That's the transformation that we perform by first rotating 90 degrees counterclockwise around the origin and then reflecting across the x-axis. So as before, we'll have our point xy with horizontal distance x, vertical distance y. We'll rotate 90 degrees counterclockwise around the origin, and then we'll reflect across the x-axis. And this time, in order to get to the point, we'll have to go down a vertical distance of x and left a horizontal distance of y. And so the coordinates of the point will be minus y, minus x. And so our new x-coordinate will be minus y, which we'll write as 0x plus negative 1y. And our new y-coordinate will be negative x, which we'll write as negative 1x plus 0y. And finally, we'll record just the coefficients to get our transformation matrix.


I'd like to invite Tom Derrick from the British Library, which is a member of the Reid Co-op, and Nicole Merkel-Hilf from the Heidelberg University Library to the stage. I hope it's okay to say that you are a private member of the Reid Co-op, and we move on with I think it's a presentation about Index Script. Thank you for the kind introduction, and good morning to you all. Tom and I are happy to have the opportunity to present two projects from two institutions with one common goal, and that is text recognition for non-Latin, and to be more specific for South Asian scripts. With our two projects, we show where the challenges lie in text recognition for this material, and what we have achieved with Transcribos so far. Tom is digital curator for the two centuries of Indian print project at the British Library and deals with 19th century printed books in Bangla script and language, but he's also working with printed material in Urdu language, written in the Persia Arabic calligraphic script Nasta League. My project, Naval Kishore Press Digital at Heidelberg University Library, also deals with 19th century printed books, but focuses on the Devanagari script, which is used for various South Asian languages. So basically we are dealing with three different scripts, and they have the following features. Bangla and Devanagari are written from left to right, and are so-called abhugita scripts. That is a segmental writing system in which consonant vowel sequences are written as units. Each unit is based on a consonant letter, and vowel notation is added. The inherent vowel, which is usually a short A, may be changed by adding a vowel mark or diacritic. Both scripts make frequent use of ligatures, and these can be formed by combining two or more consonants. And the total number of ligatures existing in Bangla and Devanagari amount to several hundred, and this is definitely a challenge for text recognition. The Nasta League script is used within South Asia primarily for the Urdu language. It is written from right to left, and is one of the main calligraphic script types for Persian and Urdu. As usual with Arabic scripts, vowels are not written, except perhaps as diacritics, and the characters have three different forms depending on the position within the word. Initial, middle, or final. So after this short excursion on South Asian writing systems, I turn to the Heidelberg Naval Kishor Press Project, which is abbreviated NKP. The Naval Kishor Press was founded in the North Indian city of Lucknow in 1858, and grew to one of India's most important publishing houses. The Press's portfolio covered books in Hindi, Urdu, Persian, Arabic, and Sanskrit, on subjects as diverse as religion, education, medicine, school books, Sanskrit literature, as well as translations of English classics. The Library of the Center for Asian and Transcultural Studies at Heidelberg University holds with approximately 2,200 titles, a representative cross-section of the Press's publications. Some books in the collection show paper decay and text loss. The books were printed with lead type, but there are also numerous volumes that were printed using the lithographic method. This was a preferred printing technique in India in the late 19th century because it was inexpensive. There are many bilingual books in the collection, so for example we have classical Sanskrit texts with Hindi commentaries, or texts in Prachapascha, a literary language that was common before the standardization of modern Hindi. And commercial OCR software, which does exist, usually does not provide a good recognition result for bilingual or multilingual texts because they usually rely on in-built dictionaries. So when we started our project with Transcribos in 2018, the aim was to digitize selected works from the Devanagari section of the collection, provide searchable full texts, and make if possible ground-truth data available for reuse. Our typical workflow with Transcribos includes layered analysis, creation of ground-truth, training of HTR Plus models for recognition, and last but not least, the application of the models on the text. The Devanagari books in the NKP collection have two typical layout variants, a very simple book layout consisting only of page number, header, and text body, and here we either use the Transcribos standard model for the layout analysis or our P2Parla model trained on 60 pages. The second book format, where you see a sample page on my slide, is the so-called POTI format which is based on Indian manuscripts. For this format we also trained a model with P2Parla on the basis of approximately 50 pages and the model was trained to recognize all text regions and these are usually chapter numbers, page numbers, header, and text body, and the model also recognizes the baselines. For the ground-truth we used existing transcriptions from an earlier phase of the project, but there was extensive post-correction necessary. And for our Transcribos experiments, which I will discuss later, we created the ground-truth ourselves. Our generic HDR plus model for Devanagari, which we now use for the NKP collection as well as other Devanagari texts outside the collection, was trained on the basis of 200 pages and 26,000 words as ground-truth and it is based on five different type fonts and it achieves on the validation set and impresses a character error rate of only 2.3%. And because of the good recognition results, we have made Devanagari mixed M1A available as a public model on the Transcribus side and it already has been tested by the community and we got quite good feedback. So currently we are experimenting with Transcribus in two directions. On the one hand we are training HDR plus models for the recognition of texts printed by using the lithographic method. And this is our first attempt with strictly speaking handwritten material. Our first model is based on approximately 17,000 words of ground-truth and has been trained to recognize the hand of two different writers. This model already achieves a character error rate on the validation set of 9.9% and we are now creating more ground-truth to improve its performance. Since scholars in Indology often work with transliterations, our second experiment is training data models for Devanagari texts based on ground-truth transliterations. This means that the original text of the on the facsimile is written in Devanagari script but the ground-truth used for training is produced in Latin transliteration. And we are lucky here because there is an internationally accepted transliteration scheme for the Devanagari script, the so-called international alphabet of Sanskrit transliteration which is widely used by scholars. So we relied on this transliteration scheme for the creation of the ground-truth. Here we are collaborating with the department for the study of religion at the University of Toronto and they provided us with roughly 20 pages of ground-truth on the basis of which we trained the first model. It came out with a character error rate of only 4% and I found that really amazing because I didn't think it would work. So these two experiments have produced good initial results and we will definitely stay tuned and try to improve the performance of our models. So what do our users, scholars in South Asian studies, get out of it? So far we have performed text recognition for around 12,000 pages. These have been exported in Alto XML format and ingested into the Heidelberg University Library's web presentation and scholars can search the text in Devanagari script or Latin transliteration and a word or phrase found searching the full text will be highlighted in the facsimile and in the OCR text online level. I tried to visualize this with a screenshot. And furthermore users can download a high quality OCR PDF of the facsimile where the text is also fully searchable in Devanagari script and Latin transliteration. That much on Naval Kishopres digital and I now hand over to you, Tom. So as Nicole mentioned I'm from the British Library where I've been working with transcribers to recognize text from our South Asian printed books collection. So these are books in index scripts that have been digitized through a project called Two Centuries of Indian Print and they cover a diverse range of topics and genres, everything from religion, history, translations of Western texts, poetry, drama, etc. and intended for enhancement of the study of book history for South Asian scholars. So we have digitized a couple of thousand books which are mostly available through our online catalog. Most of the books are in the Bengali language and script but also we have books available in Assamese, Saleti and Urdu. So in terms of the features of this collection as it relates to OCR there are around about 30 different publishers from these books. Majority of the books were published mid to late 19th century and many of these publishers adopted different typographical standards which has manifested in the books as types that are of different sizes and fonts. But mostly they are not too difficult for OCR. The majority of the pages are as you can see single column blocks of text so the layout is not enormously difficult however there are title pages often with large title font which is a little more difficult for transcribers to always correctly draw the baseline. There are some but very few multilingual pages with English and Bengali but the majority of the books that we have been using have been completely written in Bengali script. And the print quality is very good in fact not much to say on that other than some of the books have faint print and there's some show through on occasion which can affect the OCR output. On the whole not as problematic a collection as Nicole was dealing with in Heidelberg. So to take you through the transcribers workflow that we adopted for our printed Bengali books actually before we use transcribers we experimented with some other OCR tools through a couple of competitions we evaluated the OCR accuracy of Google cloud vision tool and also Tesseract. It's not completely fair to compare the accuracy of those to what we're seeing with transcribers because we gave them far less training data at the time and the results from Google were actually pretty good but at around the same time we started using transcribers and we liked the fact that we could train it specifically on our own material whereas Google's cloud vision was drawing on all the synthetic data that it's working with which is often much more modern than the historical books that we're working with. So we settled with transcribers if you'd be pleased to hear and we also could have created models for each of the different typographical styles that we were seeing from the publishers but we adopted a more generalist model where we drew on a sample of pages from our collection which represented the different types and through three different cycles of training for fifty pages and then one hundred seeing very good improvement on character accuracy eventually after a hundred and fifty pages of ground truth training we were content with the five point five percent character error rate that we would use that model to automate the rest of our Bengali books and I should also say that we're very thankful for the support of Jadapur University in Kolkata who produced the ground truth transcriptions for us. So the model as well was trained on just over nineteen thousand tokens. We verify the accuracy manually as well and found that to be consistent with the results that transcribers was giving us. So we also discovered with the majority of the books the layout analysis was very good. Baseline detection was excellent but for about two hundred books it was not it was drawing multiple baselines. We ended up training a p2pala model on just baselines and that's vastly improved the accuracy on those books that were originally struggling with and from a project management point of view very briefly we were a team working remotely in India and in the UK. We managed this workflow by using a Google Sheets tracking the status of each book through the transcribers workflow and this linked to a Power BI dashboard which updated in