Hey guys, this is Kevin. What is a direct to damper? How are we going to use it? For DTEG and DTF printers, wide ink has been a problem. And the wide ink is very easy to clog. They condense, they separate from their medium and they condense down and clog the printhead. There has been many ideas. One idea is the shaker. There are people shaking their inks and they either shake the external tank or they even shake the whole printer. And they probably got their idea from the Home Depot, the hand shaker and mixer. However, there's a difference between the hand and the ink and the printer ink. Based on our experience, shaking actually makes the ink condense and precipitates faster. And there are two forces in your shake. One is the mixing, which is what you want. And the other side of the fact is that you get the particles inside the ink, they collide. So they aggregate, they conjugate faster. So actually you're making things worse. So what we need is we need to mix in the ink very, very slowly, gradually. So to store the ink, I suggest you're looking for a blood roller mixer. It works this way. You'll set up time and rotation and they start very slowly rolling the ink around. And this example is too fast. Of course, it's not designed for the ink. So I'm going to come up with something later that's just designed for the ink. I'll make it much affordable. That was the storage. But when you put the ink into the tank, you will need a mixer like this. And I have a microcontroller to run this thing every maybe five minutes or 10 minutes. And now you understand the large tank why it has a mixer. But what about this small tank on top of the printer? What is it? The smaller tank is direct to damper circulation system. There are two different dampers in a DTF system. For regular colors, black, cyan, magenta, yellow, we're going to use this kind of damper, which is set load and have a smaller volume. And for the wide ink, we'll need this top load, have a membrane one-way damper. So direct to damper means that the ink is fully mixed before it reached a damper. Let's take a look. Those two lines are feeding from the smaller tank to the damper from the top. So our wide ink is a mixer with a mixer in this wide tank. And there's a line underneath the tank that fits into the secondary tank. From this secondary tank, either fits into the printer and also the ink get out from another side of the secondary tank. And it flows back to the wide tank. If you see from the top, if you see here, here's where the ink get down back to the tank. So can we mix inside the damper? You'll have to watch my video, subscribe to my channel. To be able to mix inside the damper, you have to know the damper construction really well. Anyway, if you need any dampers or other supplies, you can go to bchtechnologies.com. Direct to film and have a part, which is to the two dampers that we discussed today, how to use it. And also, I'm starting having printer here. There's so many people ask me, like, how can we get this printer? Okay, go there, read why there's no return from me. This is a really nice machine. I have been testing it for a couple of months. And I test other machines and this is the best I've ever had. The problem with this machine is that they're not marketing in the U.S. The instructions are not in really clear English. The machine itself is still solid. However, I don't want to sell it in the U.S. myself. The reason is I'll be modifying smaller printers for specialty printing. And each time a customer doesn't read the manual and just return it and I cannot sleep for days. And now, if a customer doesn't read the manual and return a $3,000 printer, I'm probably not going to sleep for years. So if you really want this printer, just come to my website. I'm going to put a link above and how I gave you three ways to get this printer. I can even introduce you to the manufacturer and you can deal with them yourself. Anyway, I hope you understand that the wide ink managed system what it is and what's the current technology is. Thank you all about the tips about how to get rid of the spiders. And now the spider's gone and my lemon tree is happy. And actually I made some lemon flower tea today. It's just wonderful. Peace everybody. Happy printing.


