is the final of the Olyatian National Park. The Philomena of the Moroccan is the area that you are in. Alma Olyatia National Park. Sarah Olyatia. Hail to Pina.


Hello and welcome to this session in which we would look at the COSO Enterprise Risk Management ERM Integrated Framework and specifically we're going to be looking at information, communication and reporting. This is part five of five. Simply put I already covered the first four components of ERM and this will be the fifth component. Now before I start I would like to remind you that if you are studying for your CPA exam, I don't I don't suggest you memorize mnemonics about ERM. I strongly suggest you understand the components of ERM. First if you want to memorize the mnemonics as a second step that's fine but don't try to memorize the mnemonics, understand them then memorize them and this is what I can do on foreheadlectures.com. I explain the material for you and I explain each component separately. Once you understand the components then you can go to your CPA review course and use the durn mnemonics to help you understand the material. So simply put subscribe to my website I do have multiple choice and additional resources for you and it will help you add 10 to 15 points to your CPA exam score by helping you understand the material better. Now your risk with me is one month of subscription you try it if it doesn't work you cancel if you try it it works you keep it and the potential is passing the CPA exam are you willing to take that risk that's your risk and if not for anything take a look at my website to find out how well or not well your university is doing for the CPA exam. Also take a look at my additional courses that I offer for you in addition to the CPA exam if you need help with your accounting courses please connect with me on LinkedIn if you have done so and take a look at the LinkedIn recommendation people that use my system to pass the exam like this recording follow me on Instagram and Facebook so simply put we're going to be looking at the last component of the RM and this component has three principles so the assumption here is I'm not going to go over ERM definition again because the assumption here if you're watching this it means you're either familiar with the RM or you are looking specifically for information communication and reporting in this section this component has three different principles leveraging information system community communicate risk information and reporting on risk starting with leverage leveraging information system what do we mean leveraging it means using other things something else to to your advantage you would leverage information system to support the enterprise risk management how do you do so there are many ways you can do so I'm going to give you one example because information system it encompass many many things but I'm going to give you a specific example that you can relate to to get to the point for example we have data what is data it's raw fact collected for analysis data big data we are familiar with big data so what we do is we're going to capture collect and process the data into useful information and our information system will help us do that we can that data could be internal data external data we can buy this data we can download it from a third party it doesn't matter and what what happened is once we process this information and once we process the data and to better information it's going to help us make better decision better decision to do what to run our enterprise risk management system so data will help us but we have to leverage our information system to help convert the data into actual decision making what could be a good example for example airline companies they could collect data about their competitor pricing model from open sources for example if you're an airline company you want to go on different websites those travel website and see how many seats and what prices are your competitors offering this way you can determine your price then your price is competitive this is one way to do it same thing with hotels they can go on hotels.com they can go on trivelocity.com and find out what other hotels in your area are are are charging take this data analyze it then make a better decision so notice what's happening is you're using your information system your data processing to support your decision for pricing because part of your pricing is part of your business objective so it's so your business objective is to make a profit to have proper pricing so your business is competitive here you are leveraging your information system now we have two types of data and we'll be discussing more about data in a separate recording we have a structured data structured data as well organized and easy searchable and easy to analyze here we are looking at excel sheet public indexes database file so on and so forth basically structured data as rows and columns with specific you know numeric figure or data that can be easily you can run averages or regression whatever you want to do on structured data they don't have a predefined pattern like what you're looking at emails emails it's word it's word or you're analyzing word documents you're looking at photos websites which is information all over the place tax files and you will try to make sense out of it you mean both data are important you want to have a structured data and we'll talk about data later on because it's easier to analyze okay now communicate communicate risk information remember in the first four components we talked a lot about risk we set the risk we determine what our risk is we identify it we assess it we prioritize it but at the end of the day we have to communicate this risk to support erm so each person in the company they have to know what risk do they deal with now some some department some come some department some individuals might be responsible for different type of risk for example the person in the warehouse may not worry about the foreign currency risk of the company because that's not their concern maybe the risk in the warehouse is safety okay so yeah so you don't you're not gonna you're not gonna communicate the same information to them that you communicate to your account receivable or foreign currency transaction desk because they will be interested in foreign currency fluctuation but you have to communicate risk to through the organization you have to have an open communication channel and the communication has to be to internal parties and external parties sometime as needed for example you want you you may want to report certain risks to the to the to the FDA or to the IRS I'm not IRS the SEC or the FAA depending on what industry you work with okay or the Department of Labor you have to communicate those risks obviously the management and the board of directors they should be in continual communication about risk because they want to see what's going on with the risk appetite if we need to reduce it increase it how are we doing now how do we communicate risk there are many ways you can communicate risk basically meetings emails written documents public board town hall meeting one-on-one discussion whistleblower hotlines there are so many different ways that you could communicate risk to people within the organization people outside the organization but that communication has to happen in support of the ERM so everyone is responsible for certain business objective for certain strategy they need to be aware of the risk involved this way we are in control in addition to communication we have to report on risk how to report on risk well not only risk we report on the risk of the company the culture the performance of the company on the across different level now why we we need to do that why we need to report again to support personnel to support their decision making understand the relationship among risk culture and performance because people who are making decision they have to they have to they have to have that information why because they set the strategy as as i just mentioned earlier you have a strategy you have corporate governance you have day to day operation they're all interrelated so you have to communicate and report make sure everyone is on the same page depending on their risk risk responsibility okay so the information obviously has to be accurate complete clear and has to help you have a forward-looking decision so it should help you make a better decision how often should you communicate how often should you report on risk not communicate report on risk as well well it all depends on the severity of the risk and how what's the priority of the risk for example if you're dealing with crisis like if you if you if COVID-19 is is affecting your business you have to basically report on how what's COVID-19 doing to your risk on a daily basis until because it's severe and prioritized risk so depending on how severe and how prioritize sometimes you want to report on a weekly for example if you work at a place like Walmart they may report on safety within the store on a weekly basis what's happening on a weekly basis so depending on the business that you are in and including reporting on risk you want to know the difference between KRI and KPI KRI are key risk indicators they are predictable predictable in other words they're going to give you a future a future indicator other predictable future a futuristic point of view of unfavorable event that can adversely impact the organization that's what KRI are they monitor changes in the level of risk exposure contribute as an early warning system notice KRI it tells you something might something is changing be aware of it it might affect your risk so those early signals if you can detect them early and enable the organization to report risk prevent crisis and mitigate them in time okay they can be quantified in terms of percentage numbers or they can be in terms of high low medium okay an example of KRI is an upward trend in the default rate by large customers in a specific industry so you have many customers but you're noticing in one specific industry and their large customers let's assume you sell to building construction companies one of your one's one of your large customers not one of your customers one of your customers is but you also sell to other industries not only building industry you sell to retail you sell to health industry but the the construction the construction you're noticing and the default the default rate in the construction companies are going up so this is a key risk indicator it's telling you something happening in that specific industry make a note of it because you're looking at this information and you're comparing it to health the hospitals and the hospitals are doing well they're not defaulting but the but the construction business are doing are not doing well this is a KRI it's a futuristic indicator it's an early warning system versus key performance indicators those are designed as to offer a high level overview of the organization performance okay so they do not offer early warning signals so no the difference between performance and risk risk if they're warning you there's risk coming be careful keep key performance indicator just telling you what's going on basically after the fact okay they are important to analyze trend and monitor performance but usually after the fact so an event already occurred for example now you have five percent of your loan portfolio is in the fault well that's fine now i know this it's historical data at this point it will be part of my key performance but as that the fault rate is going up in a particular industry i'm going to capture this through what's called KRI key risk indicator okay that's the difference between the two make sure you know the difference and basically we cover the five components of ERM as i mentioned earlier don't try to memorize them i mean if you want to memorize them that's fine but understanding them is better than memorize them let them make sense complete as many multiple choices as you can i'll have multiple choice on my website that's gonna help you practice and you want to do that in addition to your CPA review course once again give me a chance i can help you i'm not gonna i can't help you by myself i can help you in conjunction with your CPA review course good luck study hard and stay safe


