some more information about myself. Yeah, I'm Naveen Mamgain and working with Relya 3. It's a startup and it aims to simplify the train travel of India. We also use deep analytics technology to predict intelligent information. Intelligent information means if you have booked the ticket, you have the PNR but if it's in waiting list, so you don't know what the state is going to be. So we use that predictive technology to say, okay, this ticket is going to be confirmed or not. So that kind of information. Design, develop and survive. Survive is the most important part. And you have seen a lot of apps on the app store. So you have to make that competitive. You have to remain in the game. You have to get the installation. So that's why you'll be in the market. I just want to know how many of you are from startups? Okay, and how many of you start any startup? And especially if you have the solution of mobile application. It's around the train travel. And we simplify the train travel. Like you have booked the tickets. And again, I have told you about the conference probability all. And at the same time, you have booked the ticket and you don't know at what time you have to go to the station because you don't know the estimated time arrival of the train. It can be late. It can be early. So we predict that kind of information also. So you can plan your travel better. And we have also do the categorization of travelers. Like someone is short distance traveler. Someone is long distance traveler. So we have to cater those needs also.  We have other services as well. We have the commerce pieces. Like if you're going from Delhi to Bangalore. Okay, your route is long. So we can provide other information as well. And the services like food. We can deliver the food on the train. So and you are going to Bangalore. Definitely you need some hotels and all that kind of services we cater. So that's what we have done in the area three. And yeah, it's a start of we are also learning. We are, you know, doing a lot of experimentation in our company. Sometimes we got the good results and sometimes not. So the purpose of this talk is I want to learn from you guys also. Because definitely I talk about this vertical where we have implemented a lot of ideas, a lot of solutions. So what you can think of in this domain. And if you have already implemented something in the past, so you can share with me. There is the Indian Railways and there is the NTSC who gives the train travel information. We work initially with them. We handle their portal and then we realize, okay, there's a lot of problem which we can solve. So we started with the rail yatra. But it's not the standard ticket booking like you'd see in the IRCTC or in the Yatra make my trip. It's something different. You have to call the agent. They'll book the ticket on your behalf. Because otherwise you have to take the whole ABI from the IRCTC and it's very costly. And being a startup it's not, you know, advisable to put so much of cost initially. Yeah, that's the only product. And imagine, you know, 22 million passengers are travelling daily. Around 12,000 something trains which connect 7,000 of something stations. So the network is very huge. There's a lot of information which's going in and around. So how we can use that information that still we want to crack that idea. Face, I'll tell you before that slide comes. So I have that, my name, my company name and where all I am active in. The LinkedIn, Twitter and Medium where I regularly post the articles. And I keep posting articles till the time users like it. We are providing the content also. It's lifestyle content. Let us suppose some, sometimes back you travelled somewhere. So we have that information and we'll give you the information around that travel. Means you have to get it from the New Delhi. So we'll give you the information around New Delhi. What are the speciality in New Delhi station? What all things you can do here and there. If you want to plan your travel, you have the PNR. So if you give us the PNR, we'll check the status for you, we'll keep you informed about your PNR. If it's confirmed then it's fine. Then we'll give you other information if it's in the waiting list. That's all we want.  You've gotten some idea to solve some problem of users and you think app is the reason. So you publish it. And what if you're not getting the good number of downloads, the number of returning user. It's a matter of concern. It's a matter of concern for the new app because the download is the thing where if users are not seeing your app, they'll not value, they'll not see your product value. Apps, apps and more apps. Nowadays we are surrounded with apps. You just think about something to done and there are hundreds of apps out there. So, you know, the number of apps are available in the app stores is growing each second. Around 45,000 is the approximate number. 45,000 apps are publishing every month in stores, like if you see the application stores. So now companies, developers and the entrepreneurs who are actually in the app business, they also realize that it's not just enough to build the app. You have to make your app very competitive. And at one time, you're seeing, okay, there are a lot of companies, entrepreneurs are publishing their app on the app store. And then the study also shows 80 to 90% of apps are downloaded once and eventually deleted by users. They just see your keyword, they download it and check it and then on. And it all happens within one day. It's the data we also got from the R apps, so R app, it all happens within one day. Because you generally don't get, you don't know how to track the uninstall, but there are ways, there are things, you know, when you send the silent notification and see, okay, this app exists on the platform or not. So, app gets uninstall