we had seen in the earlier lecture how the idea of inductance is used in order to derive an expression for the force that is exerted. More specifically we saw a singly excited linear motion system which consists of a coil and an iron rod that is fixed to a substratum connected by a spring having a spring constant of k the iron bar could have a mass of m and you are exciting the coil with a voltage v in this case we wrote down the system expressions we started with the electrical system equation which said that v equals resistance multiplied by the flow of current current is assumed to be flowing inwards at this terminal and therefore the applied voltage v would equal resistance multiplied by i plus the derivative of the flux linkage as we saw this is an expression that would fit all systems and then from this expression onwards we went on to derive further equations we started with from this we derived an expression for power input and we said that this input power is equal to the resistance loss plus the mechanical power output plus the rate of change of field energy this equation is important and from this we wrote down if you get the input electrical power if you write vi and then this was equal to i multiplied by this expression and then we wrote down that the rate of change of field energy is nothing but the derivative of the field energy which we wrote down as half li square if it is a magnetically linear system this is valid for a magnetically linear system which means systems where the bh curve is a simple slope and then from this we identified the mechanical output power as let me call that as p mechanical that is half i square dl by dt from which we identified that the force that is exerted is equal to half of i square dl by dx and from this we see that the developed force it depends on the rate at which inductance is going to change with respect to x that means if you had locate if you had said that this was the origin of the bar beginning to move this is x equal to 0 and then the bar moves in the direction of x the expression for the developed force says that force is going to act along the direction of increasing x so if this is the force this is the direction in which it acts and this is greater than 0 would also mean that dl by dx is greater than 0 that means that as x increases the inductance increases which definitely is true if the bar moves inside the inductance as seen by this input will increase now all this can be obtained from this and then if you want to find out how this bar is going to move you write the mechanical equation if you call this force as fe then fe minus k times x because of the attached spring this must be equal to mass of this multiplied by the acceleration which is then d square x by dt square we had seen this in the last class so this is just to remind ourselves what we have done now this is not just an imaginary a hypothetical system this is really used in applications there are equipment known as solenoid valves solenoid switches which but which work based on this idea for example if you take a solenoid a solenoid switch then it would look like this you have a cylindrical iron structure in the center of which there would be a hole passing through the cylinder and around this around this central hole you then have coils that are wound and within this central hole there is an iron bar that would move so if you now energize this allow some flow of current into this this bar would be forced inward would be drawn inward and you can attach a spring here which will arrest the movement so it would move down against the spring force these are used for example in all your automobiles to start the engine in the starting sequence of the engine you have this with this will go down and close an electrical switch here which will then allow the DC motor to rotate and start the engine right so if you want to analyze this kind of a system and say how much force is going to be developed what will be the force which is developed when it hits the end you need to write down equations like this and then analyze the entire arrangement you need to see how the field is going to be developed in this how this bar will move what will be the input current that is drawn into this all this has to be analyzed now we have an FE analysis of this as you can see that this arrangement is entirely symmetrical about the axis in the center we call such systems as being axis symmetric systems it has an axis symmetric geometry and in order to do an FE analysis of this most of the FE software allow us to model only one one section of this which is assumed to be then swept around and therefore it may be enough to represent the section which is seen in the middle so you have half of the this iron rod and then there is a gap here this is going to hit somewhere at below below this and then these turns are distributed here all this is flow of current into this and then you have the cylinder as well so I am now drawing a view of the sectional sectional view this is how the system will be this section is as if you slice this slice this by a plane and then take one half of that alone this is how the system will look now we can see some of the outputs from this from the simulations that we have done in order to get an idea of how this input current is going to flow let us see the simulation results so here then we have some simulation results using FEM and as we saw on the board here we have a sectional view of the spring plunger system this is the outer shell and then here you have the iron rod that can move and the excitation is given here and you can see how the magnetic field is there you can see a large field value existing here which is about 0.5 Tesla as per the scale 0.4 Tesla as per the scale that is given here and the field decreases as you go to the extremities of this bar and here and due to this field then as we have seen through the equations this bar is drawn inwards and as it is drawn inwards as it goes close to the end stopper now you can see that a significantly larger field exists over a longer length of the bar and this gap is now very very small and you can see that the force that has been developed is 3.37 Newton meter in the earlier case when the gap was large and the inductance is only 0.0037 Henry 3.7 milli Henry whereas now the inductance has increased when the bar has reached the end nearly the end the inductance has gone up to 0.01 Henry and the linkage has also gone up 0.06 Weber as against 0.022 Weber one can also see that the field in this area the field in the region here is bending out of the air gap it is not really flowing straight along this but you find all kinds of field lines that are going out whereas here you do not see that effect field lines are going straight from the bar on to the other level right this kind of effect where the field lines move out of the ordinary route these are called this behavior is called as fringing this happens if the air gap is large you can see for example in this case also the air gap here is pretty large and you can see many of the field lines going through other routes and not really through this iron bar directly on to this plane below here again you can see field lines going outwards. The analytical expressions that we wrote for inductance for example in the earlier lectures we wrote that inductance is then some mu into n squared into area divided by the length of the iron path or length of the air gap path all these are valid when the air gap if there is an air gap the air gap is small if the air gap is small then all the field lines that go through this iron bar cross the air gap and get into the other area and not many lines flow through in the other way but if the air gap is large then the field is more distributed and it is very difficult to find out what the inductance exactly is your hand calculation will not match the actual inductance that you get. So this shows how the force is there and we have seen from the expressions that the force is given by half I squared into dl by dx and as this bar approaches the as the air gap becomes very small dl by dx also becomes very large and therefore the force developed is significantly higher than in the earlier case of 3.37 Newton meter. Now all this is an analysis of how the field plot is going to look when this iron bar is at different locations this is not going to say for example how much flow of current is going to be there how fast the bar will move right and how long it will take for the iron bar from beginning this position all the way to travel to this position how long is it going to take all these are not shown by this figure for that we have to do a simulation we have to solve all these equations that we have written down earlier by some means these are normally difficult to solve by hand so you have to take recourse to some kind of simulation software in order to solve these equations and if you do that here you can see the results of how this works this line that is in green shows the displacement x beginning from 0. So if you let x equal to 0 be somewhere there in fact that distance is about 1.5 inches that is considered here and then energize the system we have looked at initial or to put it the other way the initial distance between the bar and the stopper stopper is when the bar goes and hits in the end this distance is 1.5 inches and we are supplying a DC voltage equal to 12 volt right and the resistance of the coil is 2 ohms now with this one can see how the simulation has happened the energization happens at this instant at t equal to 1 second until then the DC supply is not switched on and you can see that the initial input current drawn is equal to 0 no current flows obviously before you switch it on as soon as you switch it on this bar is fairly far away from the rest of the system and therefore the inductance is very small since the inductance is small flow of current I attempts to increase fast and as this increases there is also an exerted force on this bar and the bar begins to move you can see this plot this plot shows the displacement versus time until then the displacement is equal to 0 that means bar is not moving and from this point onwards bar has begun to move in response to this ?2 and along with movement of the bar the inductance also increases if the inductance is going to increase then ? which is the linkage of flux which is equal to inductance multiplied by I that also increases and after some time the rate at which ? increases is so high that the flow I begins to fall right and in response to all these this bar then moves all the way from 0 goes up to 1.5 inches hits the stopper and there it stops you can see that the input I drawn here this axis gives you I this drawn increases up to 5 ampere or so and then drops down at this instant the bar has hit the limit and if it has hit the limit it is not going to move anymore therefore the inductive effect is no longer there and from this instant moving of the inductance does not become different it is a fixed value and therefore I increases at the normal increase of increase having L by R as the ratio so here it increases and then settles down to a level of 6 ampere which is the same as 12 divided by 2 ohm that is 6 ampere so at the end it has to settle down at 6 ampere because no more inductance is going to change everything has settled down you are giving DC current and therefore it has to settle down at 6 ampere but until then you can see that there is significant events that are happening this bar has moved from 0 all the way to 1.5 inches and stop and how that happens is displayed by this graph. Now in the analysis of electromechanical systems these are the kind of results that we are looking for we want to know how the situation how this electromechanical system behaves with the increase in T if you did not know this you would have said that applied voltage is DC and this has a resistance equal to 2 ohms which implies that it should draw 6 ampere and you see that it is not drawing 6 ampere immediately there are lot of things happening here ultimately if everything settles down no more inductance changes there then this I settles