Previously, on the Högerkustenleden. We spend the night in the most beautiful little cabin in the middle of Skulleskoga National Park. As we are gaining elevation we can really see why this area is called a high coast. We finally see the famous crevice named Schlottsdahlkravan. Since we left early we are the only ones here. The rest of the day we enjoyed the beautiful weather and saw the first glimpse of Skulle Berget. In eight episodes we are taking you along this beautiful trail. We are hiking through deep forest and mountain top view points. Passing beautiful lakes that you only see in Sweden and sleeping in beautiful places along the way. Nowhere else in Sweden can you hike at this height so close to the sea. Welcome to the Högerkustenleden. Good morning! As you can see I'm hiking solo at the moment. Ever since we finished the TNB a couple of weeks ago Alete's knee is really aching and at first during this trail there were no problems with her knee. But yesterday with quite a demanding and rocky trail her knee started aching again which is not nice of course. And we thought she would recover this night but we didn't have a really good sleepless night to be honest. Because quite chilly and wet but unfortunately her knee is still aching at the morning so I'm doing this detour by myself. Like we mentioned yesterday it's the Skullenberg detour Skullenberget. I'm not sure how we pronounce it actually. But it's a 300 meter mountain and halfway up a trail is a cave. And that cave was used by robbers in the past. So let's see how it goes. The weather is really beautiful. It's now 8.30 and it should take me about two to three hours. Then going back to Alete. She is at the tent to recover and we'll see from there. Right behind me is the robbers cave and the other side behind me the view is incredible. I think it took me half an hour to get up here and it was a pretty fun trail to be honest. It was steep and rocky but very doable. There were some ladders and steel cables but not that big of a problem from here. I think it's 15 minutes to the top. I made it to the top and it was quite beautiful. Really beautiful. And I would recommend this detour if you're hiking the Haikos trail like we are. Normally the trail goes underneath the mountain. But there are a couple of trails that lead upwards the mountain. Like this is the cave trail and you have the south trail the east trail. So multiple options. Couple of tips if you're hiking the cave trail. Don't hike it down because some parts are very slippery and steep. And one tip. Maybe leave your heavy backpack down because all the trails come to the beginning again. So leave your backpack there and just bring one easy day pack with light stuff to carry you up. So this is Skullebergat nature reserve. This is the whole mountain. This is where we stayed last night and where we camped and where Alete is right now. I took this blue trail over here all the way to the other side of the mountain. Then I went up the steep climb towards the cave that's here. Further up the steep stairs then I made it to the top. And from here my plan is to hike this blue trail down. It's quite an easy trail. Then take a side trail here to the lake back to Alete. I am back at the campsite. I think this detour cost me two hours. And I think it's a really recommended detour if you're hiking the high coaster. It's really beautiful up there. Beautiful views. The trail is quite spectacular as well. Now let's see how Alete is doing over there. I was just packing all my stuff and trying to dry the tent but still wet. So hopefully the sun will does its work. Just a little behind the scenes of camping life. If you're camping and it's quite chilly in the night like we need to dry our tent. So we kept the outside of the tent over there to let it dry. The inner tent is drying here. The sleeping bags as well. They got a little bit damp on the top. But these sleeping bags, whoa, they are incredible. On the coonslater we had minus six and they kept us warm all night. So far we're really happy with the brand cumulus. Very happy and the jackets are incredible as well. Happy, happy, happy. Alete is cleaning the inside of the tent I think. I'm just packing the stuff. Alete is packing the stuff. Well I'm preparing some coffee now. So we just packed everything and dried all our stuff and we're ready to go. Yeah and today is quite a long day because it's 17 kilometers to Oolengar. That's the next town we want to go to and it's a lot of road walks. There are quite a few road walks actually. But still there are some nice view points along the way. So let's enjoy the day. After a day filled with road walking, road walking and road walking, we decided to check in to a hotel to treat ourselves and Alete's knee with a good night's rest. On the next episode of the Högerkustenleden. We have a long but easy day with not much elevation gain. This stage promises to be the unique selling point of the Högerkusten area. With typical Swedish houses, high coast and beautiful views.


chickens. So let's get underway. We were talking about Spinner Half, the most important type of spin, yesterday, and we got this far. So any state as regards its spin, its orientation should be expandable as a linear combination of the state plus which means you are certain to get a plus a half if you measure the spin along the Z axis 100 oes. The will be these coefficients here, and the complex number here. The amplitude to measure plus half on S-Sed, or the amplitude to measure minus half on S-Sed and we're calling these, it's obviously a handy notation to call that thing A and this thing B. And then what we want to be able to do is write the result of using some ysgolwydd o'r ysgolwydd wedi'i gael sydd. Roeddwn i weithio adeil y cyfnodol i'r newid gan maen nhw er mwynhau a mwy i'r gwerthio hynny bod ysgolwydd ystafell gyda'r sefydledig sydd o ganddi-ganddi-ganddi sydd. Fe'n gwneud amdano dwi yn gwneud hynny iddyn nhw'n gyflaen amser C a D o'r ddyn nhw'n meddwl i'r g beautol yw'r gweithlo. if on the right we put in the two numbers that characterize psi on the right, we get out on the left the two numbers that characterize phi after we've multiplied by this matrix of four complex numbers being the expectation value of the relevant whatever operator we're trying to use between the plus states, the minus states and then these non-classical off diagonal bits on each side. And we said, I think we finished by saying that if i is z, in other words if we're interested in the result of using sz on a psi, then this matrix is very simple because sz on plus is simply a half of plus.  So we have this diagonal matrix which is no accident, it is simply the matrix that contains the eigenvalues of sz down its diagonal because we use as basis vectors the eigencats of sz. We made that choice and the result is that the matrix representing sz is diagonal with its eigenvalues down the diagonal and this matrix is conventionally written as a half times this matrix which is called sigma z and it's called a Pauli matrix because Wolfgang Pauli introduced it into physics although it was known to mathematicians. The matrix is like this. Okay, so more interesting is if we ask ourselves what's the matrix for sx. So the matrix from sx is going to involve things, well we're going to have for example plus sx plus, this is a complex number, we want to know which complex number and the secret is to write s, of calculating this, is to write sx is a half of s plus plus s minus where s plus minus, so the matrices, sorry, are the operators that we already introduced in the context of j and l to reorient the angular momentum either towards the z axis or away from the z axis. So these are sx plus and minus i times sy. So this operator was introduced in the form of j plus minus but remember spin and total angular momentum have the same commutation relations, the same behavior in every way. So these ladder operators are this and obviously if you add s plus to s minus you get to sx because the sy terms cancel, so this is definitely the case. So this thing here can be written as a half of plus s plus plus, sorry, sorry, well this is what I'm trying to calculate, s plus s minus plus. S plus tries to raise this to an even larger value, this is plus a half, it will try and raise it to plus three halves and the message value is allowed because the total spin is only a half, so it kills it in the process, therefore this one is zero. S minus successfully lowers this to minus but minus is orthogonal to plus so this is zero, so this element here is zero and that's the top left corner of the matrix for sx is zero. Similarly, exactly the same reasoning would need you to conclude that the bottom right hand corner is zero and the non-zero elements occur off diagonal so if we look at plus sx minus we're looking at a half of plus s plus minus plus s minus minus. S plus raises minus to plus, successfully s plus on minus is exactly one times plus so this number here is equal to one and minus tries to lower this and kills it in the process and therefore this is equal to zero so this off diagonal element is in fact equal to a half. We know that the bottom right hand element is the complex conjugate of the top right hand element because s is a Hermitian operator so we know now that the matrix is sx is represented by the matrix half of nothing one one nothing also known as a half of sigma x, the Pauly matrix, this is the Pauly matrix sigma x and when we do the same thing to find out what sy is we write this as a half of plus sorry one over two i of s plus minus s minus because if you take the difference of sx plus i y and sx minus i y you will end up with two i sy so we have this and what do we get this s plus raises this to minus to plus so so plus s plus minus again equals one so therefore this is equal to one over two i also known as a half minus a half minus i over two so the matrix representing sy is going to be is going to be a half of one minus i i sorry one nothing nothing the diagonal elements will be nothing for the same reason that they were with x also known as a half of Pauly's matrix sigma y. So that's where the Pauly matrices come from. There's simply the matrix representations of the spin operators in a basis in the base when you choose as your basis the eigen vectors the eigen ket of sigma z. So let's use these use this apparatus to do something slightly interesting it's an excellent exercise both in practicing getting experimental predictions out of this abstract apparatus and also we learn something interesting about how how the orientation of atomic scale things behave somewhat counterintuitive arrangements. I don't think this computer is going this system projection system is going to work today for some reason so okay so the point is that so the point is that a spinning charged body is a magnetic is a magnetic dipole. I think that's kind of plausible so that so electrons neutrons protons except well sorry not neutrons electrons protons being spinning charged bodies have little magnetic moments they are little magnets. So if you put a magnet in a B field you have this is the energy of a magnetic dipole in a mag field. So there's a minus sign here which says that the energy is lowest when the magnetic when the dipole is aligned with the magnetic field. So when this dot product is positive the energy is lowest so that's why magnets compass needles and whatever align with the magnetic field. That also means that if a magnetic dipole is aligned with the field it the energy will drop as it moves into a region of bigger field because it'll this will become a more negative number. Whereas if it's anti aligned with a magnetic field then its energy will increase if it moves into the magnetic field because this will become a this will be negative and the two minuses