Good morning everybody. So, basically they are on Friday when the basic installation of clicker software was given. There are a lot of queries from many of the centres because they have newly joined IIT Bombay as a new remote centres. They were not aware of the clicker, what is clicker and what is the use of clicker. So, today I am just going to give you a basic information of what is clicker. Clicker is also known as student's response system or audience response system. The very basic or simple example of this kind of system is audience response what you can say in Konbanega Karodpati, but this is we have distributed on a wide area network. The question is I will just show you basic thing. So, now you can see this is a very basic diagram which is prepared for remote centre 1 and remote centre 2. So, IIT Bombay is connected through internet. So, the clicker software what you are going to install is going to be on one of the PC which is connected to your Wi-Fi and Wi-Fi is connected to your tablets. Similar configuration is there for your remote centre 2 which is connected to your Wi-Fi and the tablets. So, in respect so you can have many remote centres. The questions will be flashed from IIT Bombay and similarly the question is viewed to all the tablets at the remote centres. The time will be defined for example 30 seconds or 60 seconds according to the quiz time and the participants are allowed to give the answers within that time frame. After the time is finished the answers are collected by the remote centre server automatically the coordinators do not have to do anything out there and automatically the answers are sent to IIT Bombay server and immediately the graphs and the data is displayed with how the people have answered. So, this is a basic diagram just for a mere explanation how the clicker software is going to work in the remote centres. For the same you all the remote centres have to install the clicker software which is going to be presented by Dipthi one of our colleague which is she will be demonstrating right now. The softwares and the required files have been uploaded on the Moodle server. I request you to download this file and if you wish to continue while installation you can do it. If you have downloaded the previous version before 11 o'clock please re download the latest software from your Moodle server. Please go to www.it.itb.ac.org in slash Moodle login to Moodle go to home go to orientation workshop for Akash coordination coordinator download the clicker software plus the clicker presentation which is going to be presented. Now I will be just demonstrating how to configure the wifi access point for your clicker devices or the tablets. We are using a tp link wireless access point as you can see here. Its model number is tlwr941nd. This we have sent it through the chat message also you can see it. The configuration is very simple. So it is a very basic access point which has got 4 hub or LAN port and one internet port. Whenever you want to configure your access point for the clicker software whatever the internet link is coming please connect to your internet link and one of the wire which is coming you connect to your clicker server or laptop whichever you are using it. So right now I have just connected the wire which is connected to the laptop and I have just powered it on. So I will just show you the basic configuration out here. I have opened the network connections. In network connection properties tcpip obtain ip automatically even dns automatically click ok. So this is the wired configuration that we have to keep it for your while configuring. By default whenever you open your browser the default ip address of the tp link is <IP_ADDRESS>.168.168 2.1.1. This you have to enter in your browser. I have already configured my links with the ip address 2.1. For you whenever it is a fresh installation it will be 1.1. I have already configured my device with 2.1 that is why I am using it 2.1. The password will appear by default the admin user and password is admin admin password is also admin. So this is the basic setup window which will be coming for you. As you can see it is giving you the ip range of <IP_ADDRESS>. The wireless is already configured and everything. So basically I will just tell you go to the network settings in the van connection. The van connection is the point of your internet connection on your back of your access point. The van connection is the same as the internet connection of your access point. If you are having a dynamic ip range which is given by your internet provider or if you have any internal LAN what you are using it. If it is dynamic ip or static ip whatever it is you can use it and configure accordingly. If it is dacp keep it dacp if it is static keep it on static and give the following ip address as per your colleges is provided. In the LAN setting the <IP_ADDRESS> is the ip address of the access point which is given. Go to the wireless setting SSID. SSID is the id which will be visible whenever you are going to connect your aakash tablet through wifi. So here I have given you the name as tp aakash. You can give the name as per your desire. Keep the channel auto and keep it in a mixed mode. Keep the channel in auto and keep the mode in mixed mode. Security presently I have disabled the security. If you wish you can enable the web security but I will suggest to keep it the security and disable for the workshop. Go to the dacp model. In dacp setting the dacp is enabled and the start ip with the dacp server of the access point which is going to release is from <IP_ADDRESS> to <IP_ADDRESS>. So this is the ip range what the wireless devices will be getting. The least time I have kept it at 120 minutes. Suppose any tablet is connected to the access point and suppose I assume that