so quickly they don't have the chance to, you know, showcase the core features. You have put a lot of powerful features in your app, but if user uninstall it within one day, again, you're all efforts are wasted. So, we can't think, we can categorize it to one, the downloads you have to give and the other is you have to avoid the uninstallation. So let's talk about the download part because this part is very interesting. You have published the app, you are very, you know, excited, it is the very exciting time, you know, you have just published it, you are talking about everyone about your app and checking, okay, how many numbers we get, how many reviews people are giving to you. So, that's the most exciting phase and once you've done that, now your app is listed in the app store. And if your app is listed here, it means you have crossed that first level. So, if you just search the keyword, you will get 10s and 20s, 30s, 100s of apps. Now, you have to make sure how to get the attention of the user from the logo, from the heading, from the keyword, rating, whatever. But rating initially, you just launch the app, you'll not have the good rating. Good means enough rating to compel the user. What you have prominent is the app logo. And it's not the app logo, it's the picture which you want to portray. I'll tell you by our example, what we have done, we have our app logo, we have used it in the app store also. So, users are seeing that from the data, we came to know, okay, we are in the page, user are searching us and we are on the page, but we are not getting the installs. What happened, what happened? So, we go to the market, our market is the platforms mostly. So, we go to the platforms, check with user and then we came to know, user are searching us, but then they're seeing, okay, they're not even give the attention to our logo because our logo, what our logo was, it's written on the R-A-I-L and then the Y-A-T-R-I. The same thing, this one, this one was our logo.  So, then we thought, okay, let's change it to the train icon, beautiful like and what we can provide. So, we have done that, but again, it also mixed up with the other things. Like you can see in the I-X-Z-O-I-R-C-T-C, other also have the same thing. So, then we have used the picture and it actually connects with the user. It's been tested with the users and they see they're more related to this picture. Okay, if I want to know something about train information, if this picture is there, they immediately download it because our users are not from, you know, A city, India cities, it's from the India B cities. So, their users, you know, get the attention from the logo and if the logo is especially relating to the real image, it impacts and that's how we get downloaded. Second thing is of course, description and the size description. It's very important because while publishing the app, you should not be, you know, lose enough just write it something and then publish it. Users will read, so many people will read it. So, it's better to have the description and, you know, I have seen one example in the description in the medium. What they have done in the past, they have made it a very beautiful game, word game in their description. So, while downloading that app, you can play with that, play with that game. You can create the, it's a sort of word game. So, it was a beautiful experience, engaging experience also. So, description is also important part and the size. Initially, it's better if you keep it minimum. Less than five MB is of course good because you don't know from where the user is using your app, in what context, somewhere there is no internet connection. So, if your app is less in size, so definitely it increase the prospect to get to download. And once your app is hit, then this size actually doesn't matter because if you see the WhatsApp, earlier it was around 40, 50 MB and now it's 90 MB. But user don't care because now it's a necessity. If you want to communicate with someone, it's good. You have to install it. So, and after sometime I think this information doesn't relevant to anyone because data cost, definitely it will go on low speed, it will get the good speed. So, this information will fail, but presently it matters. It depends on the audience, but it matters. This is the first launch of application. You have launched the application, try to keep it simple, start with your value proposition and then don't explode all the features for the users. You just see, okay, what they are using and then give the information. Try to keep it simple. Suppose you have, you know, search some app from the app store, you have downloaded and this comes. It's actually a door. So, I want to use something, but this application is, you know, creating a door for me. I haven't, I just want to use some information why this one is there. So, that's what the application do. First, create the value. Once user realize the value of your application, they'll give you the login, they'll give you all the information, habits, preferences, everything. But initially, just try to avoid it.  