real time and gave us very nice visual snapshot of our progress and for example we could see how many books had needed layout correction and we were able to forecast how much longer the work would take us. So far we have automated OCR for Bengali books on more than a hundred thousand pages with about another fifty thousand to go and we're exporting these as page XML and we're using a style sheet conversion into Alto XML version two which is the format required for ingest into the British library's repository and to work with our triple IF image viewer. So that's the Bengali project and now we're trying to do something similar with our Urdu printed books which again predominantly 19th century. First of all we didn't have the available language resource to create the ground truth so we tried Heidelberg's open model for Urdu which we were only really able to give a kind of cursory lookover for the results but although they looked reasonably good we realized we would need to produce more ground truth so we've reached out to the crowd, we posted a message on the Urdu listserv at Columbia University and about eight or nine people responded saying they would be interested in volunteering to help create ground truth for the Urdu books. So we're using Transcriber's Light to run this exercise. We have assigned one collection per volunteer for transcription so that each volunteer is not tempted to work on someone else's material and correct it and potentially get into fights about that. We do the baseline, detection ourselves and then the volunteers simply transcribe and mark the pages as done when finished. Early feedback from the volunteers is that they are finding the Transcriber's Light interface extremely straightforward. There are no difficulties from a technical point of view. Many questions they have are normally around the transcription conventions. The majority of the work has been done by one person so we're trying to give them as much as possible. They've created 44 pages which we're nearly getting to the point where we would like to train our first model just to get a baseline understanding of our accuracy and then we can forecast how much more ground truth we will need. And then there are just a few other initiatives I should mention at the British Library that we are currently working on or have been working on that might be of relevance to this audience. So one particular project we're very excited about is called Converter Card where we're working with digitised catalogue cards for our Urdu and Chinese books and we would like to convert these digital scans into online catalogue records. So my colleague Georgia trained a P2 Palom model which proved very accurate at recognising Shelfmark, Title and Author and Addy who's sat here also trained a text model which worked extremely well and so we would like to use this to extract these aspects from the XML, the Shelfmark, Title and Author and then use that to query OCLC WorldCat to retrieve the matching records and be able to populate our catalogue records eventually with that kind of data. So that's something we're exploring at the moment. Addy's also been involved over the years with a project that's working with Arabic scientific manuscripts. So these are from the, they've been digitised through the Qatar Digital Library and they achieved a good character accuracy based on just over a hundred pages of ground truth training and they're currently looking at options for creating more ground truth and the possibilities around that and there are data sets available on the British Library's research repository from the created ground truth. Yeah, we see transcribers at the British Library as a more and more an integral part of our service that we're offering for HDR and OCR and we are increasingly integrating it into our post digitisation workflows. Transcribers can read manuscript and non-Latin scripts as well as be trained on bespoke structural recognition. It really does plug a gap that we currently have. We use ABBY as well for printed but that doesn't support indexed script so transcribers has proved invaluable in this aspect. And with that in mind we're spreading the word to our colleagues in collection areas who would be interested in using their own material. We've run several training events where they're hands-on sessions that prove very popular with our own colleagues and also when we've been running events in work in India. And so to briefly conclude our talk, I think we're just running over slightly but it'll just be another minute. We think that transcribers lights or I think because I've been the one using that is a pretty good option for crowdsourcing especially if you're working with a small group of volunteers I can't comment on how it is with a larger group. P2pala has been kind of hit and miss for me, like extremely effective in some cases and or otherwise not but it proved very useful so far for digitised catalogue cards. There are, oh Nicole wanted to mention as well about the appreciation that transcribers can be trained on our own material without the inbuilt dictionaries. There are unique challenges to non-Latin scripts as our talk has hopefully shown today with the form of the characters, the scripts, diacritics, ligatures, etc. The fact that other OCR tools do not really support it often or are not very good at reading index scripts. Material challenges, the variety of printed fonts, physical deterioration that we deal with with archival documents, this all plays a part. But we hope that our projects are proving that these challenges can be overcome and often with not too much training as well, surprisingly little amount of ground truth training has yielded very good results. So we would like to conclude by saying that we think transcribers has been and will be a great solution for printed texts in South Asian languages. That concludes our talk so thank you. Well thank you very much for these insights. Nicole is joining us on stage again, so we're ready for your questions. Here we go. Microphone is coming. Thanks for the presentation from both of you. This is more a question for Tom so I apologise for that. But just off the back of the workshop yesterday about data sharing and acknowledging contributions from the crowd and members of the public. I just wondered whether the British Library has any thoughts about how you're crediting people who responded to the Columbia University call, especially if it's this one person who's transcribed 44 pages. Especially given the kind of British context of libraries outsourcing work in the past, using quite dubious means, which the National Library of Scotland was also culpable for. Yeah, particularly as the books that we're dealing with, well they found their way to the British Library through a form of effectively colonial legal deposit during British occupation of India. So this is a question I quite often face and I think it's extremely important to recognise the efforts of everybody who's contributing to this round truth and we will certainly do that. There are practical ways to do that, obviously through events, through blog posts, also where we share our data sets through our research repository, there is an option to credit people there who have contributed. So I think that's actually a very useful way of crediting them for research because that can prove to be used in citation and so on. We also had to be quite clear upfront that this was just expected to be a volunteer-led exercise. So we've undertaken other initiatives with WikiSource in India as well, where again we had volunteers correcting OCR text. There we were able to offer prizes in that certain scenario, but there was always some kind of restriction so the prizes could not be offered outside of India and therefore the people taking part had to be based in India for that competition. With the Urdu material we're still thinking through other ways in which we can fairly acknowledge the efforts of the people who are involved. It's definitely important to do something. In the meantime we have another question online. It goes in the same direction. It's also for Tom. In which Urdu and Arabic text could be translated to within the tool, so that text analysis could be done too. So textual, sorry, textual analysis. Well based on the NASC script I believe there could be. It could be, so I don't have more context. So I think with the Urdu text that being the digitized Urdu text is often in the Arabic NASC script, so that's all I can really say on that subject. Maybe we're going to follow up, but thank you. Okay, you have some more questions? I do have a question that's actually for both of the speakers. I wanted to ask Nicole if you could speak just a little bit more about how you took the Alto XML and then made it available via this site, and I think it was in Heidelberg you mentioned, the FID forestry, and the connection to the other project is I'm wondering what your thoughts are on when you create Urdu text and how you're not there yet, but once you have that text created what's going to be, what will happen as you begin to export that into XML and then try to put that onto readers, because text directionality seems to make a difference. I can say something quite important I forgot to mention during my talk is that our books, although they are online and not yet searchable because we have produced the OCR for 100,000 pages in Alto but we are not ready as an institution to ingest that into our new repository. I'm not sure I mentioned that. So we haven't done anything with our Alto other than create it and it's sitting there and networked folders waiting to be ingested but it's obviously an important format in terms of recognizing the positioning of the words on the page for full text search eventually. We did try a P2 Palo tool on our title pages to see whether we could tag the publisher, title, date, etc. that would have then come through into the Alto but that didn't work as a P2 Palo model. Yeah, we required specifically to use version 2 of Alto with our systems currently. We can't use the latest versions at the moment. I'm not sure if that answers your question. Is that fine? I cannot add much from my side because I export the Alto XML files from transcribers and then hand them over to our IT department and they do the rest but they really do. I cannot explain. I'm sorry. Yeah, we just add as well. We will make all of our Alto available as raw data sets on our repository. So it's quite important for us why I mentioned the baseline P2 Palo model that we created is obviously to try and preserve the reading order. Eventually we anticipate some researchers wanting to undertake natural language processing tasks and looking for contextual analysis in the text. I suppose regardless of the format we are producing that would have been useful but we probably will export from transcribers not only as Alto but in other formats and we've been looking at other libraries like National Library of Scotland, etc. for the types of formats they make available through their data sets and that's useful to try to make sure that we're being consistent I suppose across the industry. We have one more question here at the front. Is that still... Yeah. Yes, I had a similar question about all the rest that you said but maybe someone else knows it. I heard it yesterday as well that people export in a page and then convert it to Alto and I was wondering is it always needed and what are the benefits? I had to do it because transcribers only exports Alto version 4 and we needed version 2 so I had to convert either from Alto to Alto or page to Alto so I just found a style sheet conversion to do that but it does add an extra step into the process once you've exported to do that. I think I did ask the transcribers team whether it would be possible to export earlier versions of Alto but I don't think it is. We would have to ask the developers in terms of these things always. Yeah, it wasn't possible all the time. Right, one more question. Yeah, thank you for your presentation. I was wondering regarding crowdsourcing transcriptions. Do you offer to the transcribers strict directions on how to transcribe or do they do it freely and then you curate the result? Thank you. We offered some advice, some standard advice around the transcription conventions and also I found the guidance on the transcribers website quite useful which provides that kind of advice so that's what I was sending them. A typical question that we're coming through is where there may be a huge gap between a sentence on the printed page and how to treat that. Do they put several spaces between order to reduce the gap? As we're doing this we're kind of building up these questions so that if we do it again we have almost a cheat sheet to give to people. Okay, then if it's fine for everybody I would end this presentation here as we're out of time and of course you also get the cups. Sorry for holding you up. Here you go.