will cancel. We have a more positive energy so since things tend to move in the direction that minimizes their potential energy we have that magnets aligned with B will be sucked into a region of stronger B. So a magnet dipole aligned B so that means that mu dot B greater than nought is sucked into a field. If the field strength varies spatially which it often does the what particles which have their fields dipoles aligned will be sucked into B and similarly the other ones will be repelled. So the anti aligned whoops aligned a poles will be repelled from a region of high B. So that was the physics that Stern and Gerlach exploited in 1922 in experiments which astounded the world. They found themselves they made themselves a magnet or should we call this north and we'll call this south. They made themselves a magnet which had pole pieces one of which was pointy and the other of which was flat or even well I think it was flat. But you could it could also be concave like this and then you can imagine how the field lines run the field lines run like this somehow. I'm not doing a very good job of it my diagrams are usually rather rubbish. The point is that here we have a crowding of field lines which means we have high B near knife edge. So I have a nice picture of this but the computer isn't willing to show it because this is the end view of a long of a long thing. So this is like the point of a knife right we're looking end on a point of a knife and this is just this is a table somehow. So if you if you have some particles with some spin coming in here and name it right so that they're heading for this. Well they're heading a bit below this region of high magnetic field like this. Then the ones that have their spin aligned this way into B are going to be sucked into the region drawn attracted by the region of high B near the point of the knife and move on up here. So this is the particles which have mu dot B greater than north and particles with anti aligned with mu dot B less than north will come down here. Of course these all grotesqually exaggerated in fact you'll have a very subtle curvature and then you'll have a straight line. So we get the particles deflected either way. So what they did was they took silver atoms because silver atoms turn out to be spin a half particles coming in here. Then what and they found which surprised them and everybody else that half of their particles half of their silver atoms went off this way and half of the silver atoms went off that way. So when they they detected the atoms on a screen over here they got two blobs distinctly separated. The quantum mechanical interpretation of this is that as these atoms when the atoms are in here they sorry I haven't said that mu the magnetic moment is equal to some number the gyromagnetic ratio times the spin operator. So when they're in here the magnetic field is as it were measuring their component of spin in the direction of the magnetic field. That's what you say to yourself. So there are only two answers possible either you'll get plus a half or you'll get minus a half for the value of this. And therefore mu will be either a half G in the direction of B or it'll be minus a half G in the direction of B. If it's so and the half for which it's plus a half G will be deflected that way and the other lot will be deflected down here and there you go. So at the end of the day you have a stern girlar filter you put in the particles with they've just come out of some oven. You've heated up some silver in an oven, made some silver vapour, allowed it to diffuse out of some holes, collimating slits and that kind of stuff.  So it's a machine for it's a practical device for creating silver atoms which are in this state. Now you can play some entertaining games by installing another stern girlar filter.  So let's measure the spin along some unit vector N and let's take, so we're going to have this to be the X direction. We're going to have this to be the Z direction and what the Y direction will have to be out of the board. And what we're going to do is we're going to take N is equal to nothing, sin theta, cos theta. So N is going to be a vector which if theta is nothing is just in the Z direction and if theta is pi by 2 it's in the Y direction and it can be allowed to scan between these directions as we vary theta. And what we want to do is calculate which fraction of the atoms will survive will get through the second filter. So this is the filter F1, this is the filter F2 and you want to calculate the probability that an atom gets through both filters. Or let's focus for the moment on the probability that an atom that has got through the first filter gets through the second filter. So the probability that you pass F2 given that you passed F1 in quantum mechanical language is plus a half on N, given that you're, well we'll just say plus on N, given that you were plus on Z. So this is the state that you're in, up there it's just called plus, but now I put in a Z to distinguish it from this which is in the direction of N, that this is an eigencat of Sz with eigenvalue a half, this is an eigencat of S sub N with eigenvalue a half. And this pair of things makes me the amplitude by the basic dogma of the subject for the probability of this outcome. So I need to mod square this and I've got the probability that I want. So we can work this out, we can get this complex number as soon as we know how to write plus on N as an amount of plus on Z, plus an amount of minus on Z, right? Because, so if we get this number and this number then we have the probability that we want is going to be mod a squared because a star is going to be exactly that number. So out of this catch you could get the bra you want up there by complex conjugating it, you'd have an a star, bang in with plus on Z and you'd pick out a star. So the probability we want is just mod a squared. So that's our exercise to find a and b and we'll be all done. How to find a and b? Well what's the point about, what's the point, what's the defining characteristic of that cat? It is that it is an eigencat of this operator with eigenvalue a half. This defines N. It's totally characteristic of these sorts of calculations, a wide range of quantum mechanical calculations that this sequence of arguments. I want a certain complex number, it will involve some cat.  Now we have a well defined mathematical problem. Find it because what is Sn? Sn is equal to a half of nx sigma x plus ny sigma y plus nz sigma z. Sort of a dot product between the unit vector n and the vector made up of the three palli matrices. Well nx is zero so basically we've got an ny, we agreed was going to be sin theta and this we agreed was going to be cos theta. So at the end of the day it is a half of, now sigma z we've got up there it's got one in the top left hand corner and minus one in the bottom.  And this has got a minus i in the top right hand corner so we get a minus i sin theta appearing there and its complex conjugate has to appear down here. So this is the matrix that represents Sn where theta is defining the direction of n. Now all we have to do is say that this matrix cos theta minus i sin theta i sin theta cos theta on AB is equal to AB. This vector has to be an eigen ket of this matrix with eigen value one in order that it's an eigen ket of Sn with eigen value a half. Because the original expression was Sn on this equals a half of that but here is a half I can cancel on the two sides. So I'm looking for the eigen ket of this operator with eigen value one.  I know that because this is a matrix that represents a spin operator Sn I know before I start that the eigen values are plus and minus, well this one plus and minus a half of this one plus and minus one.  There are two equations here but because we're looking at an eigen value problem only one of them. These two equations are linearly dependent upon one another only one of them contains useful information. The other one repeats that information. So we merely need to look at the top equation and it says that a minus one sorry sorry sorry a times brackets one minus cos theta. So if I'm going to get a cos theta equals a on the right hand side so if I go on the right hand side we'll have a cos theta a into one minus cos theta is equal to minus i b sin theta. In other words we're going to have that b over a which is all that I can, it's only the ratio of a to b that I can determine out of this. The absolute values have to be determined from a normalisation condition are equal to b over a is equal to one minus cos theta over minus i sin theta. And we can clean this up a bit if we use some half angle formulae because this on the top is twice the sin squared of theta over two sin theta is twice sin theta upon two cos theta upon two. So we can cancel a number of things, the two's cancel, one of the sin theta's cancel and we end up with sin theta over two over minus i cos theta over two. So I can write now that a b is equal to cos theta over two i sin theta over two. So if you work out the ratio b over a of these two I think you will get that because this minus i can be put as an i on the top. Moreover this thing is correctly normalised, it just happens. So in principle I would now need to deal with the normalisation, I've only been calculating the ratio of the components. I want mod a squared plus mod b squared to come to one but it jolly well does by good fortune. This is the complete bottom line, this gives you the probability that we pass f2 given that we passed f1 is actually equal to, we said it was going to be mod a squared is therefore cos squared theta upon two. Does that make sense? If theta is equal to nothing then the second filter is also measuring the z component of angular momentum and the output from the first filter is guaranteed to return plus a half for the z component of angular momentum so this probability must be one and indeed cos squared of nothing is one. If the theta is pi then the second one is plus a half, then n is pointing in the minus z direction so getting plus a half in the direction n is equivalent to getting minus a half in the direction z but we know for certain that we're going to get plus a half in the direction z so the probability of this happening is zero and indeed cos squared of, if I put theta equal to pi I'm looking at cos squared pi upon two which is nothing so that makes sense. If I put theta equal to pi upon two then we're measuring then the n direction becomes the y direction and we're measuring in a direction which is orthogonal to the z direction and then you would think that knowing what components of the angular momentum in the z direction was couldn't possibly affect the angular momentum in the y direction so you would expect that there was equal probability at passing the second filter that is to say of getting plus a half for the spin along y that plus a half on y and minus a half on y be equally likely by the symmetry of the situation and indeed cos squared of pi upon four or cos of pi upon four is one upon root two to cos squared of pi upon four is a half and that makes perfect sense as well so this formula predicts the kind of thing that you would expect. Okay, suppose we now have, we won't do this in all detail but let's just sketch it out suppose we have now another filter so we have f1 as before we have f2 as we've just calculated now suppose on the output of f2 we include f3 right, so this one is going to measure in the theta direction as said this one let's say this one has its axis in the phi direction also in the xy plane right so you measure first of all the spin on z then you measure on the unit vector cos theta nothing sin theta cos theta sorry then you measure and then those that return plus a half in that direction you measure in the direction nothing sin theta sin phi cos phi suppose we do that so the probability of passing f3 given that you passed f2 is going to be we'll call this vector n and we'll call this vector m say we'll use this notation this will be a half on phi a half on theta so the output from this filter definitely has particles with plus a half component