So, that kind of intense you have to avoid. That's what we have done for the first time user experience. This is the utility part for the users. Users come for this information and from the GA, we get to know, okay, what all things they are using. So, we try to experiment with these information. So, these are for the long distance traveler and these for the short distance traveler. So, in the first screen, we almost get all the time, all the kind of travelers. And this is the information which we got from the user. We detected the user location and based on that location, we'll give you, we'll give the user some. Okay, you are in here. There's the nearest station around you. How many kilometers are there? If you want to check the live arrival or something for that station, you can see. And there's the other content card for the announcements. So, first time user experience, yeah, definitely. There is no, see, there is no shortcut formula or the one formula for that. You have to keep experimenting with different ideas and measure the results because that is what makes your application impression correct. This is what we have done with the navigation structure earlier. We have the flat navigation structure. You put our links we have, we just simply put it down. That's what happened earlier stage. And lately we realized, okay, we have to group them. So, there are more screens come in between. I just showed the, you know, third last and the last. So, then we started grouping the navigation based on the categories like, but all we can think in the preferences. Okay, these are the user's area. These are the commerce pieces. These are the trains related to the trains. These are related to the stations. So, those three main categories we have created. And it's working well because we usually we get the feedback from the user what's working, what's not. That's the beauty of the applications. Now, so you have, you got downloaded. You have given the first user experience good. And now the user comes for the second time or you can say it's the repeat user. So, here is your chance to increase the level of user experience from good to excellent, from excellent to delightful. Because you have some information about users. Some recent history, some past history. So, build your intelligence upon them and present it to the user. And definitely user will like it. So, what we have done as I mentioned earlier, you got the P and R status. You know, we got the P and R status from the user. So, we'll build, we'll create. We create the trip of the user. So, we'll tell, okay, how many days to go at what date your travel is, what is your train number, what is the status of your ticket, at which platform the train comes. And now, we see, okay, this is the long distance traveler. How about the food? We can order the food for you also. And again, the location based things. We got the location, so we are creating all the two-minute trips for that. And then the rail wisdoms. This is the important content, actually. It's a crowd-source content. Users will tell us, okay, these things I have seen, how about if I share it and then we'll share it on the behalf of users? So, it's about the interactions because sometimes what we do is we're just so engrossing on the app interaction, we forget the value. So, don't forget your value. What is the core proposition of your application? So, if you have the value, then your UX should be woven around the value of product. So, value is also very important. So, get the download. You have downloaded, you have crossed all the barriers. You have given the first-time user experience and therefore the returning time also. Now you need the engagement because engagement is the key. It's truly a key to the success even. So, you have to engage with users on proper channels, proper time. Like, for that, you have to understand your users. You have to personalize the experience and then give the engagement. Push notification, definitely. It's a very powerful tool if you use it very wisely. And reward points nowadays. So, there are a lot of channels to engage. There's one more thing offline and offline. If you can provide the information offline also, then user need not to depend on the online. So, these are the examples what we have done in the past to get the offline content. And there are other areas to consider. User feedback, analytics, app store, rating and localization. We have a lot to tell you but my time is over. So, I'm here only. We can discuss definitely if you have used some techniques in the past. Thank you guys. Data accuracy, I can tell you in the numbers, but especially when it comes to the lifeline status, we are predicting the EDA. So, we are 75% to 80% characteristic. For delivery, it's in our hand because we have to control the vendor. We know where our user is. So, that's, we are 100% because we have to fulfill the order. But when it comes to the live data, the real time data, where the tree is at this point of time. So, there are, our accuracy is 75% to 80%. We are still editing that to crowdsource content because if everybody is giving us information. What's the number one goal for this answer? Huh? What's the goal? Great. It simplifies the train route. Once you go to the station, there are a lot of things which can confuse you. At which platform it comes, where should I go, at what time the train will come. You, you take the true value. Because I think it's a great example in the station. If you want to know something, you just directly go to the inquiry number. It's flooded, it's flooded with people. People are asking, okay, this, this, that. So, if you ask any question, they'll give you just one answer. They'll not tell you what impact what. Okay. What is the status of the train? This, this train is late. They don't know how many, how many hours are late. And what end up if it impacts you. So, that kind of information building. Definitely it's possible. Actually, what we are doing is the crowdsourcing content. Like, you know, you are traveling. You're traveling from, let's suppose Delhi to Bangalore. So, you have been through all the stations. If your location is on, we can, we can detect, okay, this guy is there. So, we can tell everybody else also. So, that kind of information. So, it mostly depends on the crowdsourcing. And that's what we are working on. True, sorry. No, definitely, we will connect offline also. Thank you. Yeah. Thank you, thank you. So, I would just request Ranjit to give away the token of appreciation to Navin. Okay. We are delighted to have you here, Navin.