access tablet has got the ip address <IP_ADDRESS>. So this ip address will be allocated to the tablet for almost around 120 minutes. If the laptop or tablet is ideal for more than 120 minutes the ip will be released. If it is doing some work or some activity is going on so that time it will continue for more than 120 minutes also. So this is the maximum time that I have given it. So rest is by default the gateway is 2.1 which is same to the network of the LAN which is given. Same for the DNS, primary DNS also same. If you have any DNS settings which is running in your network you can give address as a secondary DNS. So this is the basic wireless setting that I have shown you. I will just show you how to connect your tablet device to the access point what you have configured. Now here you can see in a DACV client list since I have connected my laptop to my device. So it shows one client connected which is the client name as a clicker software, the MAC address and the ip assigned to the my laptop. To see the ip address I will just give ip config and it shows me you have connected having given the ip address 2.100. I will just bring the tablet also and show you how to connect your tablet to the access point. I am keeping this DSCP window open for your viewing and I will just show you how to connect the tablet to the access point. So below the tablet you can see the time and battery indications and all this thing I just click on that window. It will show you the setting window. Just click on the setting again. Here you have airplane mode, wifi mode and different modes which are available. You just click on wifi. The wifi window configuration windows comes. Just see to it the wifi is on. You can see different access point which are available. So as I have previously configured the tp link I will just click on tp link. Now it is obtaining the ip address and it is showing connected. So when I click again on this one it shows me you have connected to the tp link, sorry tp akash and you have assigned the ip address <IP_ADDRESS>. So if I just refresh my DSCP client list here. So you can see the android device which is connected and it has received the ip address 2.101. So like this the moment you have configured your access point and connected to your server the DSCP list will grow as your access points, sorry the tablet gets connected to your access point. I will upload the ppt files for this presentation right now. Because I have not prepared any ppt for this device I have just shown you the live configuration how to do it. Thanks a lot.


Hello, this is LaptopMedia and today we will show you how to open the Dell Vostro 15 35 91 and what's inside of it. Getting inside of this laptop is fairly easy. It requires a Philips screwdriver, as well as a plastic pry tool. First, you need to unscrew all 10 of the screws, holding the bottom plate onto the chassis. Then, turn the laptop around and open the lid. Here, you would like to start the prying process around the touchpad area. Then slowly make your way around the device. After that, just turn it upside down and lift the bottom plate away. In terms of cooling, there is a single, yet thick heat pipe, which drives the heat away from both the processor and the graphics card. It is a common solution but honestly, it is not a great idea to connect your two main heat sources, especially when there is only one heat spreader. On the other side, upgradeability looks great, there are two storage options. An M.2 PCI Express X4 slot and a 2.5 SATA drive bay, flanking the battery. As of the memory, you get two RAM Sodom slots that support up to 16 GB of DDR4 memory, working at 2,666 MHz. By the way, Dell's official specs sheet shows support of 3,200 MHz RAM as well. Finally, there is a 42 Watt hours battery pack, powering the notebook, when you don't have it connected to the wall.


The motivation for this research project was to find exoplanets. I was working together with astronomers. I spent some time at New York University, hosted by an astronomy department. I've always been interested in astronomy, even though my field is machine learning. And one of the most fascinating problems of astronomy is to find exoplanets, which means to find planets that orbit other stars out there in space in our Milky Way, typically. How do we do this? The most prominent method that's being used to find exoplanets is based on light curves. So it's based on monitoring the brightness of a star as accurately as possible. And to do this as accurately as possible, astronomers have resulted to the help of space telescopes. And the telescope that has led to the largest number of discoveries is the so-called Kepler telescope that was launched by Neissar some years ago. It's named after the German astronomer Kepler. And this Kepler telescope, stared at one patch of sky, record very accurate light curves, which are not affected by the effects of atmosphere, etc., because it's out in space. And this data is shared among all astronomers. And we can now try to analyze it and find exoplanets. And in order to be better than other people at doing this, we have to be better at removing what's called confounders. So confounders are processes or effects that distort the signal that we're interested in. So we really want to get the signal that's from out in space, but we measure it through a telescope that might have little pointing errors, that might introduce some noise, maybe the sensor of the telescope introduce noise, etc. So we are interested in a signal that's confounded by these, sometimes also called systematic errors, and we want to remove these systematic errors. And that's an example of a larger class of problems that's applicable to astronomy, but also of independent methodological interest for us as machine learners and causal modelers. Our