Hello everyone, welcome to the next lecture in the course remote sensing principles and applications. Till last lecture we discussed in detail about data collection procedure, characteristic or spatial resolution concepts, how objects of small size can be detected in pixels with a much larger size and so on. This lecture we will move on to the next concept of spectral resolution or the spectral characteristics of a remote sensing system. What is meant by spectral characteristics of a remote sensing system? The spectral characteristics of a system is given by first thing the number of bands. How many number of bands does a system has? Then the central bandwidth for each band like we will always give like a bandwidth. What is the central band or the central wavelength for each band and then the bandwidth? Say for example, if we say Landsat 7 has 7 bands or 8 bands including panchromatic, we are telling that it has 8 bands. Each band has its own central wavelength and a bandwidth surrounding it. Say for example, let us say 0.45 to 0.52 micrometers. This is bandwidth, may be the central band or central wavelength of data collection may be around 0.49 micrometer. This will be like the central point around which we have this bandwidth. So this is lambda C central bandwidth may be 0.49. So here we have 0.03 micrometers. So essentially we have 0.46 to 0.52 roughly of this size. So, a central bandwidth, central band or central wavelength, a bandwidth surrounding the central wavelength and the number of bands all these together will define the spectral characteristics of a system. Among these things, the bandwidth, the spectral bandwidth like 0.45 to 0.52 that is 0.07 micrometers. This bandwidth defines the spectral resolution. So it is easy for new learners to get confused between the number of bands and spectral resolutions because we have heard young students telling that number of bands is equal to spectral resolution. That is not the case. Spectral resolution is spectral resolution is actually for each band. What is the bandwidth for each band? The bandwidth designated for each band will give us the spectral resolution. So 0.45 to 0.52 bandwidth of 0.07 micrometers. If you compare this with 0.45 to 0.47, 0.02 micrometers, then 0.45 to 0.47 has a finer spectral resolution than 0.45 to 0.52. Always keep this in mind. The bandwidth will define the spectral resolution. Okay. We are talking about a central wavelength bandwidth surrounding internal. What exactly are these? How these things are important? A sensor with a given bandwidth will be or a spectral band with a given bandwidth will be more sensitive to incoming radiance within that particular bandwidth. That is please see this particular figure. On the left side, I have what is an ideal sensor response? How an ideal sensor or in theory, how a sensor should response to incoming signal? Let us assume there is some bandwidth scheme for the, we will take the same example. Let this lambda C central wavelength be 0.49, let this be 0.46, let this be 0.52. So this sensor or this band collects data between 0.46 to 0.52 micrometers. So this is the case in theory or in ideal response, an ideal sensor should not produce any output for any radiance coming in wavelength less than 0.46 micrometers and similarly for wavelength greater than 0.52 micrometers. It should not produce any output, output should be 0. On the other hand, any radiance coming within this particular spectral bandwidth should be producing signal with 100 percent efficiency. Like the sensor should collect all the energy coming within that particular band and should filter out or remove all the energy coming outside the band. This is how an ideal sensor or a sensor should work or in theory this is the concept. With this bandwidth everything should be or the output of a sensor is 0. Within the bandwidth the sensor should work with 100 percent efficiency. In reality this ideal response will not happen rather than having like a perfect ideal response like this we will have something like this what is given on the right side figure here. This shows the spectral response of different sensors TM, Landsat thematic mapper sensor, Landsat ETM plus sensor and so on. The numbers are different bands within the sensor. You can see like this is not like perfect like a box given here it is like it starts it is like slightly curved and it is not having 100 percent efficiency that is the relative response is not 1 it is slightly less even within that particular bandwidth the sensor response is actually not uniform non-uniform sensor response. Even within the bandwidth designated bandwidth sensor will not work with 100 percent efficiency in all the wavelength within the bandwidth say 0.45 to 0.52 means maybe in 0.46 it may have 100 percent efficiency in 0.47 it may not have and so on. So the incoming energy will not be measured at 100 percent of incoming level but with some amount of weightage. So a sensor with 0.8 relative response will just collect only 80 percent of incoming energy and so on. So essentially in reality a sensor response is not similar to what we saw in the ideal case there will be difference even within the given bandwidth. So that is what is given here. Certain bands has or certain sensors has like different kind of response in different different band. See this is band 8 for ETM plus sensor band 8 I told you this is like panchromatic band which collects data in the entire visible and NIR portion of the spectrum with a very improved spatial resolution. So look at this particular band 8 around this 0.5 micrometers and all the response is pretty low something around like just 0.6 whereas the response increases only around this 0.8 micrometers and so on. So within the selected bandwidth itself sensors will have differing response to the incoming radiance. So how people still define we see even within the band there is still some amount of complexity like sensor is not responding uniformly across all wavelengths even within the selected bandwidth. So how people define this bandwidth? People assume the sensor response curve is actually a Gaussian curve and then we get to a concept of what is known as full width at half maximum we will see it in detail in the next slide. So this is how normally the spectral bandwidth of a sensor is often defined the concept of full width at half maximum that is say this is like intensity of the relative spectral response say 0 to 1 factor we will assume. We assume the spectral sensor response is Gaussian in nature like given here or it follows it looks very similar to normal distribution say this is like response of one factor one or 100 percent intensity everything is exactly stored. So that is the case and if this is like a Gaussian function there will be some point at which the curve will be at 50 percent intensity 0.5 of relative response. So along the x-axis you project this and we will say that the full width at half maximum that is the width along the x-axis along the wavelength axis at which the sensor produces 50 percent efficiency is actually between 0.7 and 0.8 micrometers that is 0.1 micrometer bandwidth or this is like 100 nanometer bandwidth. So this is the bandwidth that is we are interested upon for this particular sensor. Here we assume the spectral response is Gaussian in nature that is for a given incoming signal a sensor will have like a Gaussian curve of response. So we will be able to define a peak point that is with 100 percent efficiency and then we will be able to define a range at which the sensor is equally producing 50 percent with in which the sensor is working with 50 percent efficiency. So for that 50 percent efficiency at which wavelength it is producing it we will find the wavelength and that will define the spectral bandwidth 0.7 to 0.8 in this example or whatever bandwidth we are this is assuming sensors have a Gaussian bandwidth. Now this bands are actually like defined we need sensors with multiple bands and hence for each sensor for each band we will use particular optics filters and proper detector elements in order to make each sensor sensitive to one particular bandwidth that is there will be a detector it will have a series of optical elements and filters before it those filters will remove unwanted wavelengths say if a detector has to sense only green wavelength or energy coming in green wavelengths 0.4 to 0.5 to 0.6 micrometers they will have filters before it which will remove all the all other wavelengths and only green will be allowed and also the detector element itself will be sensitive to this particular wavelength. So in order for us to get multiple or multispectral measurements or multispectral observations we use the optics filters optical filters and specifically made detector elements which helps us to collect data over different different bands. So all these taken together all these elements together will define to which wavelength the sensor is actually responding and that is why since many elements are involved and the complexity of the system increases and hence the response is not matching the ideal case what we saw earlier the response is not ideal but it is different. I told you in the concept of full width at half maximum we assume sensor behaves like the response is Gaussian in nature we will be able to identify central peak with 100% efficiency and then we will also be able to identify two points with 50% efficiency the whole width at 50% efficiency. In reality it is not possible for all the sensors like an example is given here in this particular slide. So this is like the relative sensor response of different bands of sensor like green band so this is like for green band and this is for red band this is for NIR band and this is for short wave infrared bands for different different sensors the sensor names are listed here primarily they are like launched by ISRO the sensors belong to ISRO. So we can see from this the spectral response of sensor is not even close to Gaussian instead of having like one single peak like this here we have like a flat curve there is like high amount of variation in this there is like a long tail and so on. So ISRO scientist used a concept of what is known as the method of moments in order to define the spectral bandwidth. So we are not going to go into the details about the method of moments interested people can look at the textbook fundamentals of remote sensing by Dr. George Joseph or you can also look at like the paper referred in this particular slide Pandya and others 2013. But the basic concept is people use statistical measures of very similar to mean and variance people use statistical measures and they try to define this spectral bandwidth. So why I am telling this here is full width at half maximum is not the only way how with which we define the spectral bandwidth. If you look at like some specifications they may put the bandwidth as this full width at half maximum like this they will put. So we have to assume that okay this bandwidth is defined assuming the concept of full width half maximum is followed. So what it means within that particular bandwidth we are very sure sensor will have at least 50% of response within that particular bandwidth that is what is known as full width at half maximum concept like just I will go back to this slide. So here if you look if the bandwidth is defined as 0.7 to 0.8 micrometers if that is the case the response from the sensor will be at least 50% of its peak value at least 50. So within this particular band it will always be at least 50 or more than 50 within that. So this bandwidth only we define as full width at half maximum. But method of moments is slightly different it works in the very similar concepts of calculating mean and variance for like a continuous distribution function we are not going to go in detail about it. But just remember full width at half maximum is not the only way of expressing spectral bandwidth but it is the most commonly used like mostly like this there is another way which is show people use for defining the spectral bandwidth of sensors. So now we have some idea about what the spectral bandwidth means within that particular bandwidth the sensor will have its maximum response. If we take into account the concept of full width at half maximum the sensor collects data with at least 50% efficiency within this bandwidth that is the bandwidth. What is or what will be the influence of that bandwidth in remote sensing data collection? So the band the location of central wavelength and the bandwidth around it will help us to identify or will help us to classify different features or different objects on the earth surface. So let us see an example here this in this particular figure the black dark line is actually a spectral reflectance of any one object let us assume. Some object we have measured the spectral reflectance in different wavelengths we have plotted it as like a thick dark black line. On below it we have what is the spectral response function of different bands say here we have many bands each having 10 nanometer spectral bandwidth here we have a smaller number of bands with 50 nanometer spectral bandwidth. So here we are following the concept of full width half maximum we are assuming all bands are behaving like in a Gaussian way okay. If that is the case so here we have more number of bands with much shorter spectral resolution or much finer spectral resolution 10 nanometer here it is 50 nanometer. So we will have more number of samples collected each black dot is one spectral sample each band collects data along the spectral reflectance curve because we have many number of bands with much finer spectral resolution. However here we have only four bands so there is only four samples. So using these four samples if we join them just imagine how clear we will be able to get this spectral