down at 6 ampere it is important to understand what we are attempting to get at by the analysis that we are doing in all these lectures we will now switch back to our the other analysis let us go back to the board so we have seen so far how linear motion systems can be analyzed they have application value by themselves but we will now move on to rotational systems most of the electrical machines are not linear but they are going to rotate about certain axis so in this again let us consider singly excited systems as we did for the linear k so in the case of a rotational system what we really have is a stator which is the fixed part of the machine which does not rotate and then you have a rotor inside this you have a rotor with a shaft there is an air gap here so let us say that all this region is iron outside all these is iron region here you have air I have of course exaggerated the air gap nobody would make a machine with such a large air gap so here is iron here is iron and then you have a shaft to which you can connect some mechanical loads this is the kind of system that we would have and we want to know how to analyze or represent this behavior of the system as an equation and we say that there is an excitation mechanism there is a wire loop that goes here so one must understand what this figure represents this is generally called as a slot in machines of course you would have seen all that at the UG machine course and this is really a structure that is cylindrical and we are taking a section of the cylinder right and this is how it looks let us say it has one coil which starts as one coil side here goes along the length of the machine completes on the other side and then comes back here may be it has several turns as well finally you get one terminal here and another terminal here what we want to see is how this system is going to behave when you give an electrical input at across these two terminals so again we write the same equations the applied voltage V across these two terminals can be written as R into I plus P times ? and then input power is Vi equal to I2 R plus I into P of ? and we know that input power has to be equal to the same ways in which it is then consumed you have a resistive loss component you have a mechanical power output hopefully it is there and then you can have a rate of change of field energy and in this system also because we are considering a linear magnetic system so far we can write field energy let us denote that by WF WF is then simply equal to ½ Li2 and we are seeing that the expression development is the same as what we had done earlier and therefore we expect to land up with a similar result that mechanical power is equal to ½ I2 DL by DT which can now be written as because this is a system that is going to rotate then you can write this as ½ I2 DL by DT into DT by DT now DT by DT is nothing but angular velocity so this is angular velocity and if you say mechanical output is something multiplied by angular velocity then this something has to be torque therefore we can write that in the rotational system torque is equal to ½ I2 DL by DT this is an analogous expression to what we had earlier in the linear motion system you have force equal ½ I2 DL by DX now since you have I2 here it means that whether you excite the system with plus here and minus here or you reverse it and say plus here and minus here it is immaterial as far as this expression goes because you have I2 so whether this current is greater than 0 or less than 0 where it is coming out the developed torque will always be greater than 0 but looking at this expression and looking at the geometry that we have drawn here it would be interesting to note that the inductance in a linear magnetic system the inductance is a function of geometry alone it means that depending on how the different elements of the system are arranged you would have a fixed inductance in the earlier case we saw that if you have let us look at the system here we saw in the simulation also if the bar was at a certain height you have some inductance and if the bar moves down the inductance increases and it is therefore only dependent on where the bar is once you fix the position of the bar the inductance is fixed in the system here the inductance if at all you say that it is ½ I2 DL by DT how can angle undergo a change angle can undergo a change if the rotor is now going to rotate if the rotor undergoes a rotation then the angle of the rotor undergoes a change and we are going to look at how the inductance of this is going to change if the rotor is going to rotate but here if you look at it irrespective of how the rotor is going to be turned what is the angular location of the rotor the system geometry does not change as far as this loop is concerned because the rotor is completely fully cylindrical it will not be able to make out the difference between the rotor at some angle and the rotor having rotated to another angle and therefore in this case DL by DT is really 0 and therefore you do not expect this system to rotate at all on the other hand if you have a rotor that looks slightly different let us say that the rotor is not fully cylindrical like this but it looks like this let me also erase these lines can create some confusion and perception so if the rotor is like this then it does make a difference whether the rotor is here or whether the rotor is here the air gap that is there at a given angle is completely different and therefore the inductance that this coil would experience is different for different angular locations of the rotor and therefore there is some value for DL by DT and in this case therefore the rotor will definitely move it is therefore important that inductance some inductance changes with respect to rotor position if inductance does not change with respect to rotor position then the machine will not rotate you will not able to develop a generated torque however one can now look at a system where the rotor incidentally this kind of rotor is called as a salient pole rotor so in the salient pole rotor inductance will depend upon where the rotor is the angular position of the rotor and this the generated electromagnetic torque which depends purely on the variation of inductance right is then called as a reluctance torque. Re reluctance torque exists in systems where inductance is going to change the inductance in the sense self inductance self inductance changes with the angle of the rotor on the other hand if you have systems which are cylindrical where the rotor is also a cylinder please note that what we are drawing is a section of the machine the machine is a cylinder and we are taking a section and we are viewing that section end on so this is the axis of the machine. So if you have a system like this and you intend to have it rotating then you need to put one more coil at least here you need to therefore have some slots it is difficult to have a coil when there is no slot it has to be housed somewhere so there would be a slot and then you have a coil that is running through this now we can look at whether this system will be able to move earlier we said that when this is not there it is purely a cylindrical arrangement no torque is developed but now will it be able to move let us see whether this will move so in order to derive an expression in this case again we have to write down equations and we start with the familiar equations that we had written earlier now there is an excitation source on the stator there is one on the rotor as well so there will be two equations in the electrical part so we write V stator that is the voltage applied to the stator is equal to stator resistance multiplied by the current that is flowing through it obviously if you are going to have a wire look here it will have some resistance there is some current flowing in and therefore there is a resistive drop plus P times the rate of that is P times the linkage of flux in the stator that is rate of change of stator flux linkage and similarly you have another expression VR which is the voltage applied to the rotor that is RS RIR plus P times IR this form of the expression as I said is fairly you it will be repeating this is a general expression voltage is always equal to a resistive drop plus rate of change of flux linkages that are there but this alone is not enough you then need to have an expression for ?S and ?R ?S which is the flux linkage of the stator can be written as self inductance of the stator multiplied by the current flowing through it again we are assuming a magnetically linear system but the linkages will not be just the result of flow of current in the stator alone there can be flux linkages here when there is current flowing in the rotor as well therefore there is a mutual flux linkage between the two and therefore it is a mutual inductance between the stator and rotor multiplied by the current IR and similarly you write an expression for ?R which is the flux linkage for the coil in the rotor that is then LR multiplied by IR plus MSR multiplied by IS so these are the expressions that need to be substituted for ?S and ?R here so far the procedure is the same as what we had done in the linear motion case and in the singly excited case we wrote the expression for the applied voltage as VRI plus PSI but there are two voltages now so you have two equations and ? is not just one there are two size flux linkage for the stator and the rotor and therefore you have both of them the next stage is to find out how much input we are giving V into I here again there is one stator coil one rotor coil therefore total power input the total power input will then be given by VS into IS plus VR into IR that is the net power you are giving some power to the rotor you are giving some power to the stator as well and this power has to be then equal to the resistance loss in the machine plus the rate of change of magnetic field energy plus the mechanical output power if we expand this is then equal to IS square into RS plus IS into P times IS plus IR square into RR plus IR into P times IR this is what we said must be equal to resistance loss plus P mechanical plus rate of change of field energy so DWF by DT the resistive loss as is usual is easy to identify it is I2R here and I2R here that is the resistive loss component and therefore this term plus that term must equal mechanical power plus DSI by DT now the question is how do you find out what is the expression for field energy in this case we said that field energy is simply half LI square but then there was only one excitation system a single coil that was there on the stator and therefore it is simply half LI square but now you have a coil on the rotor and you have a coil on the stator so we need to derive an expression for the field energy in a multiple coil system and more than one coils are there how do you get the field energy once we get that we will be able to put it in and solve that expression we will do that in the next lecture so in this lecture what we have seen is that we started with the singly excited system and reviewed how the force expression is obtained and we have seen physical examples of how this expression could be of use it can be used to design electromagnetic equipment and from the linear system we went into the linear system where you have a rotational movement the rotational systems are by far the most frequently used and in the case of rotational system we saw why a singly excited system with a cylindrical rotor is not likely to move at all you need some kind of saliency in order that you get it moving and it is important to remember that inductance is a function of the geometry of the system if the geometry is going to change then the inductance will change and again it is important to remember it is a function of the geometry alone if it is a magnetically linear system and that is what we are looking at and inductance changes with the rotor position means that there is going to be a generated electromagnetic torque. In the next case we need to derive the expression for the field energy and substituted here we will see that in the next lecture and for this lecture we will close now.