of angular momentum in the direction defined by theta and I want to know the amplitude that those particles have will definitely give me a plus a half if I measure in the direction defined by phi the answer to that is according to the dogma of the theory it's that and I can expand that into here I can slide the identity operator taking the form of plus on z plus on z plus minus on z minus on z we've slid identity operators in many times before in more complicated contexts so this thing that we're doing here is going to be a half phi sorry that's a blunt end a half phi plus z plus z a half theta plus a half phi minus z minus z a half theta now these complex numbers we already know we just calculated them right this was a which we used this was b which we didn't use but we got it written down up there it's i sin theta upon 2 so this one here is cos theta upon 2 this one here is i sin theta over 2 but we also know what this is because this is going to be the same excuse me we have a complex let's just ask ourselves carefully exactly what is b b is actually the complex conjugate of this sorry these need complex conjugate signs can we remind ourselves actually where we are on this I'm now worried about whether I'm dealing with a complex some of these need complex conjugate signs what exactly are a and b they were defined just to get this right what we said was that a half on theta was equal to a plus z plus b minus z that's what we said that was the definition of a and b so what is this this thing here is plus on z a half on theta yeah so so what I said originally was correct there are no stars here so that's just for note right now back to this this is the complex conjugate of this is essentially the same as that with theta replaced by phi so we know that this will be the complex conjugate of this with theta replaced by phi this is in fact real so this is going to be cos phi over 2 similarly this the complex conjugate of this is the same as that with theta replaced by phi so I now have to write down the complex conjugate of that which is minus i sine phi over 2 so that's what that comes to so the probability that we get through f3 given that we got through f2 is going to be cos squared phi over 2 plus because that minus sign and that i and the pair of i's make a plus sign sine squared theta of phi which is also known as cos phi over 2 minus theta over 2 I think so does this make sense it tells me that I will if phi over 2 if phi is the same as theta I'm certain to get through that's good if if the difference in the angles is pi upon 2 then I have a chance sorry we have failed to mod2 the whole thing maybe there's muttering about that so this got expanded to this and this whole thing needed a mod2 and this needed a mod2 and we were doing various calculations and then this needed a mod2 and this needed a mod2 so it just became cos2 so when the angle is so all this tells us is that it had to tell us we would have been worried if we hadn't discovered this that the probability of getting through the third filter given that we got through the second filter should depend only on the difference in the two angles and indeed should go like the difference divided by 2 yep gosh yeah sorry you're completely right right so let's go back to this line here this was cos pi over 2 cos theta over 2 plus sin pi over 2 sin theta over 2 that's what it is and then we have to do a mod2 of it excuse me we have a formulae intrig which says that this combination of cosines is the cosine what's in here is actually the cos of pi upon 2 minus theta upon 2 and then we had to square it sorry now we can learn something we can make a little get a little physical result here by considering the case that theta is equal to pi on 2 pi is equal to pi what does that mean is that N is equal to E sub Y the axis of the second filter is equal to E sub Y you're measuring the spin in the Y direction the axis of this one we'll call it M is then equal to minus EZ so what's the probability of passing F3 given that you passed F1 and that's the same as the probability what that is physically is the probability of eventually having your spin being measured to be in the minus Z direction given that as you emerge from F1 you had your spin in the plus Z direction so we already had this ok right what is that well it's the probability of passing the second filter given that you passed the first times the probability of passing the third filter given that you passed the second therefore it's equal this probability was a half in this we already discussed that in the case that that theta was pi upon 2 so we were measuring in a perpendicular direction to the direction associated with the first filter this probability came out to be a half we felt that was natural because we've seen that it depends on the difference of the two angles and the difference in the two angles here is pi upon 2 so it's times a half so it's a quarter so a quarter of the particles which emerge with their spin quote unquote in the Z direction are found eventually to have their spin in the minus Z direction and this is concrete evidence that the second filter hasn't just measured the spin of the particle it's redirected it so this is a manifestation this result is a manifest so the probability of just doing F3 given F1 and no second filter is zero so putting in the second filter the intermediate filter affects the result and that's the realignment so we should talk briefly spin a half is far and away the most important case but let's just briefly talk about spin 1 and make the point that everything that we've been doing here generalises to arbitrary spin there's nothing we've been doing here which is really peculiar to spin a half so in the case of spin 1 we have that psi can be written as an amount of 1 so 1 1 if you like plus an amount of 1 nothing plus an amount of 1 minus 1 so there are three complex numbers needed to define the orientation of a spin 1 particle and for example a W boson or a Z boson are particles with spin 1 photons also have spin 1 but they have certain pathologies because they are a rest mass so it's as well not to include them in this discussion so we have that and the consequence of that is that if I have a spin operator si working on a psi that maps to a matrix problem where we write this as a b c d times 1 1 plus e times 1 nothing plus f times 1 minus 1 so this is represented by three complex numbers d, e and f this is represented by a, b and c and there will be a matrix relation between these we will have that d, e and f are equal to a matrix which we will make with plus sorry we will have 1 1 the total total angular momentum quantum numbers so let's just call it 1 si 1 and then we'll have 1 si nothing and then we'll have 1 si minus 1 and so on and so forth and here we will have nothing si 1 nothing si nothing so we have a 3 by 3 matrix operating on a b c this is how we will concretely do our computations and we need to know so we'll have 3 matrices 1 for s x, 1 for s y and 1 for s z s z will be the easy one to do s z will be the matrix of its eigenvalues down the diagonal so it will be 1 nothing minus 1 and nothing everywhere else which follows immediately from the fact that s z on this produces 1 times this etc etc etc and when we want to work out what we want to do for s x so when we want to work out 1 s x 1 we'll replace that s x by a half s plus plus s minus s plus will kill this s minus will lower this to nothing which is orthogonal to this so we'll have a 0 in this slot when we put s x in here we have a half of a plus plus minus minus will lower this to minus 1 which is orthogonal but plus will raise it to this and it will produce in fact root 2 we'll have that s plus operating on nothing will turn out to be root 2 times 1 so s x will be a half of nothing root 2 nothing we'll get nothing in the right thing because s plus can raise minus 1 to nothing but it can't drag it all the way up to 1 and s minus of course kills minus 1 so we get a matrix that looks like this and we will get for s y a matrix that's most handily written as 1 over root 2 this is more easily written as 1 over root 2 of nothing 1 nothing 1 nothing 1 nothing 1 nothing just taking out the factor of root 2 and this one is most easily written I mean is handily written just the same way we derive it nothing minus i nothing minus i it's a emission matrix so here goes i here goes i nothing nothing so these are sort of these are the generalisations of the these for a spin 1 problem and it's worth doing some Stern-Gerlach type experiments thought experiments with the spin 1 systems to just see what the differences are I did want to talk about the okay let's just briefly talk about this let's go all the way to spin s which is much greater than 1 right so in the classical regime we want to understand how out of this can we recover the classical situation that if I hold up a piece of chalk it has a well defined orientation none of this probabilistic this thing and that thing and the other thing you can see where the damn thing points we have to recover this out of this probabilistic apparatus and the way to do that is to imagine what these spin matrices look like for spin n to construct them everything we've done carries over absolutely straightforwardly we have that s n well for s z in this case is going to be s s minus 1 s minus 2 down to minus s along the diagonal it's going to be the matrix of the eigen values of s z and diagonal s x is going to be here we will have the state s s x s then here we will have s s x s minus 1 and so on s x s minus 2 and if you want to apply this in classical physics it will be 30 something by 10 to the 30 something it will be enormous but nearly all the numbers will vanish because well this number we already know is equal to 0 this number vanishes because this you replace by a half of s plus plus s minus s plus kills this s minus lowers it's something orthogonal to this this will be non-zero because s plus will raise that to s which will couple to that and in fact this will turn out to be alpha of s minus 1 so when s x works on this we get a horrible square root which I'm calling alpha of s minus 1 times s so that's what this will come to this will come to nothing because we'll have s plus that will raise this to s minus 1 which is not good enough and s minus will lower it which is useless so this is equal to 0 and everything else is going to be equal to 0 so this matrix is going to consist of non-zero numbers just above the diagonal nothing's down the diagonal so let me write this out this is going to be on the diagonal precisely nothing above the diagonal we will have alpha of s minus 1 which is easily worked out it's the square root here we will have alpha of s minus 2 here we will have alpha of s minus 3 s minus 3 and so on down the diagonal and just below the diagonal we have the complex conjugates of those these are in fact real numbers and therefore we have the same numbers and nothing's everywhere else so this is a very simple matrix it just has two non-zero diagonals and we can work with it and we can now do things like suppose we have no time so it's time to stop sorry but I think it probably is worth I'll finish it off tomorrow


Hello, this is Laptop Media, and today, we will show you how to open the Lenovo ThinkPad T15 and what's inside of it. Getting inside this laptop is easy. You need to unscrew 8 Philips head screws and pry the bottom panel away. Just remember to unplug the SIM card tray before that, or you're risking to damage it. The cooling here is pretty straightforward, a single heat pipe, a heat spreader, and a fan. As you can see, there is only one RAM Sodom slot. This is because it has 8 GB or 16 GB soldered to the motherboard. They will work in dual-channel with the appropriate amount of additional memory, while the maximum is 48 GB. In terms of storage, there is a single M.2 PCI-EX4 slot. Similarly to last year, the battery has a 57 Watt hours capacity. If you'd like to see more disassembly videos of the latest notebooks we would highly appreciate if you hit the like button and subscribe to the channel.