reflectance curve. So this will be something like this so 0.1 here 0.2 here 0.3 here 0.4 is somewhere here it is the shape that we are getting here is much different from what we are getting here we are actually missing this absorption features. But if we use a fine spectral resolution with many number of bands we will be able to sample the spectral reflectance curve much with much more clarity or much in a more clearer way. So having many number of bands with finer spectral bandwidths will help us to properly collect information or the properly collect spectral information about the object. Say you have 100 bands for a same pixel if you plot the reflectance in 100 bands those imagine those 100 bands are very close to each other cantiquest bands. If you plot all of it wavelength and reflectance like similarly we will be able to exactly replicate or more or less replicate the spectral reflectance curve for that particular pixel it is it will be more clear. So that is why hyperspectral remote sensing developed. So hyperspectral remote sensing means hyperspectral sensors will have a large number of contiguous bands with finer spectral resolution large number means say the number of bands will be 100 200 and so on not like 10 20 hundreds of bands contiguous bands bands will be continuous 0.45 to 0.46 0.46 to 0.47 0.47 to 0.48 continuous bands much finer spectral bandwidth it will not be like 100 nanometers it will be 10 nanometers or even shorter much finer spectral bandwidth. So the advantage of having such more number of bands with final bandwidth is if you for a particular pixel if you collect reflectance for all the in all the bands and plot them like x axis wavelength y axis reflectance for each pixel if you plot we will be able to properly replicate the spectral reflectance curve for that particular pixel. Let us imagine the entire pixel is covered with vegetation. So we will be able to replicate the spectral reflectance curve of vegetation for that pixel almost all the absorption features everything will be very clearly we will be obtaining. So this is really important where to put your bands how many bands everything will define what we get as our spectral output. So this slide is actually another example of the importance of spectral resolution. So here you this is the spectral response or the spectral reflectance curve of vegetation this is how it will look for different wavelengths this is the reflectance. So this is let us say we are collecting data using a fine spectral resolution sensor with multiple bands. So there are like many number of bands each dot represents one one spectral sample. So and let us assume the spectral resolution is much smaller in the order of say 10 nanometers. So for each sample if you join each dot we will be able to replicate the spectral reflectance of vegetation properly it more or less represent the spectral reflectance of vegetation even if we join them linearly some features we may miss but we are still getting the major absorption features. Here we are not having continuous bands. So these bands are non-contiguous here the bands are also contiguous continuous bands in this case non-contiguous band with us quite broad so coarser spectral resolution if that is the case just join them we will not be able to get the proper spectral reflectance curve of vegetation. For vegetation it is okay having a smaller number of bands will provide lot of information but for other features especially like earth science people who work towards direction of minerals identifying different different types of rocks for them each and every minute absorption feature in the spectral reflectance curve is very important. Maybe we will see little bit more detail about the absorption features and all in later lectures but what I want to say is the number of bands the central wavelength of each band and the spectral bandwidth all of these things that is essentially the spectral characteristics of the system will define the amount of information or the proper spectral information that we collect because only within that particular spectral bandwidth we are collecting data. You can just think it analogy with spatial resolution okay in spatial resolution what happens whatever the features present within the JFOV everything will be averaged out and we will get one single value right similar concept here whatever be the spectral reflectance within a given bandwidth let us say a feature has something like this okay let us say the bandwidth this is the spectral bandwidth so this is the reflectance. Whatever be the reflectance we will be finally getting an average reflectance for the band because this is our bandwidth lambda mean lambda max we will be getting a average reflectance recorded in our sensor we will miss this fine absorption feature. Let us imagine now we have a sensor or we are using a very fine spectral bandwidth like this in this case the reflectance may be somewhere here because of our fine bandwidth if we average everything this will be somewhere here and hence say now I have like 4 bands 1, 2, 3, 4 so this will be rho 1, rho 2, rho 3 and rho 4 if you plot rho 1, rho 2, rho 3, rho 4 it will be like this rho 1, rho 2, rho 3 and rho 4. So if you use many number of fine spectral bands we are able to get this absorption feature properly with some accuracy if we use a single broad band everything is averaged out you are getting only one rho as output. So the spectral characteristics of a system will define the information we collect in the spectral space whatever the energy coming in within that particular spectral bandwidth you can think of they will be averaged out. So find out the spectral resolution we will be better able to capture the finer absorption patterns within the spectral reflectance curve anyway when we deal more about spectral reflectance curve these concepts will be more clear much more clear to you all. So this line gives you spectral characteristics of some sensors this is ETM plus sensor, Aster sensor, MODIS sensor and so on. So here you can see what is known as a PAN band written as PAN which is PAN chromatic. So PAN chromatic generally means all colors PAN we can think it of all colors chroma means colors. So essentially PAN chromatic bands spans a very large or a very broad spectral resolution say maybe here 0.5 to 0.9 micrometers. The reason for having a PAN chromatic band is to sacrifice spectral resolution but get high spatial resolution. So we will talk about this in detail like the tradeoff between different resolutions but still imagine PAN chromatic band essentially means a band most likely in the visible and NIR range PAN chromatic generally means a band which is in visible and NIR range it will have a very wide bandwidth say spanning across entire visible and some in NIR where we are concentrating on increased spatial resolution instead of or the cost of spectral resolution we are losing spectral resolution we are increasing the spectral bandwidth thereby losing spectral resolution but which will help us to achieve high spatial resolution. Maybe we will see it in detail in the later classes but just imagine PAN chromatic band means a band with a large spectral bandwidth in the visible NIR portion mostly blue will be removed out because we know blue undergoes lot of scattering produces haze in the majoring. So in PAN band people will remove blue so green red and NIR these three will be combined to produce one single band. The advantages PAN band will have high spatial resolution in comparison to other bands. So Lancet has a PAN chromatic band and each band defines the number of bands the system has and its spectral bandwidth. You can see like how wide this particular band 7 how wide this band 5 in Lancet etm plus whereas in modus most of the bands are pretty narrow. So modus has these bands has fine spectral resolution than Lancet or Aster sensors. So the selection of spectral characteristics of a sensor. So the choice of spectral bands or the spectral characteristic of a sensor is not arbitrary. You cannot just pick this sensor should have 10 bands with these bandwidths that is not the case they are not arbitrary. Each thing has to be selected with proper reasoning. Some of the factors that one should consider for selecting the spectral characteristics of a system are first thing the feature of our interest should be identifiable in that band. Let us say vegetation take an example later class we will see that vegetation can be better studied using a combination of NIR and red bands. So the sensor should essentially work in NIR as one band and red in one band. So the feature of our interest should be identifiable in that particular band. So which band the feature has feature produces a distinctive signature select those bands select those wavelengths. Second thing the selected window or selected bandwidth should be located within atmospheric windows that is let us say like vegetation shows a characteristic water absorption band like presence of liquid water inside a leaf will produce characteristic absorption bands around like 1.4 micrometers 1.4 1.9 micrometers and all. But atmosphere also has water vapor. So if you put any sensor around like say 1.4 micrometers and if you send it to space whatever the energy coming in from the vegetation will be absorbed by atmosphere itself we would not get any signal in the sensor. So if you want to study certain characteristics about the object the band should be selected such that the band is not in atmospheric absorption window. It should not be an atmospheric absorption band it should be in atmospheric window where the atmosphere is cleared where it transmits radiation. So if we want to study about Earth's surface features the band we select must be located in atmospheric windows. Third thing proper sensor elements should be available that is okay we decided this is the bandwidth I am going to use for studying this feature that is present in atmospheric window no problem. But still we should have some detector to collect that energy right what if no detector available in Earth will be able to collect energy in that particular band it is a waste right. So we should have proper materials using which we can produce sensors which can collect energy in that particular wavelength. So it is not that in olden days like when the sensor technology was evolving only certain wavelengths can be imaged or can be observed certain wavelengths cannot be observed later with the latest technological development now we are able to observe in many different wavelengths now it is okay but in olden days it was a major problem. So people will say okay use this particular band this is of our interest but sensor will not be available in that particular band. Say if I ask if I give you like a normal camera and ask you to take a photograph in NIR band will it be possible no right the camera should be attached with an NIR filter or NIR sensitive sensor basically a sensor which produces output to NIR signals then only we can collect that energy. So that should be availability of sensors in that particular band then the band should be uncorrelated to the extent possible uncorrelated in the sense let us say we have two bands two neighboring bands say if in band 1 if dn increases in band 2 dn increases in band 1 if dn decreases band 2 dn decreases. So essentially you have like a similar response between band 1 and band 2. So the output finally we get from these two bands will be more or less the same or we will get equal amount of information from both the bands if one increases the other increases if one decreases other decreases. So essentially the bands which we choose should give us new information like I told you like hyperspectral sensors was really wonderful but hyperspectral sensor has a problem of data redundancy and data dimensionality that is they have lot of data hundreds of bands but the information in all the 100 bands will not be unique the information 100 bands will be repetitive in nature repeated in nature. Similar information will be present in many different bands each band will will occupy a large amount of memory storage in our storage system in our display system and all. So everything is like a having a large number of bands has its own problem it has it occupies lot of storage in the memory. So we should choose correct number of bands I do not need 100 bands I can identify the feature only with 10 bands choose that particular 10 band. So that is where like in hyperspectral data processing even though there are like hundreds of bands people will select bands few bands that is of useful for the selected application. Then only this the data processing will go smooth else there will be so much of memory consumed so much of storage will be wasted. So the bands should be uncorrelated each band occupies or produces large volume of data like if you download one Lancet imagery each scene will be like in 1 1.2 gigabytes gigabytes. So imagine for to cover the entire earth how many gbs of data will be produced every day or how many tbs of data will be produced every day just imagine each and each and every added band adds to our increased memory storage. So the number of bands we put in a system should provide us as unique information as possible they should not be related to each other. So maybe like if you come across like digital image processing courses there they will explain the concept of like identifying similarity between data removing data and so on. So the bands we are going to select should be uncorrelated to the maximum extent possible. So the features that we have listed in this particular slide will help us to select spectral bands for any given application. So as a summary in today's lecture we have seen concepts related to the spectral characteristic of a system. With this we end this lecture. Thank you very much.