Hello friends, I am Ajay Gundalai, Assistant Professor, Department of Electronics, Vulture Institute, Solapur. In this video lecture, friend, we are going to put some focus on the shortest remaining time first algorithm. At the end of this video, we expect all these kind of outcomes that you should be able to describe the working of the shortest remaining time first algorithm. I will shortly call this as a SRTF and then we also try to evaluate the performance of this algorithm. Now, these are the goals of this discussion that is working of this SRTF, then evaluate all this performance of this algorithm and we also have a focus, the different parameters we can use to evaluate the performance of this SRTF. When SRTF is, I will say here, this is a preemptive type of the algorithm that schedules all the process for the execution there. I will also say that this is a preemptive version of a process or algorithm we can say which is called the shortage of first here, because shortage of first is algorithm that uses non preemptive type of the working mechanism. But in the case of SRTF, it is a preemptive type of scrolling mechanism, so that in this case, I can put any process at any instant in the given CPU by interrupting the CPUs ongoing process here. Secondly, this process also uses a mechanism that takes burst time into account here, that is I will select that process which is having small burst time for the execution. So, in this SRTF, initially the CPU will choose that process, in fact OS is going to choose that process which is having the smallest burst time available at that instant here. Now after that, that process is now executed for only one time instant here and again at every end of time instant here, I will again think of all the processes available in the ready queue and I will choose that process which is requiring the less burst time to execute it. So, when here in this mechanism, we take decision at the every end of a single time instant here. Suppose friend, you are finding two process, suppose if I take some decision now, suppose I just ended one time instance here of execution, now OS has to take decision here. Now I found that that two process in ready queue which possess the same burst time here. So, what we can do? So, in that case, we operate again that first come first serve criteria to choose the process for the execution means I will choose that process which is coming in the ready queue earlier and friend in this mechanism after every instance execution, I will decrement the burst count a burst time by one. So, we will operate all this mechanism until I finish all the processes execution there. Friend, rather wasting more time, let us describe all this functioning with the help of this small table there. So, the table again has got some process are waiting in the ready queue. The process name says P1 up to P6. The second column is marking the time of arrival of those process in ready queue and last column shows you the burst time. Burst nothing but the time quantum it requires to execute completely. Friend, here I am just showing one small chart here to describe the functioning here. So, friend initially from the given table, I found that the P1 is having the smallest burst time here because at 0 to interval I only got P1 is ready in the ready queue. So, I get no option to choose the P1 there. So, from 0 to 1 time slot here, so friend, here this is a time interval part of this table here. So, this is marking the first time instant here from 0 to 1, second, third like this here. So, as P1 is alone in ready queue at 0 time instant here, I had to choose that P1 for the execution here. I will execute this P1 only for one time instant here. So, in that case the process may finish execution or may not finish execution here. Currently P1 has got burst of 7 there. So, after execution of this one instant here or in one time interval I can say the burst remain at the 6 here. So, in this case I will execute P1 initially here and at the end of this first, now I will just take all the process ready in ready queue here. Friend, we know here at the end of one time instant here, you find that the process P1 is in the ready queue. I also find that one more new process is now in the ready queue which is called P2 there. Presently P1 has got burst of 6 and P2 has burst of 5 there. Now, CPU is going to choose the smaller burst time process here that is P2. So, in the 1, 2, 2 instant here I will execute the process P2 in the running queue here and I will decrement the burst time by again 1. So, friend this is a mechanism. Now again at the end of this I can say what the 2 time instant here means somewhere here. At this 2 I am getting 3 process are ready in ready queue that is P1, P2, P3 here. Now burst of P1 is 6, the burst of P2 is 4 and the burst of P3 is 3. So, again we have to make a choice between either 6, 4 or 3. Now from this values number 3 is smaller and so that between this 2 to 3 time instant here or interval I will choose the process P3 for execution there. So, friend just operate this kind of mechanism and just try to have some sort of idea. Again at this end of this I will say here that 2 to 3 interval here I will again not take process ready in the queue up to the 3 time instant here. So, at this time I find 0 is ready, P1 is ready, P2 is ready, P3 is ready and also we get P4 here. So, but I will choose now P4 because it is showing me the least burst count here. So, that is executed completely in a single time instant here. So, friend this P4 will not been contest onwards here. So, we operate the same mechanism now for all the further processes and friend we are going to again decrement the burst count after each interval execution here. So, friend this chart is showing me this kind of execution phenomena and all the yellow marked rectangles are showing you the end of that process here. So, P4 ends at this friend this P4 is ending at