Jimmy Stafford and Paul McDevitt all the way in Lifford there. How are you getting on? Hello, Mikaela. How are you doing? How are you, Mikaela? All good. Have you been busy? We have been flat out. We have this morning, we have been up at Alcorn's Tropical World. And it was absolutely amazing. It was my first time and not the end of things. But what we learned and what we've seen was just something. An education, Mikaela. So it's part of the Fall Charlotte dedication across Dulley Gull.   And it's amazing tropical words like you don't think that this is on our doorstep, but it is.  Me and Paul got an education on butterflies today. So much so that when we came to the courthouse here. When you see this is the thing about it, right? And you're dropping out there a bit. The butterflies must be affecting. Can you hear me? Not only that, but they've all these different types of butterflies, the lifespan of a butterfly. I didn't realize it in weeks, three weeks, three weeks. You know, what we learned and then they had all these educational things inside and all of it, you know, fantastic. Are we there? Yeah, you're there. I'll get you very, very shortly. Now we're here now. Are we back now? You're there. Yeah. You're there about. I am sorry. But probably we're down in the jail here in court in the courthouse. That's probably what the problem is with the we talk about that in a minute. But just just Clive and the team out in Alcorns, just an amazing just the passion that Clive has Clive Alcorn himself for the actual facility, the animals he's brought in species. I've never heard of a scene before. So from a family perspective. Well, his second is on from childhood. It was actually a childhood obsession. And it's grown under what it is now. And you have to respect and appreciate everything you have because the crowds were there today. He's open seven days a week. Sunday is one to five. I think it is and it slows up in the last day in September. And he's hoping this year to do a Halloween kind of theme thing around on too scary. He said, but I would recommend anybody to families. Even individually just go along. It's you'll be blown away. But that's an amazing. So he's took the short trip then to Lifford. Have he's been behaving yourselves in the courthouse? Or do you need to be dealt with there? Well, Jimmy being a home from home, you know, he was that sort of was trying to say we were one of the cells and we were being shown around by a guard. And I have to say thanks. It was Luke Maxwell, who a lot of us will remember the legendary Brandon Maxwell, the grandson of the the guide around here. And I swear to God, they must be seven foot. Oh, they said to me, but the courthouse itself, Mikaela, when we were down in one of the cells, Jimmy thought of water. They had landed in the ground. He's obsessed with the butterflies now. I am convinced that it must have flew in these golden alcoons and it fell out and he stood in it and killed it. Jankers. But then that's another one. Now, the courthouse is the historian. It's just and it's on your doorstep once again for your your daycation. But Jimmy, you can talk. I think, Mikaela, when you look at Donegal and you ask people, where can you go and what can you do? We can all run off different things right across the county. But for me, you know, if again, whether it's a family or whether it's a group, like you could pick the two today, alcoons and the courthouse. And you could do actually both. You have a fantastic day in alcoons. There's a playground. There's a garden, beautiful tea rooms out there as well. Absolutely amazing.  You go into the cells and I think not alone, the pleasure of being indoors and places, but also the education side. This is incredible, Mikaela. Yeah, I remember so much today. I remember going to the courthouse in Lifford when I was a primary school and the education. It's such a history of the local area, but it did put manners in here. It was a bit scary when I was younger now, you must say. It was because there are different cells and things down here. And the thing about it is they also have a breakout game, which we attended back in the early summer from work, where you're lucky and you have a certain amount of time to get out of the cells. That's the fastest crack. Honestly, God in heaven, it's really, really brilliant. It gets your mind, it's not a straightforward thing. Plus also they have a great function room and it's in the actual court room itself. They have a great facility for music venues, which we have attended here. That's just a brilliant this. There's a full menu there. There's a library where we're sitting in here. There's meeting rooms, it's just... And then even in Alcorn's, you know, for Paul, he was delighted. There's a beautiful playground. So I'm in just the obstacle course there as well, Mikaela, that we undertook today. So, you know... Well, are we going to help and save the issue because there's a wee five-year-old trying to walk the beam and Jimmy pushed him off. And that's been dealt with, you know, in my average region. It wouldn't be straightforward with the use to it all. It wouldn't be straightforward with the use to it all. No, it would not. But not all at all. It was a good crack.  It's really brilliant. Mikaela, the best part was we held I can't remember the name, whatever it was. It was like a snake, come turtle, come beautiful animal. All right, well, go on a kind of thing or a... Yeah, it was a really kind of a thing. But we have it on video tomorrow. Anya, Anya's been a super help today for us. She's working hard all day. So she's going to put amazing editing skills in the video and there's going to be some crack in it. She'll learn her money doing that. But I have to give credit to Clive, Alcorn and all the staff. They're a really good twist today. He said to us, Clive, why don't you go and see this mad parrot? Parrot's a big beast of a thing, right?  And I thought he'd not get a chance at me, but there's more and more going on here. So he took us under the cage. We opened the cage and we went, and Anya was following us and the thing comes out. You know, we saw him very well looking at parrots on TV, you know. But the next thing he came out on, he crawled on to Jimmy's arm. But I took this notion, he's there at me. And I thought, that's why he's going to go for my head here. So the next thing he crawled on my arm, but there was a lovely count on this, I thought. I just felt so... And Miguel even bettered us another parrot, right? Which is, this guy speaks. Right. And we leave the video due to talking, right? But it is incredible. This guy says, what's the crack? You want to hear him? Oh, and he can see it on the video, of course. And I played, what's the name of the song here? You know that one, Sugar Daddy, Baby Shark. Right. And he loves Baby Shark. And you want to see him dancing to Baby Shark. So go, if you want to see, I swear, it's worth the entry for you just to see this guy. So when we were moving out, I was kind of whispering a couple of wee words on the parrots here, but he didn't pick up my language. Well, I'd say, thank God the parrot didn't pick up on every year we were whispering. No, I'll be right up, it's quite a crack. Honestly, God, I'd say, you know, it does put on the perspective, watch on our doors down here. Decation, there's lots more. You've seen it throughout the week and encourage people. Now, we had about eight takes on the start to about the dedication. So Paul kept saying, stay occasion, but we're calling the occasion. I couldn't remember the image. And they're only half an hour apart, so you can't make a whole day and, you know, you're home then again in the evening. It's great. Absolutely. I'm getting the feed here now and everything, which is even better. So Casual's waiting for us outside. Right. Well, I will not keep you any longer then because I don't want the casserole getting cold. But thanks so much. Enjoy the rest of your day. Thanks. Have a good tour. Bye, bye, bye. Get great menswear at greatly reduced prices in the big summer sale now on at Watson menswear letter candy. Brands like Superdry, Penguin, Sixth Sense, Andre.


Thomas and I are here on top of the ITU tower in Geneva, Switzerland, where we have just installed a bird box.


The reason why you want to lift weights or do strength training is because that is the most effective, loudest muscle building type signal that you can send your body. If you do not lift weights and you attempt to build muscle and burn body fat, it's not going to happen.  The type of lifting you do I think is really important too because a lot of times, especially people that are wanting to reduce body fat, they get caught up in the calorie burn type of training and they focus more on this like circuit based, high heart rate, constantly moving, constantly sweating. And for what we're trying to accomplish here, I would say that's some of the worst ways you could potentially train, right? Yeah, no, you got to focus on the loudest possible signal for muscle building exclusively. And there's a couple of those compound lifts that really provide that kind of stimulus where your whole body is just geared in that direction towards muscle.


Empowering students to analyze primary sources can change a history classroom. Parmarily teaching focuses on improving history instruction using the National Archives collections. But why stop there? Expand this learning and earn graduate credit and history at George Mason University. This three credit course begins with the National Archives Summer Institute and continues into the fall semester. But how does this course benefit you and your students? You will learn to integrate new teaching strategies and content, reflect on your teaching, and receive feedback from historians and education specialists. After submitting your project plan in August, you will receive instructor feedback. Then submit a revised plan in September and teach your project by mid-November. And in early December, submit your final plan as well as a reflective essay and student work samples. Visit the website for course requirements and information on dates, cost, and registration. Download and complete the enrollment forms and send materials before your institute ends. Questions? Contact education at chnm.gmu.edu.