use thoroughly and if you've got a cable on, put it on the wire and let me see them. I don't see enough of their attitude to get a feel of it and watch the Westmoreland messages of any consequence and get them to me. The second thing, as any feeler's out anywhere, is your imagination and get two or three others going that wouldn't hurt if you could get Wilson to do something with somebody or if you could get the polls to do something to do it, if there's any hope of anybody even using it. We don't want to hear anybody saying, well, we want another pause, but if there's any hope of anybody making any use of this, we'd like to know it without making a commitment and I don't know who I get to talk to, but I guess somebody, Wilson, we need that court of the public opinion a little bit and he's always likes to get into it and Canada too and when somebody drops or had port been there 45 days and nobody touched them, haul them in that way because a single motor plane drop over and drop a handkerdam ship out, work like hell there. But they just don't have any port facilities and we've either got to find some new port facilities or we've got to find some new methods and we haven't done either for 45 days. Tough, able operator and he says, you're Marston, who's not fit and fell down on the job. I didn't have the personnel involved, but it sounds to me like we need some real industrial expeditors out there that I imagine you would think you ought to say that you're seeing reports here about port plugins and let's see what remedies we have and what solutions before we decide whether we're going to bomb anybody and I don't want to get the worst into it. Well, other general thanks, he's damn easy to go tackle a teacher, but when he turns around they tackle him. I don't know what he's going to be prepared to do, how he, how's he going to defend himself in this one port we got. I'll try to talk to Russ, because he there, I will try to talk to him and get he and Tommy in and your officer will go over there and they all try to think about three or four things that you could do and let's evaluate whether second woman taking 48 hours is worth it or not. Go to Westmoreland if it is, well then we'll decide it and let's talk through four hours, maybe 30 minutes from here and get to damn networks and just running people crazy. Within every 30 minutes they extort, we're not bombing and the Air Force says they don't know why they're not keeping the mouth shut. Have you been hearing the Air Force's announcement? I've seen it. Air Force announcements outside gone as we don't know why we're not bombing, we ought to be bombing as they've stopped us. His lodge back yet were my message to the head of the Philippines with him today, just giving out interviews for a man.  I told him he could worry about his own goddamn damage and go to worry about the world a little bit. Well, we will take care of his image here. I don't think it's wise to have him and make any proposition to anybody about anything and I think we're just going to say to him what they ought to do, that the best thing he ought to do is just say that Vietnam is important to that area of the world and if we get licked there we don't know what to how they'll stand up. Truth we won't say that's a matter you better talk to Bobby's and the Teddys and everybody else now, it's got any ideas. Let's just have them and let's deal them out and let's see if the New York Times has been that daddy of the pause if they've got any suggestions. I don't like it because we have it now. Well, if they tell us who the hell's interested in it we might announce it then just tell them. If anybody's interested in it, the Russians are not interested in it. We can't be interested in it. Tell us who the hell's interested in it, we might be interested in it. The Russians are not interested, they don't seem to be interested in it. I know I'm not interested in much of a truth. I don't think he's anybody interested in it except Johnny Oaks and he doesn't have any truth. I think you might say to him we've gone two, three days and we're willing to go for two, three months if anybody can show us anybody's interest but we've contacted everybody. Now if y'all got better sources, if Scotty's got a better source than we have we'd like to have it. And I would certainly explore it with Grinowski a little bit, let him make some pitch to somebody and maybe the Canadians will let them make a pitch and just to take care of their Nobel prize people and maybe Wilson. Why is that bad on him if you wait for him for delaying longer get back to us, they'd get back to us, it wouldn't matter.


by Sy Howard promised his mother that he would write and tell her about his adventures. So now let's read Luigi's letter as he writes to Mama Basko in Italy.  Yes, this is true. I'm always the wiser, the slow one in a family. Take even a thing like America. Humber discovered it to 450 years after Columbus. Tomorrow, Mama Mia, all Americans are going to celebrate the Columbus a day.  He's decided to discover America in 1492. Because if he's tried to discover it today and he's got nobody to bring him over from Italy, he's never gonna get passed the immigration department. Mama Mia, if Columbus could only see his America, how it's a look today, he could not recognize it. Everything is a change. Instead of a little cabin is a building. Instead of a forest is a road. And instead of a wild Indians is a trafficker cops. Also, Columbus would be surprised to see such a big inventions like the radio, the telephone, the airplane and the greatest American intervention, the hot dog. But tomorrow is going to be a big day for me. All of the night school classes that they're gonna have a Columbus a day exercises in a main high school. Every classes are gonna do something.  Of course, some are not really gonna sound like a Columbus because I'm a speaker English. It's too good. Well, I'm a finish of this letter later, Mama Mia. It's a time and hour for my night school class and I'm gonna hardly wait to see what is it like. This play my teacher Miss Pauling is going to give us America. I love you. You like a papa to me. From ocean to ocean. Here, Mr. Olson. Mr. Schultz. Miss Schultz, you are beautiful. You are wonderful. You are simply gorgeous. Mr. Schultz, why that sudden outburst of affection? Because I didn't do my homework today. Mr. Schultz, you know that every time you come in without your homework, I keep you in after school. Now, why do you insist on coming in unprepared?  Mr. Schultz.  Our fine city spends money, so you should get an education, but you just waste it. Now look at me. I'm looking. I give up evenings with my family used to come to school. I give up gymnastics. I give up bowling. Olson, why don't you just give up? Let's have no arguing. Mr. Schultz, I'm keeping you in after school. Oh, she still loves me. That's enough, Mr. Schultz. Now, class, as I told you last week, tomorrow we're holding the Columbus Day ceremonies at Franklin High. And I don't suppose we have to review the facts about Columbus Discovery. That's right, Miss Pauling. Everybody knows he discovered America in 1492. Thank you, Mr. Basko. Don't thank Luigi, thank Columbus. I have here a copy of the little sketch you will present tomorrow night. It runs only three pages and it concerns Columbus trip to America. Miss Pauling, if I may be permitted an interruption, will we all accept the fact that Columbus discovered America? But the real truth is, someone else did before him. Olson, how can you talk like that? But that's a fact, Luigi. A fact that Olson is sometimes you're not so smart. I'm sorry, Luigi, but someone else did discover America. He's right, Mr. Basko. What? Who did it? An other Italian, Amerigo Vespucci. Hey, you know, Olson, you're really smart. For the minute you were worried, hey, Luigi, where I'm sure to know, Olson is never wrong. As a matter of fact, class, Columbus discovered America by accident. He was really looking for a short trade route to the Indies. Olson, how better you could even tell us where he looked like? Yo, I can.  If anybody sees this man, notify the police or you're lonely. We'll have to make a fine showing tomorrow night. Our principal, Mr. Petrie, will be there, as well as Mr. Campbell, head of our Board of Education. You know, the night school session is his pet project. Don't worry, Miss Pauling, we'll do a fine job. And I'd like to delegate somebody in the class to supervise the presentation of the Columbus play. Miss Pauling, who's it that they're going to be? Mr. Basko, I was thinking of you. Me?   I see you have the backing of the class. Now here's the play. Now you assign the parts. I'm sure you'll have no trouble memorizing it. It's very short. Miss Pauling, I got the bad memory. I can't remember lines. Well, you have to play some part. All right, then make me the ship. Horowitz, do I detect an error? Did Columbus come over on one ship? Certainly, the Mayflower. You Horowitz, even I know better. What's three ships? That's very good, Mr. Schultz. Suppose you name them. With pleasure. The name of Columbus three ships, what? The Nina, the Pinter, and the Santa Anita. You're the first two, but you guessed at Santa Anita. At Santa Anita, what else can you do? Miss Pauling, Miss Pauling, when we're doing a discipline, can I give it the patch to anybody I'm alike? Oh, yes. It's all your responsibility, Mr. Vasco. Now you put those pages in your pocket and don't lose them. And I'm sure I'll be very proud of you tomorrow night. Oh, don't worry, Miss Pauling, you will. We'll be a knockout, like they say in Hollywood. You're identical. Try identical, but we're going to be so sensational, they'll make us put on a Thanksgiving Day play, a Christmas play, a Lincoln play, and on July 4th. Yes, Schultz. A legal holiday. We take the day off. Hey, Vascolly. Hey, Vascolly, guess what? Tomorrow I'm going to be Columbus. What? Sure, it's all decided. I'm going to be Columbus. All right, Luigi, and I'm going to be Napoleon. I said two nuts to go out and talk to the squirrel. See, we're going to have a Columbus Day play tomorrow. It is in my pocket, and tomorrow morning, Schultz, Harowitz, and Olsen, they're going to come to my store and we're going to rehearse. Oh, wait, wait.   