The Cavalcade of America, sponsored by the DuPont Company, maker of better things for better living through chemistry. That is the ear of the United States Coast Guard, listening for a submarine. Bearing 2-1-4, nothing there. Pick up anything, Casey? No, sir, not yet. Bearing 2-1-5, nothing there. Bearing 2-1-6, nothing there. Bearing 2-1-8, nothing there. Bearing 2-2-0, contact. Ladies and gentlemen, this is the Cavalcade of America, sponsored by DuPont.  Later in the program you will hear from our special guest, George H. Corston, chief gunners made of the Coast Guard cutter, the Campbell, which recently sank or dispersed six German submarines. Listen then to Submarine Astern, starring Ray Milland, on the Cavalcade of America, sponsored by the DuPont Company. My name is Dan Harper. Gunners made first class, and the submarine chaser, Dewey, signed up out of Boston. Just another member of the United States Coast Guard. Right now we're in Port, with a few hours to kill, so like every other sailor from Singapore to sail him, convoy 5-foot-2 of female. Pretty, isn't it, Dan? I'll see. I mean the music sailor, not that number with a hen of red. Oh, my error. If you won't make an eye to some Brooklyn special, you're looking back at the table at Pat. Don't worry, she's in good hands. Yeah, too good. That's what I'm afraid of. Does a little competition scare you? Of course not. I love it. But just for fun, let's go back to the table and see what they're talking about, huh? Just for fun, eh? Pardon me. Excuse me. Come in through. Sorry. Sorry. Thanks for the last. Hello, you two. Hi. As I was saying, Pat, he zoomed out of the clouds and opened up an area. Hey, look, pilot. You don't expect a brass band. Just a nice friendly hello, too. Oh, sorry, I was just talking to Pat. Yeah, so I see. Tired of dancing, Dan? Ah, that's not dancing. That floor's the second front. Phil was telling me the most thrilling story about the first time he shot down a zero. Oh, he was, was he? Hey, Bosun, you just sticking an oil for the Coast Guard? I was listening. Doris, you ought to get Phil to tell you all about it. I'd be glad to. I didn't hear anybody ask. And besides, it's time the Coast Guard got a few words in. Ah, that's the trouble with you, New Englanders. You've got salt water running through your veins. I can remember the time we rescued the crew of that fishing boat to Mary Ann. It's bounding off the coast in Antarctica.   See, what do you think we're doing that ocean? Go fishing? I thought we were fighting Hitler in the Jap. This isn't a fight, baby. I'm just setting this eagle straight on the Coast Guard. Oh, Bosun, tell us about the time you caught Fearless Fosdick smuggling in a boatload of French perfume, huh? Say, Phil. Yeah, what? There's something I'd like to ask you. Go right ahead. Do you ever go up high enough so you have to use oxygen? Oh, plenty of time. Ah, that accounts for it. It's affected his brain. Let's dance, then. Sure, sure. Getting late, Dan. Yeah, we've got to be shoving off. I'm heading out to sea tomorrow. Hey, Boats, take care of my share of the check, will you? Give it to you back on the ship. Don't worry, I'll remind you. So long, sailor. See you. They can catch me away, oh. So you walk a couple of blocks and hop on a Washington Heights Express. Past 72nd, 96th, 103rd. A few other stops before you get to 181st. You walk a few more blocks up the steps of a brown stone and... They're here. Yeah.  About why? About having Phil tell me how he shot down that plane. Oh, it wasn't that.  I don't think so, Dan. I know you don't, baby. Well, it's getting late, and I got to get up early. So you're careful out of that plant, aren't you? Oh, sure I am. You know, that riveting is pretty dangerous work. You got to watch yourself. I worry about you, too, Dan. Uh-huh.  Oh, she's sleeping by now. You know, these blackouts have some good points, too. You sure do. How long are you going to be gone? I don't know. Can you tell? Look, I better be shoving off. Dan, once more before you go. Yes, you. Keep your chin up, baby. So you say good night, and then that long trip back to Staten Island.  The train's almost as crowded as two in the morning as the early afternoon. You remember beneath the streets of New York and read the ads. You know, what you guys had won too many. Take a look at the different uniforms from the different countries. Fliers from Australia. French sailors, American dough boys. You start to nod yourself. Then finally you get to Battery Place. Hop out of the subway, one across the street, then one to catch the ferry. You start to feel a little prayer when you get on a Staten Island ferry. There's as much of a boat, but it goes on the water, and that's good enough for you. You watch the dimmed-out skyline of New York fade away, and then in the distance you see the lady with a lamp. Not many civvies on the boat at that time. Mostly sailors. Finally you bump against the dock. You hop off, start walking back to the ship. You spot a couple of other guys in the medouin. You catch up to them just before they get to the gang plane. Ah, who cares what they're wearing? Hiya, Danny. Hiya. As I was saying, blondes over redheads any time. Well, stick to redheads. Ah, less sometimes, I think. Well, let's leave it up to Danny. Leave it up to him. Not after what he was dragging down at Baltimore. Well, so what if she wasn't pretty? She went to college, she had brains. And besides... Hey, who's doing that? Who's whistling? Me, why? How long you been in the Coast Guard? Five months. Hasn't anyone ever told you never to whistle aboard ship? What are you trying to do, jinxes? Don't you know the whistling is just like asking for a storm? Well, I don't know about the rest of you sailors, but I'm going to hit the sack. And the rest of you do the same thing. Down the ladder into the belly of the ship. Crawl out of your clothes and into the sack. Couple of the guys are playing AC Ducey. From buff to snoring as usual. Just stretch out and you know your home. A slight heave of the ship as you ride that anchor. The water slapping against the sides. The smell of grease. You're yawn. Roll over on your side and start dreaming. That buzzard just ain't the rich. You like breakfast and bed hopper? Sure legs, dammit. I'm showing, I'm showing. Doesn't that guy ever sleep? Someday I'm going to get him in a dark alley and make him eat that bosun's pipe. Yeah, and don't forget the cord. I won't. Come on, let's wash down. I'm starving. Hey, who's got my toothpaste? Not me. Then it must be just a coincidence that it's in your left hand. Well, imagine that. Hey, cut it out. What are you splashing water? What are you, a fresh water sailor? See ya, chow. All right, I'll be right with you. Hey, Cookie, take my sunny side up. This morning that's cramble. You know I like them sunny side. There you want egg? Of course I want egg. Just close your eyes, Harper. You'll never know the difference. Well, we had it, Captain. Just a routine cruise to calm three. There's plenty hot down there. Wolfpack of German subs has been reported working there about. If we're lucky we'll find it. We're shoving off at 0800. Have the boss in pipe, muster. Yes, sir. Boss in. Mike, muster. Yes, sir.  You take care of about a hundred different things. The last mooring lines are cast off. The ship starts to move down past the docks. Out into the bay. Down the narrows and out to sea. Rudder 15 degrees right. Rudder is 15 degrees right, sir. Dear course, 1-8-5.  Off to Torpedo Junction. How old are the sounds and the smells of the subchaser around you? Around you and about 54 other guys. Men on the bridge of the ship. The brain. Helmsman. Captain. Radio. Young Ensign from Buffalo. Standing up there guarding the ship and all the time listening to the incessant ping-pong of the sound detector. Listening for that ping to come in pairs. Listening for a contact. Captain. What is it, Mr. Becker? What are our chances if we do spot a sub? Excellent if we spot a first and the depth charges sinker. But if she surfaces, we'll have a fight on our hands. We'll give a good account of ourselves, sir. I don't doubt that. But remember that a sub's a good elegy than we are. It won't take many shells to sink a 165-footer. In fact, one well-placed torpedo will do it. A 165-footer with a 55-men aboard. Every man aboard can hear the steady thump of the diesels. Even the men are sitting the crow's nest for hours with the wind whistling like thromb. Relief for the lookout. The lookout is relieved. I sure don't envy you, Larson. My watch is behind me and I'm headed for a cup of jamoc. Is there anything? Not even a fish. Now, if you don't mind, I'll leave you to your thoughts. I'm freezing. And down in the recreation room. A recreation room where it isn't a mess room.  That's where you go to stretch out and shoot the breeze when the other guys are knocking themselves out. Hey, Hederman. What now? How do you spell retaliate? Retaliate? Why? I'm writing to my girl. Oh. Or, uh... How do you want to use the word? Well, I'm just saying, like, Dear Dolly, I have received your letter and now I've retaliated. Down in the galley, there's the everlasting symphony of pots and pans banging against the bulkhead. There's the thump of the engines and the steady ping of the sound detector on the bridge. Whatever you happen to be on a gun crew, you get plenty of fresh air when you're giving that three-inch of a beauty treatment. Hey, hand me that hunk of waste, will you, kid? Hey, uh, a nice-looking gun. We wouldn't know. Oh, we've been shooting at his pop bottles and flowing whales. He's kind of touchy about that, kid. You see, every time he leaves the ship, he sinks us up and the ship he joins goes dry. It's sort of a game in the Coast Guard.  Ah, listen, Sergeant York, I never heard about you bringing in any Germans. Well, that's only because I've... Say, what are you wearing? A sweater. My girl made it for me. Looks more like a bathrobe. The ocean is starting to turn green and black. The ocean isn't the only thing that's turning green. I'm all right. Looks like we're in for a blow. Look at those clouds. You know, Skip, I remember once we were in a storm for 10 days. Is that so?  It's getting worse, isn't it? Oh, this is practically calm. Why, I can remember when... Tell them all about it. He'll enjoy it. I got a wheel watch coming up. See you, chow. I'll be there. So will I. Relief for the watch, sir. I'll leave the wheel. The course is 185. The wheel has been relieved, sir. Steering 185. Very well, little old. Bearing is two to eight. Nothing there. If there's one thing you do want, it's a target. You'll settle for just one submarine. Basically, you've just been drilling, but you can never control when you're liable to find one down Pelisco Valley. So you practice loading and firing, loading and firing. With all your griping, you keep the sound of the detector running through your mind. The ping, ping, ping. And after a while, you think you hear them in pairs.  