Appalachian Wireless now has new forward pay pricing where you can pay up front and get the data and features you desire. Five gigabytes of data just $39.99, unlimited just $79.99, better service, bigger savings. That's today's Appalachian Wireless. Before classes got started this morning at Elkhorn City Elementary School, commotion in the hallway outside the main office quickly got everyone's attention. We had a female adult come in the building. She actually wanted to speak to her daughter that's a teacher here and from that point it got into a confrontation between her and an instructional aide at her school. Principal James Mercer tells EKB News that witnesses say the woman was yelling at the employee over something that obviously occurred off school property. The accusation had nothing to do with the school, had nothing to do with our students. It was something outside the school. She puts her hands on our employee close by. We had one of our custodians and she immediately steps in immediately and stopped it. And then at that point an individual starts making some threats that gave us reason to go into lockdown just to secure the safety of her kids. He says thanks to recent trainings on school safety issues, his staff responded instantly. It was over just in a few minutes. The lady was told to leave the building, 911 was called, the law enforcement was here, it was handled correctly, professionally and everything was under control just didn't last long at all. The Elkhorn City Police Department is conducting the investigation and at this point no arrests have been made. As far as the Pike County Board of Education is concerned Superintendent Reed Adkins says they are also looking at steps that they can take to ban the woman from returning to the school property. Principal Mercer says student safety is the main priority. Something will come out as to where the message will be clear that you can't come into not only Elkhorn school but any school to settle a dispute. In Elkhorn City, I'm Shannon Deskins, EKB News. Thank you. Thank you. Thank you. Thank you.


Guys, subscribe and turn notifications on, leave a like and drop a comment down below. Get here first and win giveaway calls, I will pin as first comment on some of my videos. Be fast and good luck. What is going on guys, welcome back to the channel and I appreciate you being here today. I bring you another Destiny 2 video and today I bring you exclusive details on the exclusive recent release details and the festival of the last, the looty offers, the things we'll be able to do and much much more. But before we get into the video, guide if you enjoy it leave a like, it really helps out and if you are new around here and enjoy daily Destiny 2 videos be sure to subscribe. Okay so Bungie, not long just drop some information on the festival of the last. We're going to go through it all right here, right now, quote him Bungie. The festival of the last begins for all players of Destiny 2 on Tuesday, October 16th which is next Tuesday people, weekly reset, lights in the dark. No one has heard from evil Avante since the city fell. Shipwright Amanda Holliday has stepped up to raise everyone's spirits. Thanks to her the tower is filled as memories good and bittersweet fill our hearts. New triumphs will be available for you to earn and Holliday will offer daily bounties that reward fragmented souls. These items can be used to purchase festival of the last masks as well as the horror story legendary auto rifle which looks pretty damn cool. But even with the tower illuminated by spooky violet candles there's always something scary lurking just out of sight, fear and fright. This year festival of the last brings more than just masks. For a limited time all players of Destiny 2 are invited to the haunted forest. Guardians have been tasked with clearing out its ghouls and demons which are spooking up a storm. You'll have 15 minutes to dive as deep as you can into the haunted forest and clear out the nightmares lying in wait. Be wary the deeper you go the more difficult your job will become. Sounds pretty cool. You jump into the dark as a solo player with a pre-made fire team or through matchmaking to join other guardians in the fight. On the case most players are forsaken and have already won justice for K6 but near the conclusion of the festival of the last there will be called once again to avenge a fallen friend. Master Ives has been struck down. Master Ives I believe was the cryptarch from the wreath from destiny one of you guys remember him. Maybe someone wanted to settle an old score or lost their temper when receiving an edge transit. That's probably the case. Whatever the wrong doing justice must be served. The pursuit of Master Ives killers will take place through a quest line which adds an additional powerful reward for you to earn each week. The hunt begins on Tuesday October 30th. Pretty damn cool. Treats for all. Alongside the festival of the last rewards from Amanda Holiday and the festival of the last triumphs players will earn an ephemeral ingram every time they fill their XP bar after receiving the max character level. Players will receive this ingram in addition to the steadfast ingram which effectively awards players double writing grams for the duration of the festival of the last. Players may also purchase ephemeral ingrams from Tess Everest in the tower if they so choose and we see an image on screen now of some of the loot obtained from this new festival of the last ingram and they look absolutely amazing. Look at that gold shell kitty cat with the ears and the whiskers. Absolutely epic. Can't wait to get that. Tess will also feature rewards from the ephemeral ingram on the bright dust star throughout the event for those wishing to purchase specific items directly and we see two emotes on screen now. The one with the guitar looks pretty bad that's not gonna lie. The festival of the last begins on Tuesday October 16th and concludes 10 am PST on Tuesday November 6th. So we've got quite a while to farm this event. Gonna be pretty damn cool to be honest. Not gonna lie I expected a little bit more but we don't know exactly what we're gonna be getting so we will have to wait and see but some of the loot looks absolutely epic and I can't wait to see more but guys on that note we have come to the end of the video if you want to check out the full blog posted by Burns you'll find it linked within the video description but guys thanks as always for stopping by if you are new around here and enjoy daily destiny videos be sure to subscribe and hopefully people I will see you on that next one.


Hello. Hello. In the following, we will look at the morphological processes that define different types of words. In fact, there are two such processes, namely inflection and word formation. Other, more exceptional processes are not considered in this e-lecture. Let us look at the main formal differences between inflection and word formation first. Yes. Let's look at inflection. This process involves one base form, also referred to as free morph, and at least one morphological operation. Here are three examples. Walk, walked, that's concatenation. Mouth, mice, that's volcanic change. And go, went, that's apletion. Interestingly, sometimes several operations may occur simultaneously. In German Haushäuser or in present-day English, say, said, we find two operations, concatenation and volcanic change. And word formation processes? Well, word formation processes can be subdivided into two main types. Into derivation, where we have one base form to which one or several operations are applied. And compounding, where we combine several base forms. Thus, derivation is formally just like inflection. Compounding by contrast is different. In order to keep inflection and derivation apart, a set of criteria have been put forward. Let's look at them in detail. Okay. The first and maybe most important criterion is referred to as productivity. It defines the morphological process as fully productive if it applies to all members of a given class. Take the formation of the past tense, a typical inflectional process. All verbs have a past tense form, irrespective of the type of morphological operation involved. That is prefixing, suffixing, vowel change, and so on. So inflection is fully productive. Derivation, by contrast, is less productive. Take the formation of nouns from verbs, act, actor, swim, swimmer, but rain, rainer, or seam, seamer. So derivational processes do not apply to all members of a particular class. Well then, inflection does not change the word class of the stem, but derivation may do so. Take apply, applies, applying, and applied, they're all verbs. In derivational processes, by contrast, the word class may change as in act, actor, or able, enable. But it may also remain the same as in boy, boyhood, both are nouns, or happy, unhappy, where both are adjectives. To make it absolutely clear, inflection never changes the word class, but derivation may do so. But there are further criteria to keep inflection and derivation apart in present day English. Yes, for example, inflection doesn't involve a change of the stress pattern of the stem, and again, derivation may do so. Take the verb standardize. If we inflect it, it keeps its stress on the first syllable. In forms such as standardized, standardizing, whereas the addition of derivational suffix, asian, causes a stress shift to the third syllable, standardization. In some cases, stress shift is even accompanied by phonemic changes. For instance, if we add a ball as in move, moveable, to the verb apply, we get applicable. Yes, well, and furthermore, inflection is semantically transparent across the board. Derivation is not. If you add ed to a verb, the result is either past or past participle. Derivatives that are generated, for example, by the addition of ion, however, denote different things. In many cases, ion means the act of, but not in examples such as commission or television. But note, all these criteria are primarily based on present day English. In some languages, the criterion stability of stress pattern does not work. Here is an example from Welch, a Celtic language. Aval. Avalai. Or take Russian where the nominative and the genitive of a noun, that is, case inflection, may involve different stress patterns. Okay, let's summarize. Right. We said that morphological processes define different ways of building words. Formally, a distinction can only be drawn between compounding and the other processes. For this reason, we need additional criteria such as productivity, the stability of the word class, the stability of the stress pattern and semantic transparency to keep inflection and derivation and, more generally, inflection and word formation apart. Thanks for your attention.