Luigi, instead of fooling around with that, a night of school with that two and two is a four, and three and one is a five. Well, wait, Vascolly, you all are wrong. Three and one is a not the five, and three and one is a four. Three and one is a machine oil, and don't tell me about it. You might have fallen around with this baby play stuff. You should have been thinking about your home, your wife. Vascolly, what are you talking about? I'm not going to get a home wife. Luigi, this can be arranged. No, Vascolly, please. I'm not talking now about your daughter, Rush. Why not?  Luigi, sometimes you don't use your ignorance. Think of this. What would you rather have? A skinny, nervous, underweight, the wife, or a bigger, happy, overweight, the wife? Vascolly, I'm like a nice medium, my girl. You're going to take what I got. So, please, Vascolly, I'm going to go now to my store and figure out who's going to do what in my play. All right, go, go, go.  You look more like one of the barnacles that was on as a ship. Vascolly, I'm going to be a good Columbus. Now, for you, excuse me. Wait, wait, Luigi. Reason you don't want to marry Rose, that's because you don't spend enough time with her. I'm going to just take it. Why don't you put her in your play? You get to know her better, you begin to like her. No, Pasquale. Don't talk so fast. There's a part for a girl of Columbus who's going to Queen Isabella. Rose is a beautiful. She's looking like a Queen Isabella. She's looking more like the Queen of Mary. Now, Pasquale, no, no, don't push. I'm going to go to my store now and take the three pages and copy out all the parts and... I'll see you later, Luigi. Pasquale, Pasquale, in my play, I'm going to have it right here in my pocket and now it's a missing.  How could you pocket a missing? I'm not in the pocket of Pasquale. I'm not in the pocket of my play. Where is it? The where it could have been? Search me. I mean, go look. I don't know. Come on, mummy, it's terrible. Maybe I'm left in a trolley car. I'm going to go out to look. Pasquale, if you find her, please let me know. Sure, sure. Let him know. I'm going to let him know nothing. Come on, I'm not in the pocket of a little Columbus play. My, my, three beautiful pages. Six beautiful pages. Twelve beautiful pages. Eh, what's the difference? There's a lot of pieces. Now, in fact, at Luigi Vasco's Adventures in Chicago, we turn to page two of his letter to his mother in Italy. And so, mummy, I'm in a terrible trouble. After I'm left to Pasquale last night, I'm going to turn to Chicago upside down and looking for my play. Near the school, I'm going to see a cop, and I'm going to say, please, did you see my Columbus play? Cops have said to try the handball court. But a cop is no helper. So for hours, I'm going to walk around in the streets, looking and looking and looking. All I'm going to find was a two pennies, a high bounce ball, and I want to try the transfer for a good till the 9 o'clock PM east of Bond. Again, I'm going to keep her looking. And I got her the sidewalks of garbage cans. One old lady is a follow me for two blocks, and then she's a put a diamond in my hand, and she's a say, you put a man to take this for a cup of coffee. I'm going to tell her, lady, please, you got a wrong idea. I'm a no selling a coffee. Anyways, the morning now, I'm tired of from a no sleep. And in any minute of my friends, they're going to come in to rehearse the play that I'm not the guy. Luigi, my fellow pooper. Well, am I the first one in for rehearsal, or am I the rotten egg? I'm sure it's just a bad news. I'm lost to Columbus to play last night. Lost to play? Oh, no, Luigi, did you look for? All over all night, I was looking the streets, and old ladies, I want to buy a cup of coffee for me, and a cup as I told me, Columbus, it was a plain a handball. Oh, Luigi, are you for shimmelt? Now look, are you sure you lost to play? I'm sure I said terrible. Smile, Luigi, smile. Like the cow said when it tripped and fell down, what's the use to cry over spilled milk? I'm not going to smile. It wasn't my responsibility. I'm lost to play. I'm not got the Miss Polling's telephone number, school is closed. I'm not going to find it. Shoots, I'm feeling so bad. No, wait, wait, wait, wait, Luigi, into my head, an idea just pooped. At last tonight, we was all looking at the play. Yes. Well, I remember most of it. You do? Sure, sure, smile, Luigi. And what I don't remember, I'll write myself. Well, Shoots, you think you know enough about the Columbus to write this a play? Luigi, don't worry, facts ain't everything. Riders always use it, the imagination. Now look, look at Mark Twain. He never owned a fruit stand, still he wrote Huckleberry Finn. It was time arguing. Mr. Delicatessen, a man, what are you doing here? Until you came in, I was breezing fresh air. Pascuali, now if you don't mind, we are busy. I got to write a new Columbus play for Luigi because he lost the other one. That's right, the Pascuali Shoots says he's a member most of the play. Oh, that's nice. The Shoots, maybe you write in a powder for my daughter Rosa, eh? Absolutely not. And that the case, and maybe I'm going to go to the school tonight to tell him Miss Polling, and maybe she's at the side, it would have been better if you have no play at all, eh? What? You want to do a thing like this, Pascuali? Would you be a stool pigeon? When it's a concern of my daughter Rosa, I'm even going to be a vulture. We are trapped. All right, we give a part to Rosa. No, wait, wait. It's even a help. Horobitz has got such a bad memory. Instead of giving him two parts, we're going to let Pascuali play one. Thank you, Shoots. I'm a little like at the brag, but my wife thinks I've got a profile like a Barry ball. I think you've got a profile like Barry if it's Gerald. Shoots, here comes Olsen and Horobitz. Yeah, we've got no time to lose. Give me quick, a pencil on the paper and we start to write. Well, Shoots, Shoots, I'm afraid. Oh, Luigi, cheer up, smile. Don't worry. Tonight, when all this is over, it will be an experience you will never forget. And then a speck, a light, a light, a light, a light. It grew as grew to be time's burst of dawn. He gained a world. He gave that world its greatest lesson on... It was Henry Robinson of the graduating class of the LaSalle Street Night School, reciting the poem Columbus by Joaquin Miller. And very good indeed, Mr. Robinson. Now, ladies and gentlemen, we close our Columbus Day program with a short playlet to be performed by our charming Miss Spaulding's Night School class up at North Holster Street. As they say in show business, take it away. Go ahead, Luigi. Go out on the stage and read what I wrote. All right. What a wits to get ready. You come on the stage after me. Hello, ladies and gentlemen and friends and Miss Spaulding and Mr. Petry. That's the principal. And Mr. Campbell had support of education and friends and ushers. Columbus. Christopher Columbus was a Discover America and a Columbus a day. Well, for the 19th of 1492, this period of the 1490s was a very happy period and is now known in history as the gay 90s. Generator to discover America was not such a cinch. History proves that Columbus had a tough time. Now, to give you a glimpse, we've toimed back the pages of history to that famous scene between Columbus and Queen Isabella. Come with me and glimpse a little. Queen Isabella, I'm like to ask you a big favor. What can I do for you, Columbus? I wish you to discover no route to the endings. I'm asking you for ships. No. All the explorers I give ships to, they never come back. This is because the world is flat and they fall off the edge. But the no queen of the world is not the flat, he's around. Here, I'm a prove it to you with this egg I'm a brought. I'm a standard on the table. Watch. Excuse me, ladies and gentlemen, Schultz has forgot to boil the egg. Brave voids from a brave man. Columbus convinced the queen and got three ships. The Nina, the Pinta, and the, it was three ships, believe me. But did Columbus have an easy time on the ship? Toim back the pages of history for another glimpse. Another day still in no land. That's no good. Where's my first to mate? First to mate? Aye, aye, sir. First to mate, the Nina the ship's alive. On the fifth day, the main sail fell down. The eighth, ninth, and tenth days, we went through a hurricane. The sixteenth day, a fire broke out in the gangway. The twenty-second day, the Nina and the Pinta disappeared. It was raining, terrible. And yesterday, the cook fell overboard and got swallowed by a shark. Captain Columbus, I'm afraid. Why? Any day now, we may run into bad luck. Like I'm always to say, sail on from a brave man. A few days passed, again the glimpse. Captain, it is now thirty-four days we've been sailing. Still no land. What are you two Columbus? We just sprung a leak. What are you gonna do to stop at the lake? Well, I already got a pan under the ship. Sail on, sail on. All right, the Horowitz. The discoverer finally found land. And he deserved it too. Anyway, he and his first mate went up on the beach and all they saw was Indians. So now, let's take our last glimpse. Columbus, I am a discoverer in a disland. Any one of you Indians, can I say a few words? What are you saying? Is that all you're gonna say? You only ask for a few words. Speak very well. Then a call. Pocahontas. The men of my ship are the birds in the sky, the fish in the ocean. I'm an almeca-circle. And I'm a hereby name of this place, Columbus Circle. Sure, sir, it was a terrible night. The way people were laughing at us.  What are you talking about, Luigi? We were sensational. Orson, Horowitz, what do you think? I don't know. I was too nervous to think. Well, I told you, sir, some of those things you wrote.  Mr. Basko, what happened to the play I gave you? I'm sputting. I'm explaining. Oh, our Columbus. So you're responsible for this. Well, what have you got to say? Don't just stand. The play Mr. Sputting hasn't given me. I was unable to carry responsibility. You're absolutely right.  