Look out to sea. Maybe. Yeah, but there's nothing but sea and sky. Pick up anything, Casey? No, sir, not yet. Bearing is 204. Nothing there. Bearing is 206. Nothing there. Bearing is 208. Nothing there. You are listening to Ray Milland in Submarine Astern on the Cavalcade of America, sponsored by Dupont. A moment ago, we heard the shrill whine of the sound detector. The single whine that means the dewy is still searching for a submarine. There's 210. Nothing there. It's the waiting that gets you. Three days out in that ocean, and you haven't even picked up a sleeping whale. Nothing but drills and eating and sleeping and waiting. Always waiting for that whine to come in pairs. Your nerves get on edge and you snap at the guy next to you.  Bearing 216. Nothing there. Bearing 218. Nothing there. Bearing 220. Contact. Contact bearing 220. Ranges to 00, sir. Rightful rudder, steer course 210. Target changing, bearing rapidly to the right, sir. He's wise to us. Rightful rudder, sir. 220, sir? Yes, sir. Horses 220. This looks like it. It might be just a whale or some fish. You got a great help. Hey, I wonder where it is. Change your mind? Yeah, we're doing too much dodging and weaving to be playing tag with a whale. I wonder where he's hiding. Why don't you go up and ask the old man? We're only too glad to point it out to you. I was only wondering. I know what's going to happen to one of those 10 fish. Topito the port! There it is, Skip. Topito, two points to port. Topito! Look at that thing come. If anybody wants to pray, now is the time to do it. Boy, it's getting awful near. Too near. Why doesn't the skipper get us out of this? Stair course 240. Rudder is full right, sir. Study of port. We turn it off. Maybe. Maybe. Wow, it's a good thing we ain't where we were. You can say that again, brother. All depth charges 100 feet. Set all depth charges 100 feet. All depth charges are set, sir. That hiding won't miss on the next one. Bearing 224, range is 165. Stair course 224. Study on course 224, sir. We'll keep bearing right down on them. Our only chance is to throw those icecans before he has a chance to send another topito. Bearing is 230. Range is 150. Target bearing changing rapidly to the right, sir. Study on course 240. Study on course 240. You think they'll let go with another one? They will if they get a chance. Now stop talking about it and look. I'm looking. I'm looking. But a guy can wonder, can he? Maybe he'd like me to swim over and ask him. Keep looking. Range is 230. Range is 90. Study on course. Study on course it is, sir. Stand by to drop pattern number four. Standing by to drop pattern number four, sir. Range is 65. Water is cold. You sure picked us well, Tom. We're talking about swimming. Why don't we drop those charges already? Look, Mac, stop bothering me with questions. I got things in my mind. Range is 400. Bearing is 290. Right 15 degrees, rudder. Stair course 290. Water is 15 degrees. Right, sir. Study on course. Range is four. Lost contact, sir. Well, quite. Yes, sir. Got it back, sir. Range is 450. Bearing is 242. Stand by to drop charges. Standing by to drop charges, sir. Stand by to drop charges. Does that answer your question? Boy, I'm still sweating. Yeah, you've got good reason to. Range is 400, sir. Range is 350, sir. Drop charges. I've got chances, Danny. Well, pretty good if a depth charge is find it. Not so hot if she services and have to fight it out with deck guns. I never knew these boats were so small. They can hold their own. Boy, the way that water shoots up, it looks like a picture I saw once of a thing called Old Faithful. Never mind that scenery, Rembrandt. Look for oil and wreckage. Well, the way this ship is weaving around it. Now this is where I find out why we practice. You ain't kidding. All guns target. Two points on port quarter. Range is 550. Scale 496. Commence firing. Well, you heard him. Come on, let's go. Ready one. What? Ready two. What? Out of the war line of wicked singers. They don't get us worse. What do you think we're going to do? I'm okay. How's the gun? We caught a real one that time. What are we waiting for? Another one? No, I see what they mean by I'm moving. One. I can see it. It's really getting hot. It's them or us. Come on, baby. Push those shells off. We're counting on you. For you, Skip. Now for a close look at some of those Nazis. There's one now. Water's freezing. That's their worry. Come on. Get up here. Come on. Over there with your buddies, chum. Hey, there's another one. Hey, the fishing's pretty good. Looks like you caught some gold braid on this one. Oh, I did. So I did. Thank you. Hey, this one speaks American. I'm Captain Schweitzer. Would you please take me to your captain? Yeah, you walk in front. I'll tell you where to go. I like to tell him, too. Harper reporting, sir. There's a captain of that sub. So I see. Good shooting, Harper. Thank you, sir. And now, Captain, if you would step into my quarters. These are pretty dangerous waters, Captain. What are you doing around here? I have been waiting on the bottom for three days for a convoy to pass. I thought you were the first ship. That's why you picked up my sound. I see. It's embarrassing to be sunk by such a small ship. Fortunes of war, Captain. That's the way it happened. The next time I get a sure leave, I'm going to catch up with that aviator. I'm going to tell him the Coast Guard motto, Semper Paratus, always ready. Thank you, Ray Milland. Ladies and gentlemen, in a few moments, Mr. Milland will return to the microphone to introduce our special guest of this evening, Chief Gunners made George H. Corston of the United States Coast Guard. Meanwhile, we have a story of a new chemical development saving thousands of pounds of rubber in the war effort. Bomber noses of loose site and other transparent sections for fighter planes while they are being manufactured are covered with protective sheets of tough brown paper that usually stay on them until the plane finally rolls off the assembly line and takes to the air. But just to say they're covered with paper isn't enough. The paper must be fastened to the loose site so firmly with a special adhesive that particles of sawdust or dirt cannot accumulate under the covering when the loose site is cut with a high speed saw or, say, drill. And though it must cling very tightly, the adhesive must allow the paper to be peeled off leaving very few smudges and spots. The problem that came up was that the best known adhesive which would do all of these things required scarce rubber latex. Well, America needs bombers, but America also needs rubber. So DuPont chemists and technicians set out to compound an adhesive which would be the equal of the one used or better if possible but which wouldn't call for any rubber latex. They experimented with more than 150 formulas. And to make a long story short, they finally created a new adhesive. DuPont and other manufacturers of acrylic resins would have used this year hundreds of thousands of pounds of rubber latex cement. That rubber will be saved. This new DuPont adhesive for acrylic resins so new that it doesn't even have a name is actually better than the old latex adhesive. Right field and the Navy quickly approved it. It can be manufactured in already existing equipment. It withstands high and low temperatures, high and low humidities. So loose site replacement parts may be shipped to North Africa or Russia with safety. It has no chemical effect that might swell or discolor the loose site. It doesn't age as rapidly as rubber. It withstands sunlight better than rubber, an important factor in protecting a plastic so vital to aircraft. It is much more uniform than rubber. In fact, it has everything rubber has for this purpose plus other advantages. The new adhesive replacing a more critical material was developed by DuPont at the request of the Army, the Navy and the War Production Board. It is under allocation by the War Production Board for this particular use. But there is little doubt that it will find other uses after the war. Another wartime problem has been solved. A wartime conservation measure has succeeded. Thanks to the DuPont know-how which brings you better things for better living through chemistry. And now the star of tonight's cavalcade, Ray Millan. Thank you, ladies and gentlemen. Our fictional story tonight, partially parallel to the true story that was in the news a few weeks ago about the Coast Guard cutter, Campbell. We are fortunate tonight to add realism to the broadcast by having with us George H. Causton, chief gunners made of the Campbell. Thank you, Mr. Millan. I really enjoyed your show. For a while there I thought I was back on the Campbell. Chief, truth is stranger than fiction. I read that you men contacted six subs in 12 hours. That must have been quite an experience. It was, but that's what we've been trained for and we were ready. I also read that you remmed the last one. Did you get any of the others? Well, I can't say definitely. Personally, we on the Campbell feel that more than one of the subs will never get back to Jimmy. Well, good for you. I judge by those ribbons you're wearing that you've gotten around quite a lot. Well, during the past eight years, I've been on the Coast Guard. I've done quite a bit of traveling. In fact, during wartime, wherever the Navy goes, we go. And that included landing marines on Guadalcanal and Casablanca. Well, thank you, Chief Causton, and the best of luck and good hunting. Be with us again next Monday when Cavalcade presents a week from tomorrow, April 13th, and throughout the United States and in every country in the world where the democratic way of life prevails, the birthday of Thomas Jefferson will be celebrated. In special observance of the occasion, Cavalcade will present a new radio play, The Lengthening Shadow, in tribute to Jefferson. Our star will be Frederick March. Be with us next Monday when Cavalcade presents Frederick March as Thomas Jefferson in a new radio play, The Lengthening Shadow. The orchestra and musical score on tonight's program were under the direction of Don Burry. Cavalcade is pleased to inform its listeners that tonight's star, Ray Millan, will soon be seen in the Paramount picture, Lady in the Dark. You've done your bit. Now do your best. If you are not investing 10% of your wages or salary in war bonds, now is the time to start. America's second war loan starts in one week.  This is Clayton Collier, sending best wishes from Cavalcade sponsor the DuPont Company of Wilmington, Delaware. The program came due from New York, the National Broadcasting Company.