So how many people are familiar with Prometheus at all? All right, good. Well, this will be a good overview, which I think is the objective. And Prometheus, I'll give you an overview of the different components that make up Prometheus. And then I'll give you a quick example of how to deploy it and how to pull data out of it. It's a pretty interesting tool. I used to work at a company called Orbitz in the US. Their online travel site, I think Rates to Go was like an Asian version of what they used to do. At least back in the day, they did. I don't know if they're still around. But we created something called Graphite. You might have heard of Graphite, but it was an open source project that came out of Orbitz. And I was on the team. Actually, one of my teammates is the one who actually wrote Graphite. And then my responsibility was getting the metrics out of Graphite and creating graphs and meaningful information. We also created a whole event processing stream around that as well. So whenever I dive back into the world of metrics and see how we've kind of progressed, it's always really interesting to me knowing that I have this knowledge or background from 11, 12 years ago of what we were trying to do of monitoring our systems. So a little bit about me. I'm all things open source and sysdig. We have a couple open source projects. We also interact with a lot of open source projects. And Prometheus is one of them. And we like Prometheus because it gives us a standard way to pull metrics out of applications. It also gives us a standard way to pull metrics and push it into our cloud-based SAS monitoring tool from all of the components in your Kubernetes cluster as well because the Kubernetes world, the cloud-native world is starting to kind of standardize on Prometheus metrics. I used to work at Chef. And so I have a background in open source for a while now. I worked at Chef for about five years and did a number of roles for them. And like Anton, I'm a DevOps-based organizer as well. I organized DevOps Day in Ohio. And then I also found DevOps Day in Minneapolis and a few others as well. And if you want to reach out to me, that's my GitHub and Twitter handle, as well as the Twitter handle will be down in the corner. So this is not picking on open shift. This is just kind of like the most complete diagram that I had. But this is your typical Kubernetes cluster and what it looks like. So you have lots of different components. You're going to have storage. You're going to have the master node where Kubernetes runs. And then you have where your applications actually run on the infrastructure nodes. And then you have a whole service layer and hardware and pod provider and a whole bunch of other things that you still have to monitor and get whole information from. So the other thing is these infrastructure nodes are going to scale out, scale up and down, depending upon what your workloads are and how many application nodes you need. And then, of course, on every single one of those nodes, you're going to have tens of containers running on them that are actually running your application. So it gets very complicated to figure out, how do I start pulling metrics back from all of these things? The other thing that makes it complicated is that these environments are dynamic. So machines are coming up and down. Or containers are spinning up and down. And so how can you pull back the metrics and information from things that are very rapidly churning and going out from underneath you? So the question is, how do you monitor your core infrastructure services? How do you alert when there's an issue? How do you monitor the application themselves and not just look at infrastructure metrics? While infrastructure metrics are important, the real golden signals that you want to look at in your environment tend to come from your application. And then how can you give developers access to monitor their application? Not only how can you give them a way to instrument their code, but how can you give them a way to actually look and see into those particular metrics? So let's talk about what is Prometheus. So it's multiple meanings for a word. It can be a monitoring stack. It can be a way to instrument your code. It can be a metrics interface that Prometheus has defined. It can be a query language, which is actually called promql, or it could be the actual metric server itself. There's actually several components of the Prometheus stack. And this is what it looks like. So you have where we get our metrics from. So we have pull metrics. The metrics are typically in the default scenario in the Prometheus world. Metrics are pull-based, meaning that Prometheus server goes out and scrapes metrics off of an HTTP endpoint. You can have short-lived jobs that will push metrics. And you can push metrics to a push gateway. And then the Prometheus server pulls the metrics again from the push gateway. It can use the information that's provided through the Kubernetes metadata API to pull back information about what's actually running in your Kubernetes cluster, also doing things like auto discovery. So if you put annotations on your pods, those annotations can be used to actually go in straight-back metric off of the endpoints that you put in those annotations. So it's an easy way for Prometheus to auto discover where it needs to start pulling metrics from. There's an alert manager, which allows you to send alerts. And you can use the same language that you use for promql to actually write the queries. You can use that same language to write what you would be alerting on. So you basically run a query. And if the value is of a particular range, then you would have the alert sent out to those various locations. And then Grafana is kind of the default open source graphing solution. It can interface in with a whole bunch of different databases, not only just Prometheus. And it gives you a common place to do dashboarding and visualization, give access to dashboards to your developers and other things like that as well. And I'll deploy that quickly here as well. So let's talk about the first component, Prometheus being a way to instrument your code. So back in the day, and we still kind of have this problem. So this is the problem that Prometheus is really trying to solve, is that if you wanted to pull Java metrics and you would have to pull metrics in the JMX format, if you have custom metrics and you might be pushing them to something like stat to be, and then you need to pull metrics from stat to be and then store them in database.  So you might push to a vendor API, or you might have to pull metrics off of a vendor API. A good common one where I pull a lot of metrics from is the Docker Hub repository or registry. You can query the API, and you can find out information about number of pulls. And so as we're tracking the success of our open source projects, I actually have to scrape back data from that API to figure out how many times people are downloading our software. And the problem is that everyone knows what PETA means.  You have to maintain this huge code base to figure out how you pull metrics back from all these various different locations. You have different ender faces, especially if you're doing something with vendors as well. It's not always available for your language. So you might not have an SDK to actually go and implement the thing that you need in your language. And it doesn't always work in this dynamic microservices world, as things are spinning up and down and auto discovery of metrics and things like that tend to be very hard with the traditional way that we've done things. And so there's a whole bunch of different things that people have done to try and fix this problem. Prometheus Metrics is one of them. And Prometheus Metrics and Open Metrics are this slide was written a while ago. But my understanding is Prometheus Metrics and Open Metrics are essentially merging. And the Prometheus Metrics format is becoming the standard Open Metrics format now. So Prometheus Metrics or Open Metrics have really become this de facto standard of how we expose metrics. So a lot of the cloud native applications already support exposing Prometheus Metrics, as well as the projects or services that you'd be running on top of your Kubernetes platform. So things like Istio, traffic, 4D, and S, 4D, and so forth. They all expose their own Prometheus Metrics. And so once you install Prometheus and you have those services running on the cluster, you're able to start collecting information back around how those application services are performing. The nice thing is that you can instrument once and you can support many different use cases. You can also support many different providers as well, so that if you have a commercial company that you want to use, most of the commercial vendors will pull back Prometheus Metrics out of Discover Prometheus Metrics, something like DataDog or even Sysfig, you could automatically have those metrics pulled back. So you just need to instrument once and then you can support the Prometheus server, your commercial agent you might use, Grafana, whatever dashboarding the commercial vendor provides, and so forth. And so the goal behind this is really trying to get rid of all those custom exporters and scripts and everything that we used to do to massage JSON. And this is an example of massaging JSON. We'll skip that. So let's talk about the metrics format and what it looks like. So you have the metric name and then you have a series of labels. You can have more than one label if you wish. And then you have the value of the metric and then the timestamp. And there's a format that this all follows. There's also the data model that they talk about on the Prometheus IO documentation as well. So you can see here we have HTTP request total. In this case, we're just looking at posts that were successful. And then we are looking at posts where the code is 400. And so the nice thing that this allows us to do with these labels is that we can query these labels later using Prometheus well to only get the information out that we want or only get the metrics that we want. So if we wanted to track errors, you could do 400 star star and then a tilde there to match something that matches that regular expression. And I'll show that here. All right, so there is the metrics interface as well that's defined. So the first thing that's important is understanding how metrics names work. And a couple things I'm going to highlight on here because this is really long. So typically the first thing that you have is the prefix. And then beyond the prefix, you then you have the actual metric itself. The other thing is that you're going to have at the end, you're going to have things about what the actual unit is that you're measuring. So you can see here that we have seconds, we have bytes, or we have total. And total isn't necessarily something that's unit. So like HTTP requests doesn't necessarily have a unit that you're measuring. You have requests per second. That could be another metric that you define. But a total or accumulating counter would just be a total. And then you can see here when we combine them where this is the total over number of seconds as well. There's a ton of libraries that allow you to instrument your own code. And so you want to instrument your own code around things like how long is it taking your application to do the business logic type things. And that was actually the problem that we were trying to solve at Orbitz was that we had hotel searches that were taking 60 seconds and we had some hotel searches that were taking 10 seconds. And so we needed to be able to see when those events are happening, when all of a sudden our hotel searches start to fail or our hotel searches start to take a long time. And then we could use that information to determine maybe one of our providers were down or maybe one of our providers were having their own issue.  