approach is that we try to think hard about what kind of information is available in the data. We are interested in one star. This one star is confounded by the effects of noise taking place in the instrument. We don't have direct access to this kind of noise. Therefore we have no direct access to the physical signal out there in space that we want to reconstruct. However, in addition to the one star that we're interested in at any given point in time, we have 150,000 additional stars. Now if it's the case that these additional stars are also affected by the same noise sources, then in principle it might be possible to remove that information from the other stars to correct the light curve of the star that we're interested in right now. So whatever the stars share might be new to the confounding effects of the instrument. Whatever they don't share is actually the true physical signal out there in the world, because in space these stars are separated by light years and they don't directly interact. From a practical point of view, if you work in machine learning or pattern recognition and you try to tackle such a problem, what you do is you get together with domain experts at the blackboard and you try to brainstorm what kind of information is there and how could we use it. So in my case the whole thing started with a short sabbatical that I spent at New York University in 2013. And this time was so productive that not long after that visit, we got a return visit from our colleagues in New York and then we sat together in Tippingen in late summer 2013. Talking about this problem again, we hadn't solved it yet. We're sitting at the blackboard thinking about what kind of information is there, drawing down diagram, what affects what, and starting to think how could we phrase this as a machine learning problem. So how can we phrase this as a problem where we have data, inputs and outputs, where we have observations on which we can train a system that can learn to predict outputs from inputs and how we can use such a system to correct these light curves. The result of our research is a new method to detect the presence and correct the effect of a confounder. So to correct the effect of something that is caused by the measurement process, but that's not really what we're interested in. We're interested in a true astrophysical signal out there in space. We're not interested in the noise that our instrument adds when measuring that signal out in space. Now we're using the other stars to estimate the effect of this confounder because all the stars are actually affected by that confounder and at the same time the stars out in space are independent from each other. So we have a set of independent things that are light years apart. They don't interact directly out there in space. And then we measure something, light curves, which are dependent because they share the same confounder. And then we can use these other light curves to correct a light curve of interest and we do this by something that's called regression modeling. So we try to predict the star of interest from the other stars and then that prediction we subtract from the star of interest. And it turns out subtraction is exactly the right thing to do if a certain additivity assumption about how the confounder acts holds true. So we can actually prove theorems about this. We can prove that if the additivity holds true and if sufficient information is present in the other stars about the effect of the noise then subtracting that regression is the right thing and it corrects the signal and reconstructs the true signal up to an offset. Now there's a nice analogy that we can draw that's maybe easier to understand and it works quite parallel. Suppose you have a set of children that all share the same mother but one of them looks very different. In America they call this the milkman's or in England they call it the milkman's child. I think in America it's called the male man's child and we all know what this refers to. And then the problem is the following. Suppose you have such a set of children. Now here we have one that looks a little different and what you can try to do is you can try to explain how that one child looks in terms of how the other one's looks. So they have certain similarities. These similarities are caused by the fact that they share a mother. Now in our astronomical application the mother is the instrument that records the signals. So the instrument makes sure all the measured star signals share some information. We want to remove that effect and reconstruct the star out in space. Now in the milkman case we would take the children, we look at one, maybe the one that looks different. We try to explain the appearance of that child in terms of the siblings. If we then explain away this appearance by subtracting now it's going to be more complicated in this case because the effect is not additive subtracting what we can explain in terms of the siblings then hopefully if our mathematical assumptions hold true which they don't in this case we would recover how the milkman looks. Now in practice things are a little bit more difficult. So in practice we not only use the other stars to predict the star of interest in order to correct the light curve corresponding to that star but in practice we take into account what we're interested in in that light curve. So what we're interested in are actually transit events. A transit event means the geometrical alignment of star and planet is such that as we look the planet passes in front of the star and occludes part of the surface of the star which leads to a small dip in the light curve a small decrease in brightness. So that's what we're interested in and this is a so-called transient event. It just takes a few hours. So for instance if you