Let's go through model creation using Keras part. So this part of the activity covers six steps. Please do not mix those six particular steps with the five-step, five-generic steps of mentioned in previous part. So those six steps are related only to the model creation in Keras. So what should we do? We should gather the data, collect the data. We're going to build the learning dataset. And today we'll build the model of audiosync classification neural network. So to do that we'll use public dataset. So having the raw audio learning dataset we need to prepare the data. We need to do some digital signal processing. I will explain later on the details. But in general we need to frame the audio signal. Then the second step of preprocessing it will be log mal spectrogram. I will also explain the details later on. Then having the ready dataset, learning dataset, we'll be able to build the model. So this is the fourth step to build the model in Keras library. The fifth step is to train the model. So the core activity in fact of this part. And then evaluate the model by evaluation. I mean the testing of the model accuracy against new unknown data so called test dataset. We are building audiosync classification application. So as an input we have time domain signal. We have just raw audio signal. What can we do? We can transform the time domain signal into frequency domain signal. It means the frequency domain means that we will build the spectrograms based on input time domain, raw audio signal. What is the spectrogram? Spectrogram is just a picture. So what is the conclusion? We can use the well-known structure of neural network for the picture recognition. It is convolutional neural network to recognize the audio scene. Why? Because we have transformed the audio, the time domain signal to the picture, to the frequency domain signal. So this is our signal transformation flow, time domain, frequency domain. Then picture as input data for the convolutional neural network. And then three classes to be classified. Indoor, outdoor and in-vehicle. What about the learning dataset? We will use as I said before, we will use the public dataset. It is dataset collected by Helsinki University. It is 20 gigabytes of raw data composed of 30 seconds long, let's say atomic recordings. And they have recorded bigger number of audio scenes, acoustic scenes, they recorded 15 scenes. We need to have in mind that our micro is limited in terms of computational power. So we decided to decrease the number of acoustic scenes down to three classes. Indoor, outdoor, in-vehicle. And we also decided to decrease the sampling rate from 44.1 kHz down to 16 kHz. Decrease the mode of recording from stereo to mono. And decrease the accuracy of the recordings from 30 to 24 bits integers to single precision floating point. Okay, our tool to build the model, it is the Python source code. The Python is a basic stuff in this case. And I have a general remark. Now please do not analyze line by line the Python code. It doesn't make sense. You can do it later on. My goal, my idea is to show you the flow of the development chain. So as a first step to build the learning data set, we are downloading the raw audio data set from the public location here. We are doing it using Python code. As the output, as the result of this download process, we have 1,170 30 seconds long segments as a development samples. And we have 390 30 seconds long segments of the evaluation samples. A lot of data. Okay, the data preparation. What should we do now? To perform the data preparation, at least the basic, what I would say the medium data signal processing knowledge is needed. This practice, the framing of the signal is well known to the DSP experts. So the first step of the data preparation is to frame the signal. So we need to slice the 30 seconds long atomic recording into overlapping 64 milliseconds long frames. This is the basic frame here, the yellow one, 30 is 64 milliseconds long. Why 64 milliseconds long? It was the arbitraried decision of the DSP expert based on his experience. And here is the second overlapping window. The overlapping ratio is 50%. So the half of the frame overlaps the previous frame. Maybe I will show you the numbers. As you can see here, we have 30 seconds long atomic recording. And we decide to slice this atomic recording into frames 64 milliseconds long. So 30 seconds divided by 0.064 seconds. It is 468. Let's take the integer part of the result only. So we have 468, 64 milliseconds long frames. But the frames overlaps with the ratio of 50%. So we need to multiply this integer part by 2, because of 50% of overlap ratio. So 468, 468 multiplied by 2. It is, as a final result, 936 frames. Each frame consists of 1,024 ADC samples. Just to remind you, our sampling frequency is 16 kHz. The goal of the overlapping is to avoid the boundary discontinuity during FFT transformation. So this is another more detailed explanation of the framing. Here we have 32, 64 milliseconds long samples. What does it mean? As you know from the previous slide, the frame length is 64 milliseconds. And the overlap ratio is 50%. So we have 64 milliseconds divided by 2. The stride is 32 milliseconds long. And again, because of arbitrary decision of the DSP expert, we decide to slice the 30 seconds long atomic recording into 1 second long parts. So 1 second is the equivalent of the 1 picture. Why 1 second? Because we have 32 frames. So the stride time is 0.032 multiplied by 32. It is 1 second 0.024. So here we have time and the frequency. So this is the spectrogram of 1 second long audio recording. In fact, to be more precise, 1 second 0.024. So the x-axis it is a time, y-axis it is the frequency. And the color of this FFT spectrogram corresponds to the magnitude of the audio signal. So this is the framing. And as a result, we can perform FFT. This picture has one disadvantage. The useful signal is only present on the small area of the picture. So let's consider, let's think how to magnify this area, which for sure increased the accuracy of the neural network in terms of the picture recognition. So just to remind you, we are building an audio-steam classification and we want to mimic the human perception of the audio-steam classification. This is the goal. So we need to implement all the human-audition system mechanism, biological mechanism. Our perception of the magnitude of the signal, of the audio signal is logarithmic. But also the reception, our human reception of the pitch of the signal is logarithmic. So we are much better in differentiation between the frequency difference of the lower frequency than between the difference of higher frequency. This chart shows this feature. The equation has been developed by scientists, the laboratories. So this equation is taken from the practice. This kind of mathematical approximation of the phenomenon. And here you can see. Let's take the frequency difference between 300 Hz and 500 Hz. So our perception of this difference is much better than the perception of the same, in fact, difference 200 Hz between 3.2 kHz and 3.4 kHz. And we can reuse this relation, this chart, as a kind of magnifier glass to magnify this area on the picture. We can approximate the curve, but by set of filters, triangles shape and we saw called the set of filters, the male filter bank. So one filter here, the second filter here, etc. Just to approximate this curve. So again, we have row signal. Then we are framing the signal to perform the good quality FFT to avoid frames boundary discontinuity problems. Then we have male filter bank taken to approximate the logarithmic characteristic of the pitch perception. Then we can present the result in logarithmic scale. And as a result, we have quite nice picture. So this is the, this picture corresponds to this area and consists of much more useful information than the row FFT. So as a result, we have set of 1.024 seconds long pictures and this is the Python code to prepare those pictures. So just to remind you, we have set of recordings, 30 seconds long atomic recordings and each of the 30 second long row audio recording is transformed to the frequency domain and as a result of this transformation we have 29 pictures. So the 30 seconds long atomic recording is represented as 29 spectrograms. While 29, each spectrogram covers 1.024 seconds long recording. So we need to divide the atomic recording, 30 seconds long, by 1.024 So as a result we have 29, of course we need to take only the integer part so we have 29 pictures. And as final result of this preprocessing code we have 33k, almost 34k pictures of the 32 pixels resolutions. Okay, the next step is after the preparation of the input of the learning dataset is quite technical because the picture, it is the input to our neural network but we know what this picture represents. For example, this picture, this particular picture represents the outdoor audio scene. So this is our ground true data. Let's say picture number n represents the class number m. We have three classes starting and we can assign to each class the number starting from 0. So let's say 0 means indoor, 1 means outdoor, 2 means in vehicle and because we have a lot of pictures, let's consider the development dataset 34k of pictures. This is our input data and we have output data, expected result of the neural network ground. So this is the vector. So we have 34k items vector long. And the technical because Keras expects us to provide the binary matrix instead of a vector we need to transform the vector to the matrix. So this is technical operation. The next technical step is to standardization. This is the mathematical operation. The goal is to remove the mean and scale the input data variance to the unit variance. Why? Because we want to avoid the saturation during MCU data processing. So the standardizing of the data. Okay, this slide is important to catch the generic idea of the neural network and the learning dataset. So to learn the neural network, we need a dataset. But as you have seen, for example, on this slide, we have two datasets. Development dataset and this dataset is bigger and the evaluation dataset or test dataset. And this dataset size is lower than the development dataset. And what is behind? So the general learning dataset, the development dataset as a subset one evaluation dataset as a subset number two. So the development dataset taking the school example is the material for the lecture. So we have the lecture and after the let's say the school period, we have the kind of validation test. But what is the main feature of this period test that the material is known? Because the teacher said the pupils that during the test will go through the already learned material. The evaluation data the subset number two is used for testing the neural network. And the main feature of the evaluation dataset is that this evaluation dataset has not been presented to the neural network. During the development, during the learning, so the evaluation dataset. It is the equivalent of the final study exam for final university exam. So the questions are or should be not known to the pupil during the final exam. The subset is split into two parts, the test data itself and the partial test. The size of partial test is much lower than the final test because of practical reasons. For example, let's consider the test of the microcontroller of the neural network running on the top of the microcontroller and virtual comport as a channel to provide input data to the neural network. The virtual comport over the of course over the USB channel, the band of the USB is limited. It would be not so much practical to send gigabytes of data using USB. That's why we can define the partial test