The other thing that we were really wanting to look at is air search metrics and other things like that. And so we wrote actually a custom format for our Java application to expose these metrics and push them into graphite. And that's an open source project that's probably the code was released but never touched again called Irma. I know it's still out there. I've seen it in a few places. But that was only for Java. So the nice thing is what's happened in the world of exposing metrics is that no matter what language even bash, you have a library that you can use to easily expose metrics in this Prometheus format. The other thing is I would avoid trying to write your own metrics exporter for your language. And I would really encourage you to use one of these that's provided. You need to be careful about when you're collecting metrics is that you don't want to block your application. And so a lot of these libraries actually take into account. We needed to have multiple processes, one serving metrics collection and one serving the actual application code itself. And you also, there's also a lot of libraries and these where you can create the data structures around the actual metrics and things like that. It makes it a ton easier. So there's what's called the metrics exporter. So what you do in your application is you use one of these SDKs to create the exporter. And it's all metrics are exposed via HTTP or HTTPS. So this gives you a common standard way to go in straight metrics. The other nice thing is that you can just open up in your web browser or you can just do a curl against the metrics endpoint to see if you're getting metrics, see if your metrics are incrementing and other things like that as well. There are lots of well-known exporters and there's about 470 different ports allocated for the different exporters. So these exporters are all around things like even low-level things from the hardware layer. So if you're running like Dell and what's that called, the DRAC inside of the Dell, you can pull in stats off of the actual hardware components. You can pull information from PodWatch and other things like that as well. And then there's lots of different exporters as well. This is more of a definitive list of the actual exporters, the ports allocated, but not like for example, we've allocated a port for one of our open source projects, but we haven't started exposing metrics yet. So it kind of gives you the idea of like, there's a lot of people that are wanting to expose metrics in this format and shows you the popularity of them. There's a couple of different ways you can collect metrics as well. So there's some good examples are things like Cadvisor and NodeExporter and KubeStateMetrics as well, which will pull metrics back from your Kubernetes cluster and then expose them for Prometheus to pull. We also have a commercial agent, but I'm gonna skip that because that's not relevant for us. So let's talk about the query language real quick. So PromQL is a full-featured query language that allows you to analyze metrics in real time. You can filter metrics by labels. There's a whole language where you can actually use functions as well. So you can do things like averages, standard deviations, square roots and other things like that as well. Logarithms as well, if you need to smooth things out. You can also do deltas very easily. So it all depends upon what you're trying to create out of your metrics. So if you're trying to create a gauge or if you're just trying to graph a counter, there's different options available to you. It also automatically creates histograms for you as well, just by leveraging this query language. And so the data you get back isn't the raw metrics data, but instead you get the histogram with the bucketing already done and then it makes it easier to expose it to a UI like Rippon or something like that. You can also leverage regular expressions. So let me look at this real quick. So I keep moving this and it's rattling the mic. Sorry. So HTTP request total, this would just be every single request. It's not scoped by time and it's also not scoped by any labels. Then if we wanted to get more specific, we could then say show me the job API server and handler slash API slash common. So this is kind of showing you how you can use, expose different metrics, especially it's really important inside of your application. You're going to want to say the handler. So you can actually trace back into your application where that metrics actually coming from as well. You can see how you can use regular expressions as well. So maybe I want everything that starts or I'm sorry, everything that ends with server. Or for example, I want to not show anything that's a 400 error. And so not anything that matches this expression. So dot is similar just like in grep or standard regular expression. So any character and then star is repeating of that previous character. So in here, since status codes are only three characters, we just put two dots. And then you can also do things like where you're running functions or using functions. And so this is going to give us the rates over five minutes and it's just going to return the data back from 30 minutes ago to one minute ago. So we're just getting that set of data instead of all of the data. All right, so let's talk about the monitoring stack real quick and what's all composed in this stack. And then I'm going to do just a quick deployment and I'll play around with how you set up Rafa and things like that very quickly. So you have the Prometheus server. You have the alert manager. You have the Grafana for UI and then you have exporters and the push gateway. And I kind of had already talked about this as well. By the way, if you were in the operator talk earlier there is a Prometheus operator. And that operator allows you to set all of this up very easily. I'm going to use a Helm chart today. If you're not familiar with Helm, it's essentially kind of like app yet RPM but for Kubernetes manifest. And so, or kind of like Terraform as well where you can very easily go and just say Helm install the name of the thing you want to install and it'll automatically set up that for you in your Kubernetes cluster. And when you have one of these large deployments using something like Helm or other tools makes it a lot easier or even the operator. This is the real idea behind the operator is that if you want to install Prometheus it's much easier just to have one block of JSON instead of all the JSON I'm going to show you or YAML that you need to actually go and set up this entire stack. So there's a different, a couple of different ways that you can do this. I kind of already talked about these as well. One thing that I'll point out is that you probably need lots of Prometheus servers. And that's kind of one of the limitation of Prometheus is that scalability at this level works in a horizontal fashion. And so you have lots of Prometheus servers that are all collecting metrics and storing metrics. The other thing I'll point out is that I'm gonna work around this in a different way. Sorry. Prometheus doesn't do long-term storage. So if you need long-term storage or let me put it this way. Prometheus long-term storage is only as good as the durability of the disks that you provide to Prometheus. And so if you have a SAN and you're like, we're still doing SANs or something like that or using EDS volumes and things like that, you can have some guarantee around persistence.  So you need to use something like inflex DB or Cortex. There's some other commercial software that you can use as well to actually go and store those metrics and have a durable cluster. And then instead of going and connecting Grafana into Prometheus, you connect Grafana into one of these time series database tools. And so let's talk about Grafana real quick. So Grafana is an open source dashboard and graph editor. The other cool thing about what Grafana does is that there's a whole marketplace around data source plugins or data provider plugins and dashboard as well. There's a whole bunch of different data sources that you can use to query data from as well. And so it's just not Prometheus focused, but it's focused on lots of different databases as well, including simple things just like MySQL. So just doing MySQL queries and pulling data out of MySQL if you wanna check. All right. So there's also, as I already said, there's vendor solutions as well. So there's Grafana Cloud and Weave Cloud. We have our own backend that we run as well that lets you store these metrics in a common location as well. We also do things like implement prom QL so that you can actually run queries. So whether this is more about long-term storage, the other thing that we can do is you can use Grafana with us as well. If you choose to. So that's kind of how we try to interact with the open source community by leveraging a lot of the de facto standards that the open source community has created as well as our own projects that we do around open source as well. So let me just grab a chair here and we can do a quick demo. Hopefully my demo environment didn't crash as well. All right. So if I do a kubectl, git, pod, I shouldn't have anything running here. Must be getting close to lunch because now the Wi-Fi is not working. All right, there we go. That wasn't too bad. And so I'm just gonna do a history because it's easier because there's a flag I gotta set. So if you wanna know how to get started with Helm, it's actually really easy. You just download the Helm binary and then you run a Helm init and that Helm init, what it does is basically installs Helm for you. And so this is actually a new cluster that I had just set up and did all of this this morning. And so if I just run a Helm install, specify the name, that's your unique identifier for it and then you specify the chart. And then just like we learned in the Terraform chart, there's values that you can set to change what actually happens when this gets deployed. So we're changing a variable that's defined in the Prometheus chart, RBAC.create, and we're setting that to true. There's things like image names, image versions, there's a whole bunch of different things that you can change. And I actually downloaded the values.yaml. And so you can see here, there are things like mounts that you can change, upgrade strategy, if you have a service and you want to expose it via an IP or a particular load balancer, then you can do that as well. All right, so I'll hit install. And then you'll get back information about how to actually get to the things that you want to get to. So I'm going to export this, and we're just going to connect directly to Prometheus and not use Grafana real quick. And so now if I go to 127.0.900, I can see that Prometheus is up and running. The other really interesting thing here is, as soon as I deployed it, I started getting metrics back as well. And so if I click execute, then I can actually see the metrics and the value. You can also click on graph and you can actually see that data as well. And so maybe I want to go back just 15 minutes and you can see that when I did that deployment, it's automatically started pulling metrics back for me as well. So it's really just that easy and just that quick to start pulling metrics back. And then let's install Grafana. And so once again, using a Helm chart and I'll do a Qubectl real quick, Qubectl get pods. And this is the value that Helm provides. So you can see all of those different components that Helm created for me that are running Prometheus. And then you can see that it created the Grafana container or Grafana pod as well. And so it makes it a lot more simpler to actually go and deploy things to your Kubernetes function. So now I need to go and get my secret. And now I'm going to go and export this again. All right, so grab the secret. And now I should be able to go to port 3000 and Grafana is up and running for me. Then I'm logged in. So the first thing you need to do is you need to configure a data source. And so you can see all of the different options that are available. There are different plugins that you can add in as well. So if there's not an option there in the default out of the box, you can download a plugin and then that plugin allows you to access one of these other data sources. And then I'm just going to add Prometheus and I'm doing a half the cheat because it's a long URL. There we go. And all I need to do is save and test. And it tells me that the data source is working. So I should be able to go here now and say create dashboard. And I'm going to create a graph and do edit. And then we should be able to do that node load one. So that interface that I was looking at earlier, remember that kind of query interface against the Prometheus server, you're not able to save anything. You're not able to get these dashboards and other things like that as well. So this gives you a much more fully functional UI to actually go and create these graphs. You can resize things. You can zoom in to any time range as well. You can turn things on and off as well if you only want to look at particular things. You can do that. But the nice thing is that Prometheus or I'm sorry, Grafana offers, let's say, lots of different dashboards that you can import as well. And so if you go here to import and let's just go to Grafana and click on dashboards and you can see all of these different options that are available to me. And so let's take this one here and all you have to do is copy this ID and then I paste in the ID and click load. And it's gonna give me information about this and I say import. And now I have the host metrics of like Kubernetes cluster. I can drill down into the dashboards that they provide, looking at things like interrupts, what version of the kernel that I'm running and so forth, an overview panel as well. I can drill down into CPU or load and other things like that as well. So there's a whole host of different dashboards available that you can very easily insert into your environment and load them up. So with that, thank you for taking the time to listen. Hopefully you've learned something about Kubernetes and I'm happy to, I'm sorry about Prometheus. Maybe you learned something about Kubernetes too. Happy to take questions if anyone has any questions. I just say that like this is also a good way if you have a bunch of, I know there's a lot of people that are like hardware hackers in this community. So if you're having IoT devices and other things like that as well and you need to expose metrics, this is a very good way to expose metrics from your IoT devices and other things like that as well and then you could have a collector go and collect those metrics so they can push it back to a push gateway or something like that as well. And then you have Prometheus and Grafana where you can go and easily start to graph those metrics and pull that information back as well. I'll be around for a little bit if anyone wants to chat but thank you very much for attending.