I'm going to have you expelled from night school. Expelled? Oh, but Mr. P- I've made my decision. But, but, but you can't do that to Luigi. He loves school too much. You break his heart. If you saw Luigi out, I'm quitting school too. Even if it means spending evenings home with my wife. Please, Mr. Principal, you can't despair Luigi. I'm the one who brought him from the older country and I'm not how much his education is a meaning to him. I was the one who took away the play from Luigi and tore it up into little pieces. What? Basko, are you dead of that? I'm sorry, Luigi. I've heard enough. My order remains. And, Miss Spalding, I want to speak to you tomorrow too. Put a pan under the ship. I haven't heard that one since potash and pearl murder. Petrie, you old sour-puss. What? Ever got into you allowing such a wonderful bit of entertainment on your program. Well, Mr. Principal. For 20 years I've been hearing the same old poem, play, and pageant. Who was responsible for the sketch? Columbus Circle. This man, right here, Mr. Luigi Basko. Young man, they'll teach you a lot of things in night school. Reading, writing, and arithmetic, but you've learned one of the most important things we can teach you is one of the great qualities of an American is the ability to laugh at himself. Isn't that right, Petrie? Yes. When he's three days, they say he'll laugh. You're right, you're right. It's funny, all right. Believe me, there's a lot to laugh at. Not even.  I'm gonna laugh, too. Come on, Aros. Happy tonight. They're laughing a lot. You know how there's a city in the United States that's called Columbus, Ohio? Well, I was just thinking, what would happen if your son, Luigi, was to discover America? At the city, it would be called Basko, Ohio. All of a sudden, instead of a Columbia Records, it would be Basko Records. Would it be a Basko picture company? Basko broadcasting a system. And in a school, all the little children, they would be singing Basko the Gem of the Ocean. And I'm your son, Luigi Basko, a little immigrant. You should listen next Tuesday at the same time over most of these stations when Luigi Basko writes another letter to his mama Basko describing his adventures in America. Life with Luigi is a sigh hard production and is written by Mac Benhoff and Lou Derman and directed by Mac Benhoff. J. Carol Mash is starred as Luigi Basko with Alan Reed as Pasquale, Hans Connery as Schultz, Mary Schiff as Miss Balding, and Jody Gilbert as Rosa. Joe Forte as Horowitz and Ken Peters as Olsen. Music is under the direction of Lud Gruskin. Bob Stephenson speaking. CBS tops off its Tuesdays programs with one of the greatest quiz shows on the air, Hit the Jackpot.  And Danny Seymour is here to quiz studio contestants and listeners from coast to coast. Have you tried your wits on the current Secret Saying? Well, stick around and stay tuned for Hit the Jackpot, which follows immediately over most of the same CBS stations. This is CBS, the Columbia Broadcasting System.


Hello, hello, how's everybody doing today? This is rich from rich TV live, and we have some breaking news for you today Breaking news for you today here live on rich TV live. Hope you all had a great weekend and We have some breaking news for you today and Yeah, been an interesting weekend lots of things happening and the markets just Been under a lot of selling pressure right market's been under a lot of selling pressure the stock market's been under selling pressure The cryptocurrency markets been under selling pressure and we've got some news for you today So thank you guys for joining us if you like the video Please smash the like button comment down below share the video everywhere and subscribe if you're learning how to trade You can join us at richpigsdaily.com and you can learn how to trade stocks and crypto currencies Obviously has been a tough for market recently markets coming back from all-time highs in both the stock market and the cryptocurrency market So there is incredible opportunities in my opinion in the market right now for those that understand How to find them? So let's talk about the news that is breaking news this morning breaking news this morning alright, so The big news that I want to break to you today is from Pharmathare Pharmathare announces FDA approval of ketamine. That's right. Finally. We've been waiting for this We've been waiting for pharmacare to get their FDA approval and they've got it Finally now getting the FDA approval of ketamine ind in the treatment of Parkinson's disease This is breaking news big breaking news from Pharmathare breaking this morning the symbol for pharmacare is PHRM in Canada the symbol for pharmacare in America is PHRRF That's a symbol for pharmacare if you guys like the video, please smash the like button comment down below share the video everywhere and subscribe Good morning, Steven. Good morning, Amjad Hope you all have a good morning. Hope you're ready for a big week Obviously markets have been tougher recently and this is where Investors get paid Everybody wants to buy stocks and buy cryptos when the market's high, but that's not the way to trade You want to buy when they're down? But people get scared when they're down because they're down so they don't want to dump any more money into the market Well when stocks are down, that's when we're buying when when stocks are down We buy the dips and when stocks are up. We're selling. We're taking our profits. So This is really where Investors make their money in markets like this. So let's talk a little bit about pharma there holdings limited Pharmathare announces FDA approval of ketamine IND in the treatment of Parkinson's disease. This is big breaking news. I'm literally breaking this news to you first So pharma there a psychedelics biotech company now remember psychedelics have been under a lot of selling pressure be aware of that Okay, it's not a super hot sector right now when I do these videos They're strictly for information and education purposes Please do your due diligence do your research before you invest in anything that we talk about here on rich TV live Okay, and what I'd like to do is open the discussion to know what you guys think about this news Do you think that this is a company that has potential? Do you think that long-term? They've got a chance to be successful Obviously, this is big news that they have announced FDA approval of ketamine IND in the treatment of Parkinson's disease Do you know anyone that's suffering from Parkinson's disease? How much has that affected their life and could this be a game-changer? So Pharmathare is a psychedelics biotech company pleased to announce the US Food and Drug Administration FDA has approved the company's Investigational new drug IND application to pursued with a phase two clinical trial to evaluate the safety efficacy and pharma pharma cauconetics of ketamine in the treatment of levodopa induced dyskinesia in patients with Parkinson's disease LID-PD Pharmathare expects to begin enrolling patients in the phase two clinical trial in Q3 2021 Assuming the phase two clinical trial is positive The company will request a meeting with the FDA to discuss its plan and obtain an agreement to move into phase three clinical study under 505b to regulatory pathway next year Big breaking news. What do you think of this news and like I said to you guys about pharmaceuticals and about Psychedelic stocks. They're early. We're early to the party, right? They're two years away from having revenue But some of these companies that we've been talking about are going to absolutely explode just like mind medicine did Mind medicine went up over a thousand percent after we brought it to you first and for the first six months They didn't trade very well. They were stuck for six months And they didn't even move and then all of a sudden out of nowhere they exploded So at the very least what you want to do with these companies put them on your watch list put them on your radar, okay? Fabio Cianelli who we've had on our show chief executive officer of Pharmathare said The FDA's acceptance of our IND application for ketamine to treat Parkinson's disease is a significant milestone for us The FDA IND is our first of many we will aim to obtain and we're one of a few psychedelic focused Biotech companies that have an IND approved for the FDA for a recognized psychedelic drug the IND paves the way for us to expediously evaluate ketamine and other psychedelics via the FDA regulatory pathway in various mental illness Neurological and pain disorders. We are committed to building a rich product pipeline of novel uses Formulations and delivery methods of psychedelics and with our FDA IND in place We now have the foundation in making Pharmathare a global leader in psychedelic based therapeutics And like I said, we're early to the party This is just the beginning for Pharmathare and this is just the beginning for psychedelics Parkinson's disease is a debilitating disorder that affects over 1 million people in the US and more than 7 million people worldwide There is currently no cure for Parkinson's disease Although some drug combinations are used to treat the disease symptoms the global Parkinson's disease market is expected to grow from USD 5 billion in 2019 to USD 7.5 billion by the end of 2025 So that's huge growth potential folks and is estimated that the potential market opportunity for lid dash PD to be over 3 billion USD in the US alone. Wow This is a huge market opportunity folks and you guys are getting a chance to learn about it first About phase 2 clinical trials the clinical trial is titled a multi-center phase 2 randomized double-blind Perspective active placebo controlled trial of sub anesthetic ketamine to treat Levodopa dash induced Diskincia in subjects with Parkinson's disease It is anticipated that up to eight clinical sites in the US will randomize a total of up to 36 subjects to the investigational product ketamine or active control Mitazolam the primary endpoint of the study is the change in the united in the unified diskincia rating scale Udy srs total score from baseline to week eight secondary endpoints of the study include the change in total objective scores of the Udy srs total daily off times as Assessed by subjects completed 24-hour diaries and change in the UP DRS total and some scores of Motor and diskincia from baseline to week eight because lid can marked affected a lid can markedly affect a Parkinson's patients every day activities a Reduction in lid could improve the patient's quality of life. It's a game changer