say few megabytes, several megabytes and use USB to test the neural network. Okay, it was general explanation and this slide shows the Python code which splits the dataset into development and test and validation. And partial test datasets. So for the training for the development dataset, we have 25 k of pictures for the validation. So just to remind you the validation means the end of the school period exam. This about 80 k pictures. The final school exam, the evaluation of the neural network dataset consists of 11 k of pictures and the partial data test sample consists of 114 pictures because we will use USB as a communication channel and just because of practical reason we need to limit the amount of data. And what is very nice for Python and Keras, this quite complex operation is done using only one line of source code here. So now we have the preprocessing of data. We prepare the development and evaluation datasets and now it's time to the I would say core activity to build the neural network model. Because in fact we are recognizing pictures, we will use well-known structure of the neural network for the picture recognition. It is convolutional neural network. And again, you can see the big advantage of the Keras library because we need to use only one line to build or to define each layer of the neural network. As a first line, we are defining the type of the model. It will be sequential. It means that we are defining layer by layer of the neural network. So first layer is a convolutional 2D layer. The second layer is a max pooling. Again, convolutional 2D max pooling. Then we need to flatten the data to fit the dense layer. And next point is the definition of the dense layer of the brain of our neural network. And the output layer consists of three elements because we have three classes indoor, outdoor and in vehicle. This is different representation of the graphical representation of the neural network. This is another representation of the same neural network. This is the representation of the neural network generated by Python script. And here is a basic explanation of convolutional layer. Convolutional layer is just kind of digital filter. Very basic one, as you can see on this picture. So let's consider 2D input for the neural network, 2D matrix with the numbers. And for the convolution filter we need to define the window of kernel size. In our case kernel size 2 by 2. And stride value or step moving filter step value. So in our case stride value is one by one. So we are moving one field in the direction of the matrix. And what is the operation behind? Let's consider this green area. We need to take the input value multiplied by the weight of the corresponding neuron input. So 8 multiplied by 0.5, 10 multiplied by 0.1, 3 multiplied by 0.2, 15 multiplied by 0.8. Then some accumulate all the values and as a result we have 17.6. Here is another representation. This is I would say analog representation of the operation. Here is a more digital representation. Just to simplify the picture I assume that all the weights are the same and equal to 0.5. So as a result we decrease the amount of data. This is in fact the main goal, the main feature of the convolution layer filter to decrease the amount of data. The max pooling layer, the explanation is similar. The idea is even more simple. So again we have moving window of stride value. And we need to just find the maximum value within the moving window. So for example for this window we have 15, for the magenta one we have 9, for the green one we have 8. And again the amount of data is decreased. And for example this filter is very good to detect the edges of some shape. And the fully connected layer, the dense layer, here it is the brain of the neural network. Okay, the training process. So having the learning data set, having the neural network structure we can start the training process. And again this is only the one line using Keras and Python. Before we need to select the optimizer and compile the model. As a result we are getting the loss function. So I think I should explain the loss function which shows us the quality of the learning process. Of course the lower losses, the better result of the neural network learning process. We need to back to the school at least for a minute. And the basic idea behind the loss function is a gradient. What is a gradient? Gradient points to the direction of the fastest function increase. So using the gradient we can find the maximum of the function. But just to be more clear, gradient doesn't point to the maximum of the function. Gradient points the direction to the maximum of the function. So let's consider the very simple free variables function like here. And the gradient of this function, it is a set of the unit derivatives of the function. So df by dx, df by dy, df by dz. Let's evaluate the partial derivatives. So df by dx of 2 multiplied by x, it is 2. df by dy, it is 2, 2y. df by dz, it is 3 z power of 2. And let's consider the starting point coordinates to find the maximum of the function. Let's assume that we start from the coordinates x, y equal 1, y equal 2, z equal 3. So this is our starting point in the 3D space. So we can plug in current coordinates into the gradient. You can see here. And evaluate the point, another point in the space, 2, 4, 27. So the maximum of the function starting from this point in the space, in this space, is in this direction. So we need to draw the line between the starting point and the end point. And this is the direction. Again, just to highlight, this is not the point of the maximum of the function. This is the direction of the maximum of the function. And now the really basic question is, how long should we go in this direction to find the maximum of the function? We can go the small step and then add the maximum of the function. We can go the small step and then evaluate the next direction using the gradient again. We can go the medium step and evaluate the gradient, the direction again. We can go the big step and evaluate the direction. Why it is so important? Because we can just overlook the maximum of the function. So it was the gradient explanation. And now let's come back to the loss function. So what is loss function? Loss function maps the values of one or more variables. In our case, it will be neural network weights and biases. So really a lot of variables, sometimes billions of variables, onto a real number, one real number, which represents some cost associated with those values. And our goal is to minimize the loss function. So on the previous slide, we have discussed the very simple function of free variables. In our case, we have function, neural network weights and biases. It could be even billions of variables. So really demanding in terms of the computation power. Okay, so the gradient points the direction of the fastest function increase. So it can be used to find the maximum of the function. What about the minimum of the function? We need to use the negative of the gradient. The gradient descent approach to find the minimum of the function. So exactly the negative approach of this basic rule. So we should go not in this direction to find the maximum. We should go to the opposite direction to find the minimum of the function. And again, the absolutely the basic question is about the step when trying to find the minimum of the function. Because if the step is too big for the big step of the gradient, the state is possible that we will never converge for the small gradient descent step. For sure we will converge, we will find the minimum, but the time needed for the computation will be really huge like days or weeks. Okay, how to evaluate the model? How to build the metric of the model? So the I would say most intuitive one metric is the accuracy. And the accuracy represents the ratio between the evaluation of the model metrics. The most basic one metrics is just accuracy. You can see here the example 0.89. What does it mean? It means that for 89% of inferences the result was proper. So 11% of the queries to the neural network, for 11% of the queries to the neural network the result of the inference was bad. The test loss represents the error during the learning process. The quality, in fact, the quality of the learning process and the lower test loss is the better quality of the neural network learning and in fact the better accuracy. The test accuracy is quite a generic number. It is kind of overview of neural network behavior and we cannot see the class-wise errors. But there is another metrics, so-called confusion metrics and for this metrics we can see the quality of the accuracy of the neural network class-wise. So as you remember we have three classes to classify indoor, outdoor and in-vehicle. And the size of the metrics you can see here is 3x3. So because of the number of classes. So here you can see that for class 0 it is the indoor class. The neural network inference results is 0.99. It means that if the neural network was fitted, the picture represents the indoor spectrogram, for 99% of the cases the inference result was proper. For 1% of the cases neural network mixed the indoor class with in-vehicle class. The same for the outdoor class, so 98% proper inferences. The neural network mixed the outdoor with indoor class for 1% and mixed in-vehicle with outdoor class for 1%. And for in-vehicle for 100% the result was OK. So this accuracy here is a little bit different than the overall accuracy here because it is just a mean of the diagonal of the metrics here. So it is 0.99. How it is done with XQBI, the confusion matrix evaluation process. So we have custom data, for example in CSV file. Then we fit the generated C model with those custom data. Then we have expected output. Grants true, so we know what we should expect. And there is a dedicated Python script to evaluate process the confusion matrix. I mentioned here the CSV file, so it is more technical slide showing that using Python code we can generate all the data sets, both the input data set as output data set in CSV format using Python script.


What's up everybody, Jason here for Jaspys, KSpricks.com. Excuse me. 2032 Playbook, pick your team number 12, so I was out with this 17-team R&B here. And again, guys, so none of these teams sold, so we put them all together, divided them up into 10 spots, and you get a piece of all these 17 teams via a random number block. So, of course, it's a serial number break. We go by the first number, the left side, the serial number dash. Just remember, any and all redemptions go to spot 0. If there's non-numbered cards, we'll randomize them to the group later at the end of the break. And, yeah, a lot of good teams in here, guys. So, of course, here's a dice related to customer names, numbers, and then here are the 17 teams that everybody gets a piece of, to get a piece of all those teams of any of those teams hit. We'll see who gets them by with a serial number, of course. So, let's dice roll it, and we got ourselves a three to two, five times. Good luck. One, two, three, four, five. Five times, three to two, five. So, Eric down to Eric. And again, just your names in there. Now, let's go numbers. Zero, one, two, three, four, five, seven, eight, nine. One, two, three, four, five. Five times, five, five, zero, down to three. All right. So, Eric, you have spot zero. Michael with nine, Carl with eight. Michael with two, four, and one. Carl with five, six, seven, and then Eric with three. So, again, guys, these teams here are just there for the sorting team. Let's just put these numbered. And then, of course, here are the teams, like I said, that are part of the break. So, appreciate it, folks. Coming up next is the break itself.