what I will say the fourth interval and this P3 also ends at some interval like this here. So, we have to choose all these things properly here and if I repeat this thing basically friend we are going to get this kind of execution sequence in the given chart here. So, when this is a good expression how we can treat each process at single interval and we can use the burst time as a mechanism by which we can send a process for execution in the running queue that is in the CPU. Friend this is a method which is called as a the shorted remaining time first method here. So, friend I will construct this Gantt chart here from that given last table here and you see that in this Gantt chart the process P1 is appearing at multiple times here. So, friend where to take this time of completion for this P1 execution here. So, I will take that location on the rightmost side here for the process P1 there. So, friend this chart says that P1 enters in a CPU at 0th here and that ends at the end of 19th time instant here. So, friend this is a Gantt chart for this one. So, you are going to take that NPA is legal which is on the right hand side of that process here. Now, again friend we got two parameters by which we can measure the performance one is called the turn around time that is a difference in CT that is a time of completion and time of arrival and second is the burst time that is a turn around time and the burst time difference here. Again from the given chart we can have this entries. So, you have to use Gantt chart. So, from the Gantt chart here as I said earlier P1 entered at 0 here but that completes execution at 19th here. So, friend you just see that even this P1 has got burst of only 7 it is finished at 19th time instant here because in between you are finding some smaller process are arriving in the ready queue. So, I can't keep them waiting for longer time period here. It means that the longer process require more time to execute here. This is a property of the shortest remaining time first algorithm. And if I suppose say I will take this average TAT. So, it comes as 7 millisecond or somebody can say also 7 time instance here and for the average waiting time it is coming as a 4 millisecond or the 4 time units I can say. Now, before I close friend here this is the biggest benefit I find here. In this case the smaller process will not wait longer here. They have to only wait for one time instant here. So, friend in this case we are going to overcome a very severe problem of this starvation here. So, it is finding a very good use in the practicals there. Friend these are my references of this PPT or this discussion and thank you for watching this video.


Hi everyone, Joe for Jazby's casebreaks.com, coming at you with a Salo Pack, 21-22 Panini Prism Basketball, Ranitine, number 25. We got a few things happening here. We're giving away extra pack spots. We're gonna do the break. We're gonna do that immaculate right there. Give away, and we'll do all of that with multiple dice rolls. So the first dice roll is gonna be giving away those extra spots. Now we had a promo within the promo. I told everybody, hey, the next six spots purchased, and Eugene, you technically get, not technically, but you do get LastBotMojo as well. The next six spots purchased, you got a chance to win an extra spot. And you're still eligible for this spot giveaway as well. So we'll use the same dice roll for all of that. Let's roll and randomize it two and a one, three times for both of those randomizers. So name on top gets an extra one here, one after three, two, and once more, three. Now Eugene had the odds. There you go Eugene, extra spot going your way. Now you're still eligible, everybody, for those five extra spots, same dice roll, three. So top five after three, good luck. One, two, and three. So top five Travis, or Eugene, Travis, Eugene, Steve, Eugene, congrats to you. All right, so let's gather everybody's names right here. Now let's do the break itself. All basketball teams are in. Second dice roll for names and teams, that's gonna be five and a three, eight times each. Well, you wanna save your luck for the final dice roll, Logan. Let's reserve that until the last one. That's the most important one. All right, so after eight times, we got Logan down to Eugene. Five and a three, eight times for the teams. Two, and eighth and final time. All right, here's the first half of the list right here. No trades in these little filler breaks, and here's the second half right there. All right, and we just need one more, just need to do one more of these, move some spots straight up, and we can get into that one box break. Let's do it. We can make it happen tonight. I believe it. All right, here's the final printout, hot off the presses. Let's see if we have any surprises in here. The smart green, nothing crazy here. What about this bonus pack? Some red, white, and blues. I was hoping for a big rookie in there, but it's all right. The whole point of this break though, not necessarily what's in that pack, but who's gonna get those eight Immaculate Random Team spots? That one box break of Immaculate. Let's gather everybody's names in here. One through 30, right? Joe down to Mark. Joe down to Mark and everybody in between. Top eight after seven. Good luck, three and a four, seven times. One, two, three, four, five, six, and seventh and final time. So already you can see, sorry Steve, very close on that, but just not quite. Nine through 30, thank you for giving it a shot. Top eight, happy times for you, because you are in the Immaculate, one box break Immaculate basketball. Eugene, you're in. So is Logan, Evan, Logan, Mark, Travis, Steve, Eugene. That extra spot coming in handy right there for you Eugene. There you go, Logan C. What about, I don't know what you're talking about, no luck tonight. All right, there you go gang. One more, some full spots, Brakesville, jaspyscasebrakes.com, bye bye.