I mean what these guys are doing is absolute game changing and it's important that we're identifying undervalued underappreciated underexposed Opportunities before anybody else in the world and I'd love to know your opinion. The company has assembled a prolific scientific and clinical experienced Team in Parkinson's disease including Dr. Scott Sherman and Dr. Torsten Falk from the University of Arizona Dr. Alberto Espe from the University of Cincinnati and Dr. Robert Houser from the University of South Florida So what is the ketamine potential in Parkinson's disease? Ketamine is an FDA approved N methanol D aspirate NMDA Receptor-moduling drug that is widely used and as an aesthetic agent either alone or in combination with other anesthetic agents The possible therapeutic effects of low-dose ketamine on lid was noted in a retrospective analysis of PD patients Who received ketamine for pain relief? During this analysis it was observed that the patient's experience in improvement in lid lasting several weeks beyond treatment These results were corroborated in a test of low-dose ketamine in a rodent lid model And this positive effect has been examined in a controlled study Ketamine may also have additional benefits in the treatment of pain and depression which are frequent frequent in Parkinson's disease about Parkinson's disease so Parkinson's disease is terrible and I've known people that have had it and Really destroys their life. It affects their life. I'm not gonna say it destroys their life, but it affects their life in so many ways They almost have split personalities. It's um It's it's terrible. There is currently no cure for Parkinson's disease, although the Ideology of Parkinson's disease is not fully understood. It is thought to result from a loss of pigmented Dopamine ergic neurons in the substantia and nigra and their stradal projections leading to dopamine deficiency in the Stradium this ultimately affects the corticostridal system that controls movement as a progressive neurogenetic disorder of the Central nervous system that primarily affects the motor nerve system symptoms of Parkinson's disease may emerge slowly and include tremors rigidity Brady kinsia and Postero instability Also patients may experience non-motor symptoms such as autumnic dysfunction orthostatic hypertension constipation bladder dysfunction psychiatric depression Cognitive and sensory symptoms pain, I mean there's a long list of of Really negative effects of Parkinson's disease So what these guys are doing is making a world of difference and live in a world where we need more People doing something to make a difference these non-motor symptoms become more common as the disease progresses treatments including levodopa and dopamine agonists Which restore the dopamine deficits in the brain have been employed for almost 50 years However with continued treatment using levodopa dose-limiting motor side effects often emerge This includes the emergence of abnormal involuntary movements termed levodopa induced Diskinsias which can be identified in about 50% of patients within five years after Initiation of levodopa treatment and in almost all patients within 10 years post treatment initiation these side effects often limit further dose increases in Dopaminurgic therapy There can be no assurance that the FDA will support any potential request for an expedited path to approval or further development for ketamine in the treatment of Parkinson's disease About pharma there holdings so the symbol for pharma there in Canada is PHRM and the symbol in America is PHRRF Pharma there holdings limited is a psychedelics biotech company focused on the research development and commercialization of ketamine and novel Micronetal patches for the delivery of psychedelics to treat mental illness Neurological and pain disorders love to know what you guys think what do you guys think of this news? This is the big breaking news, and I'm breaking to you this morning Love to know what you guys think love to know what your guys opinion is on the news Good morning, everybody. I'm gonna show you guys messages here Good to have you all here Happy morning Phil. Hope you're ready for a big week Obviously the markets have been really really difficult over the last few weeks. I'm not suggesting that it's been easy The stock market is not for the faint of heart and typically when the markets are down that's the best time to buy and When the markets are up, it's the best time to lock in profits So I think right now more than ever it's important to really know what you're investing in get to know every company Watch the markets watch the news watch the overall markets watch the trends of the stocks that you're investing in and Really make sure that you're investing in companies that you believe in long term Because when the markets start to sell off or trade sideways or start having volatility Those are really the best times to buy you want to buy when stocks are down and right now There's a lot of stocks, especially small caps that are down. So there's a lot of opportunities disguised in Really disguised in an aggressive selling so that aggressive selling is going to be an incredible buying opportunity for the right investor I'm not suggesting that you go and invest all your money in this stock But I'd love to at least have the conversation and at least make you aware of the news. What do you guys think? Sam says well, you always prepare us for this type of market never let your profit go away So kind of ready good. Yeah, I mean, this is what we talk about, right by the dips sell the rips We know that red is coming typically red fall is green and we've been at all-time highs So when you're at all-time highs in the markets, you have to assume that there's gonna be a pullback Same things happen in cryptocurrency Cryptocurrencies hit all-time highs Cryptocurrencies are having a pullback too. So nothing new with Investments coming back from all-time highs In fact, if investments just kept going up forever and never came down, then I'd be concerned or I'd be worried But when you see investments go up and then come down That's a buying opportunity so they can go up again Just remember how it feels when you're down right now so that when they do go up You can lock in your games because nothing goes up forever. Even Tesla has come back from their earlier Gains of last year where they were one of the hottest stocks in the world and so far this year if you had bought Tesla in January, you're down so if the biggest and the best companies are down in 2021 then you have to assume that smaller companies will also be down and In my opinion the reason why this is happening. Yes Skylight is uplifting to the Nasdaq absolutely So that will be a catalyst for skylight and there's other companies that we're looking at that are also uplifting to the Nasdaq like tat Like the Cindy Motors Corp like hut So there's a few other companies that we're watching mind medicine just recently went to the Nasdaq so there's quite a few companies that we're watching very carefully that will be uplifting there's catalyst coming and Small cap season is typically between September and January So between September and January we fully expect to have another massive small cap run But what's gonna happen between now and then so there's gonna be opportunities to present ourselves in the best companies I would say over the next four months This is the best time to position ourselves in some of the best companies dividend stocks small cap stocks You name it. There's going to be opportunities disguised in blood in this market And for those that can stomach it that have what it takes to be able to stomach the red this is the best time to buy and When they go up again and they explode Remember what it feels like when the market's down and make sure you lock in your gains Make sure you lock in your gains and you're building your vault building your treasury building your account That's the most important thing. Don't fall in love with stocks because when stocks go down They're not going to give you your money back Right, so there's no reason to fall in love with them. Okay, and when you fall in love with them and you hold through the Volatility sometimes you stop fall you stop loving them, right? And then what happens is people typically start to sell in the red. Well, that's not my strategy My strategy is I'm gonna be buying when things are down I'm gonna do the research do the due diligence look for growing companies Buy when the stocks are down and then when they're up and everybody's talking about it Like when you hop in an uber and your ubers talking about your pick and you hop in a cab and your calves talk about your pick And then you turn on the radio and they're talking about your pick. That's when you want to be locking in gains Right, you want to be locking in gains when everything's at the top, right? And focus on building your vault fall in love with building your vault Don't fall in love with specific companies. That's my best advice for you guys If you guys would like to learn how to trade you can join our club at richpigsdaily.com Left to have you we're trading stocks and crypto currencies 24 hours a day seven days a week It's been a wild ride lots of volatility in the markets We've had a huge start to the year Lots of gains were taken and now people are taking those gains in both the stock market and the crypto space So you need to be aware of the trend right now the trend has been sideways or down that's been the trend overall in the markets and That is the same trend in cryptos as well. So Left to know what you guys think about this news and this pick Farmer there huge huge huge news. What do you guys think? Hope you guys have a great trading day. The markets are now opening. I'll let you guys go What do you guys think about the big news from? pharma there, which we broke to you guys first once again pharma there announces FDA approval of ketamine ind in the treatment of Parkinson's disease symbol for pharma there phrm in Canada and phrf in America Thank you guys for watching if you're not winning. You're not watching. We bring you the winners and we bring them to first Have a great day everybody. It's your boy rich from rich to be live and I'm out peace