Welcome traders, it's not a techno chart, it's me Patrick Munley, once drew attention to the Aussie Kiwi on the daily timeframe, we've completed an equality objective versus the swing structure here, the 108-13 high had 104.67 as the target, we've also run into this support zone at 104.19, getting a nice outside reversal candle today, so what I'm looking for is a strong close, I want to see this candle close in the top third of today's range, set long positions through whatever our high is today to ultimately see a three-way corrective move, test up into monthly range resistance, 106.46, descending trendline resistance, 106.65 and the 61.8% of the tracement of the last leg to the downside, 106.64. As always traders, plan the trade, trade the plan and most importantly manage your risk. Until next time, thanks very much.


I'm back. And now we're going to talk about translation. Now we're going to take the little messenger RNA molecule we just made through the process of transcription, and we're going to talk about how we are going to use that information to build ourselves a protein in the cytoplasm using the ribosome, woof woof. Before we do this, hopefully you are wondering, okay, how is it possible that the messenger RNA even contains information? How does DNA contain information at all? And it contains information in the genetic code. And the genetic code is something that took a significant chunk of time to figure out. But once we figured it out, almost every critter on the planet goes through the process of translation using the same code. That alone kind of blows my brain. So let's take a look at what is this genetic code you speak of.


Starting so I'm actually Everybody's watching them I think we are believe it or not. We are only a stone throw away. So this is not in France Okay, maybe it's New York. It's New York cap over there. Oh, this is so cool. I feel like I'm in the subway. It's And it's video. So this is awesome. So So who are you hi, my name is Matthew so we involved in this Mask virtual retinas for the last year so that you put Galaxy S5 We use this one is a S4, but we can also use any any other good smartphone Choose a full HD screen so any good smartphone So actually I was looking at a 3d video Yeah, it's more than 360 video Because it's very cold video. So you can look all around even Okay, left and right and also Down so that there's one for each eye, but is it the same video is it 3d 3d 3d? Um, actually this one is a 360 video. Okay, it's 2d. It's 2d, but we also could make the 3d video 360 3d video If I show you we are using six GoPro to make this movie, but we could use 12 GoPro and so we have the binocular vision each side So you are ecodis and you're doing the homido. Yeah, the ecodis is just the head of this Homido is this is your product So So How soon is this on the market this product? We're rush for the fair we were ready October 10. I still have some last detail 200 like the form I'm not fully satisfied So I will fix this issue before end of October and I hope to be ready early November for Deliver the first batch of where you from? I'm from France and working in China. So 50% France 50% China. So the company is French or no? Chinese French So you got a master manufacturer this in China affordable This part optics is from Taiwan So we use a spherical lens We met the tooling in Taiwan and the injection in Hongzhou in the northern China and all of the part we do in Ningbo Very near to our office. So yes in manufacturing in China and the design was made in the French office All right, and what's this? This is some comfort adjustment like If you feel too close to the lens, you can add just think of some girls. They have the very long eyelash Yeah, they like to adjust a little and feel not so close put it further away because we are using Different kind of cups. Let me see there so that you have different ones. Yeah So we have the big one Fast sight Normal vision and also Let me see the small one So we can we can adjust Equality is really good.  We are only five people and they have two billion dollars. You don't have to be Yeah, not two billion. Yeah So what is the price? So the retail price will send the homido homido brand for Europe market is 69 euro retail price for US market 89 89 dollar for real How soon we hope to ship Mid of November will she buy air so I'm not sure we'll catch the Christmas season, but Yes for Christmas Some like link to ways for people to make the 360 videos there is this solution right here, which is pretty awesome But this is a high-end high high. Yeah, this is not a consumer Well, many manufacturing will show the 360 open give the 360 camcorder to the market very soon This one we just use six GoPro Put it all together with the holder and there's a there's a tripod. There's a yeah, there's a stand here So you just put it on a tripod. Yeah, so then we record six different movie And we will stitch it all together and make one movie So there's a company doing this This this adapter here. Yeah, this is American company. You can buy a 360 or you check online But this is I think this is professional professional matter because this is about 500 euro and we know some company They are already doing 360 cam very good at this similar price 500 euro 500 euro for the whole 360 Yeah, all 360 you even can find some company Chinese company in the fair in this fair I think there's a couple of companies are already selling the 360 cam around the 500 euro But 360 with six cameras? No 360 with three cameras, and I see another one 360 with two cameras like in like this But the huge lens. Yeah. Yeah, yeah So 360 video is we're gonna be more popular than 360 gaming, right? No, no, no, we have some pretty good games and more and more games Coming to the market because This is a Google company You heard about the cardboard. Yeah. Yeah, so this is a car. We are also manufacturing some cardboard This is just cardboard. This is just cardboard But the camera is very important to us because it will bring more and more developer to make the new games for virtual reality. So hopefully Google Start this project So here the at the Hong Kong fair you looking for partners distribute? Yeah, because we met the hardware and We also made some software So the last key to success is make the good promotion. So what's your software? We we met the apps 360 video player And we are working with developer to make bring more games And also we can use all the existing games from the Google player Apple store so the hardware is ready the software is ready not so much But we will make more and now we are looking for good distributor to make the very big promotion This is the last key to success nice So the French company who did the 360 video camera with three cameras is a neighbor for me. Yeah Yeah, we live in the same city Yeah, the city they were very successful on the Kickstarter like more than 4,000 Guys are bought from the internet and totally the two million euro. It's quite a big success. The name is a 360 cam from Geo optic, so how many are you gonna sell of this? What's your target? Actually we are talking some Some shops that just order like 100 200, but we are also talking with some telecom company They plan to sell 10% of the whole Sell of smartphone for example one markets get a one One million smartphone per year, so they plan 100,000 Heatset here just for one one market like Spain what is homey dough? What is the name come from?  Ah cool, and which which phone support is supported here? Which size? Yeah, so you can adapt or no no From four inch screen to five point three. It's working very nice. We recommend the best sizes of five inch Actually, I have to make more test because just yesterday night One guy came with her last iPhone 6 6 plus yeah, this 5 from 5 and it works very good Yeah, how about six inch too big now six inches to be I think we'll make a new headset for the phablet Trimmer set up, but I also try some Chinese Chinese mobile phone the 5.5 inch it was Not so good, so we have to try more you can get the compatibilities and and this is the bag is included for the price This is a game and maybe I show you try game so he said come One good set one extra straps. It's more comfortable. I'll show you Well if you use for more than you know How else you like to feel more comfortable? So it will give more balance on your head, and then you have three set of cups But For a start we will supply only one pair of lens and only Supply the cup order and you have to change the lens by yourself We use this lens if you have if you use some glasses, then you can from your pick all the Well, this one is this one for normal guy and this one for the old people So it's not possible to adjust exactly the Focus no, but because we tried some HMD before and we don't like the adjusting by our side because it's quite hard to get the right focus So we we design this for myopic ministry. This is normal so far We I think over 80% of it was very clear for me. Which one was I using you use this one? Yeah, okay, so this is for normal people or crazy people. Yeah, and this is a this is a lens we use this is a Spherical lens be convinced as vehicle lens We made some from plastic some from glass and finally the result was very similar actually exactly the same reason so we keep the PMMA plastic glass Yeah, and Just put it on the holder and so the lens is really important that it's good quality. Yes. Yes Let me show you here like this one is another lens We open because while while we were developing We need to test many kind of land. So this one is pretty powerful pretty good or so, but we also in the invest in the Frenel, this is another kind of lens But we cannot get the result we want and also this kind of lens It's just a big convex, but the distortion was too big So finally we came up with this with this one is the best lens we have so far and we are still developing Researching with a Hongzhou University. So maybe we can come with a better lens in some months So there could be a lens options in the future. Yeah, just developing. This is our v1 Our first item, but we know we have to make it even better So I hope in next april you can come back here and I have a v2 even better than this one And this is a new media, right? There's 4k, which is cool, but this is new thing Um, sorry, what do you mean? I mean, this is like a this is a new way to experience Yeah, yeah, yeah, it's very special Yeah, the gaming so the gamer they already know us because we are many people have heard about their curious, but we want to bring more Not only surprise the hardware, but also doing some a new way to Do the things like we think in the future before you go someplace you can look at it Um, also enjoy the movie in the train your personal movie We also have one One idea is For the x the sex movie it will be very Very hot because we can give something never seen before the full immersive experience So we also target the big market too. Yeah, but I think personal videos That's gonna be interesting like you get your own camera you film your own event and you really live The same event again and again You can feel like inside 10 times a read of time It's never the same and this is what you need for personal movie videos for family Yeah, like you want to be there you you record the movie and then you can Show to your family and they really can have the feeling of where you were and they can watch again and again And that's what families do and we hope there is some platform Website where you can put all your 360 degree video and it's easy to show Yeah, they will support it. No so far. We have the one issue is the 360 video is a 3 mb Per second, so you need a very high the very high Right, even google have enough bandwidth. Yeah, yeah, we'll send them new Okay


With regards to the administration's empty promises about climate change... No more empty promises!   Why would I?  I'm not giving it to you. It's the principal ingredient, my rat burgers. Look, that authenticity is the main ingredient to dreams. And you're going to have to give me a lot more than empty promises about climate change if you want one of my rat burgers. This is a rat burger.  Not bad. As a matter of fact, this is the best burger I've had in years.