were to look at Earth and Sun from space if you were lucky to pick up a transit it would take half a day. So we're looking for such signals that take a few hours or take a day in the light curves. So we want to retain this kind of information in our light curves but remove everything else. We're just interested in that. And it turns out if we use present not just the present of the other stars the present values of the other stars but also the past and future values of the star that we're actually analyzing we can do an even better job. And we have to make sure that this past and future is sufficiently separate from our point of interest so we don't actually explain away the transit itself. But if it's sufficiently separate we can do a better job not only at removing the confounding effect of the instrument but also we can remove the variability that's intrinsic in the star itself because it turns out stars are not as constant as we used to think. Almost every star shows some brightness fluctuations anyway and if we look for exoplanets we are not interested in the brightness fluctuations of the star but we're interested in the fluctuations that we get if an exoplanet occludes part of the star. Our results are relevant foremost in terms of the methods that they propose. So we develop methods and we have a new method along with some performance guarantees under which conditions it works and this method is applicable in various domains in bioinformatics medicine but of course we developed it for astronomy and it's applicable in this field and we have applied it in another paper and this other paper is looking specifically at new data from the so-called Kepler-2 mission. Now Kepler-2 means at some point the Kepler satellite broke. The satellite had four so-called reaction wheels that are used to stabilize the position of the satellite in space in order to make sure it's looking at exactly the same stars all the time. There were only two reaction wheels left and people, which means that the satellite cannot stabilize anymore but people had this idea that they can use the remaining fuel and the thrusters like in a rocket you know you have thrusters that are driven by fuel to try to stabilize the satellite as well as possible. Now that's much worse, it's not as good as before but in a sense that's good for us because we exactly deal with this problem how to remove these kind of errors. So the data that the satellite, the satellite in the Kepler-2 mission and started looking at some other fields that haven't been observed before and then we immediately started looking at this data and then in this data essentially using our method combined with some clever method for searching through light curves because our method just corrects light curves. Now we have to search for these dips that come from a transit. So combined with some method for searching these light curves we came up with a list of exoplanet candidates published this list, it was a list of around 30 candidates and about half of them were confirmed afterwards relatively soon using other means. So they are considered as true exoplanets by the astronomers of course nobody has visited them but that's the same for all exoplanets we know. So that's an outcome and we've been quite happy with this. Where do we go from here? Of course there are many other applications for these specific methods some in astronomy, some in other fields but really we are methods developers and we are interested in the broader picture of the relationship between statistical observations and causal structure. And it turns out that statistical observations are just a surface phenomenon and underlying we always have to have a causal structure that brings about these statistical dependencies in the first place. This was first understood by a physicist and philosopher Hans Reisenbach who postulated what's called the common cause principle. We have reason to believe that if we understand this underlying structure we can build machine learning systems that will generalize better from one task to the next one. So currently in artificial intelligence we have amazing successes with machine learning systems that are very good at solving one task. We can train object recognition systems on labeled data if we have millions of images of animals each of them labeled as cat, dog, etc. We can train a classifier that will recognize cats and dogs extremely well and maybe more accurate than a human by now. But we're not very good at transferring knowledge. So if someone gives us a new type of animal to recognize we can only do that well if this person also gives us millions of training examples again. So we're not good at transferring the variability that we've learned from the animals we've seen to a new class of animals. And we think the reason for this is that the current systems only focus on statistical information and don't try to understand the causal structure underlying these observations. And we think if we can model the causal structure while retaining the attractive property that we do this in a data-driven way we don't want to sit down and write down differential equations for everything. This is a data-driven approach to handling complexity. So if we can retain this attractive property but go one level deeper trying to automatically learn causal structure that gives rise to the statistical structure we have reason to believe that in this case we will generalize better to new settings. So this is the big challenge for us at the interface of causal modeling and machine learning. How do we automatically learn causal models from data and how do we exploit such models to generalize across different tasks which is something that humans and animals are good at and that artificial intelligence systems so far don't know how to do.