This is stock number 10320. We are here at Summit Automotive in Fond du Lac, Wisconsin. You're new and used SEV headquarters. Today we are checking out this super clean 2016 Chevy Suburban LTZ. This vehicle has the 5.3 liter V8 motor. From this HD video, you will be able to tell that this Suburban is extremely clean all the way around inside and out. It is an LTZ tungsten Metallic is the color we shoot all of our videos in 1080p So if you have HD capabilities on your computer tablet or smartphone device turn them on right now because it is like you're right here looking at the vehicle with me and Definitely your best way to check out the vehicle before seeing it in person comes with the 20 inch I'm sorry the 22 inch painted alloy rims with the chrome pockets Michelin Defender 285 45 R 22 tires with just about all the tread left I'd say 80 to 90 percent of the tread left on there didn't see any denser dings on that front fender projector lamp headlamps front bumper parking sensors No dense dings or cracks on that front bumper the grill is an excellent condition I didn't see any denser dings on the hood Passenger side fender is an excellent shape as well and the passenger side rim no scuffs or scrapes on that As you go down this side of the vehicle you can see just how clean the body is how reflective and mirror like that paint is We take these HD videos So if you are far away or even if you're close by and just cannot make the trip down You can still see the vehicle hear the vehicle and have confidence in what you're looking at before you even get here Down the passengers side one more time very very clean didn't see any denser dings on those doors factory running boards Back rims and pretty nice condition got one tiny little scuff at the top there Back tires have just as much tread as the front tires As we come around to the back of the vehicle the rear bumper is in excellent shape No dense or dings or scuffs on that has the backup parking sensors The rear gate is an excellent condition you get a really good idea of that tungsten color And this is a power lift gate. You can see it does have that receiver hitch seven pin wiring and the receiver hitch Does have the cover for that receiver hitch and those seats are powerful down I'm always amazed at how fast those seats go down and how fast they come up as well Really cool Nice storage area back here nice and clean and you get a little bit more storage underneath there to close this rear gate Just press this button right here, and then that glass that flipper glass goes up as well Down this side of the vehicle just as clean as that passenger side No denser dings or scuffs on this rear quarter and for full disclosure this back rim is in excellent shape as well Paint is very mirror like really nice condition Built-in directional signals blind spot monitoring believe these mirrors are power fold-in as well They are and go like that and out our windows power locks power mirrors memory driver seat bows premium sound system The LTZ package gives you the black leather interior. There are no rips or tears on these seats Really nice condition factory floor mats throughout auto headlamps turned dial four-wheel drive Stability control power pedals your lane departure warning you can turn those parking sensors off your power tilt and telescopic steering wheel and this suburban has 76,325 miles on it instrument cluster is very nice and clean comes with a heated leather wrap steering wheel Bluetooth and information center controls on the right cruise controls and heated steering wheel controls on the left as well as your forward collision warning Controls this one also has the factory navigation System in it This is also where your backup camera shows up AM FM and Sirius XM radio capabilities and this radio actually goes up like that for a storage bin There's a USB port in there to charge. I say you want to charge your phone, but keep it out of sight Dual climate controls down here as well as all your other climate controls You also have your heated seats cooled seat buttons on here as well Finally this one has the projection system so you can Hook your phone up and project your Apple CarPlay or Android Auto on there Passenger seat is very clean as well. This suburban smells very clean I don't think it's ever been smoked in has the power sunroof This one pretty much has just about every option you could get Home link buttons for your garage door security systems and lighting systems your map lights on star capabilities And finally it does have the wireless cell phone charge pad right there as well We'll take a quick look at the back seats, and then we will check out under the hood Back seats are just as clean as the front seats You do get the heated quad seating back here the captain's chairs. No rips or tears on those seats Very very nice and clean does have the latch child safety system for your car seats Child car seats rear air and audio controls you get a power point back here as well Well, it's 110 volt 150 watt, and then you get the dual Blu-ray players back here as well Which is a really nice feature if you got kids And the third row seats and very clean as well no rips or tears back here And we'll take a quick look under the hood I would personally like to thank you for checking out the video today. Hopefully from this HD video You will have been able to tell just how clean this Suburban is all the way around inside and out under the hood. We have the 5.3 liter V8 motor engine bay is very clean runs very smooth The suburban has been fully safe deed and inspected by our service shop has a fresh oil and filter change All the fluids have been checked and topped off The vehicle has been gone through mechanically 100% has like new tires on it and is 100% ready to go See more pictures of this suburban or one of our other 450 new and used cars trucks SUVs mini vans Wranglers half tons three quarter tons one tons you name it We got it go to our website www.summitauto.com full pictures and descriptions of every single vehicle from two locations all at summit auto.com And if you'd like to check out more HD videos you can go to youtube.com So I have some at auto remember to like subscribe and share on this video and all the videos that you see there In fact in a second you will see a link to subscribe to our YouTube channel on your left It links more used inventory videos like this one on your right If you have not been to our website on the bottom link to this vehicle on our website click those check us out And we really look forward to helping with this super clean 2016 Chevy Suburban LTZ. Thanks again


No one is going to tell you this about the narcissist. YouTubers are not going to tell you this. Life coaches and therapists are not going to tell you this. Even your family and friends are not going to tell you. And it's not always because they don't know. It may be to suit their own agenda. Or maybe they're just trying to protect you. But I decided to create this video. Because I believe you have the right to know. There is something that you need to know about the narcissist. You deserve to know the truth. And the truth is that you're really not that significant to the narcissist. You're not as important to them as you might think. As they may have led you to believe. It's an illusion of significance and importance.  You had a possessional purpose. You meant something to them. But it's an illusion. It gave you a deceptive appearance and impression. They planted a false idea and belief in your mind. You are never going to be anything important to the narcissist. Because they see you as something temporary. As something they're not going to need for very long. As something that's only going to last for a short time. It may have seemed like they were excited about you in the beginning. But it's like a child on their shiny new toy. When they first get it they want to play with it every day. But after some time they get bored with it. They don't want to play with it anymore. They neglect it. Because it no longer has the same effect on them. It no longer excites them. And it's the same thing with the narcissist. You're not significant to them. You're not special or important. Which is why their interest in you gradually fades away. It doesn't last long. They're always thinking about something else. They're concerned with other things more than they're concerned with you. Because they have short attention spans and they're easily distracted. They can't focus on one thing for a long period of time. They get bored. Because after some time it no longer has the same effect on them. It no longer gives them supply. But when you first met them they were excited. And in that moment you were important to them. But after some time it dies out. It fades away. They no longer feel that same way about you. They treat other people far better than they treat you. They always treat the people closest to them the worst. Because they don't value anything they have. They take people for granted. They see you as something expendable. As something that they can easily replace. Because you're not important to them. You're not special. They're used to you now. They're bored of you. And that is when they feel like they can easily replace you. Without any concern for you. And they're always looking for your replacement. But even if they stayed with you for a long period of time. That doesn't mean they were faithful. They were never exclusive to you. They always had someone else that they were talking to. They always had someone else on the side. They need to have multiple relationships at one time. Because they're addicted to people. They can't live without constant attention and admiration. So you were never significant to them. You were never the only one. And this is what people are not going to tell you. But you need to realize this because it's the truth. You weren't. But you thought it was real. You thought they were exclusive to you. But they were never exclusive. You shared them with other people the entire time. You shared their time. You shared their attention. You shared their love and affection. Because you were not special to them. And no one will ever be special to the narcissist. Because they don't value people. They value what you can do for them. They value how you can make them feel. All that matters to the narcissist is what you're giving to them. If you really matter to a person. They're going to be considerate of you. They're going to be careful not to inconvenience or harm you. They're going to be attentive and thoughtful. They're going to show kind awareness and regard for your feelings and circumstances. That's one of the main signs you matter to someone. If they're not considerate of you. That should tell you they don't have your best interests in mind. You also need to look at their emotional maturity. You need to look at how they respond to certain situations. Because narcissists don't like to talk about anything deep. They don't like to talk about problems. They'd rather brush it under the rug and forget about it. Because it's not important to them. You're not important to them. And no one is going to tell you this. But this is what you need to know. Thank you for watching. I hope this video resonates with you. Please like, comment, share and subscribe. If you would like to donate, my PayPal link is in the video description. Coaching Inquiries, you can email me at coaching.ncfivert.uk Thank you for watching and I'll talk to you soon.


The resulting protolignin contains high levels of beta-04 structures, which are important structural elements of lignin. Additionally, this process does not require any additional solvents or chemicals, making it more environmentally friendly than other methods. The team also scaled up their process to produce kilograms of protolignin, demonstrating its viability for industrial applications. This article was offered by Wuhan Lu, Shinyue Sun, Yan Yan Yu, and others.