Hi, from San Francisco, it's theCUBE. Covering Red Hat Summit 2016. Brought to you by Red Hat. Now, here are your hosts, Stu Miniman and Brian Gracely. Welcome back, we're here getting towards the end of day three of live coverage from Red Hat Summit 2016. I'm Stu Miniman, joining me with Brian Gracely, and happy to have on the program first time guest Jose Miguel Parella, who's the open source product manager from Microsoft Azure. Thank you for joining us. Thanks for having me. All right, so your colleague, Joseph Serocha, gave the keynote this afternoon. We actually had him on theCUBE earlier this week down the street at Hadoop Summit, so another open source show. So, it's one of those things I think everybody here is still like, Microsoft's here, and they've got little penguins that says Microsoft, you know, hearts, Linux, and things like that. Tell us a little bit about your job and your role with open source. Yeah, so the penguins were really, really popular, I guess, and a bunch of other things that we had here. It was their first time at Red Hat Summit, but you do see a pattern in these open source events, and I think it reflects on the Microsoft journey with open source and what we have in Azure in terms of an open and hybrid cloud. We have a number of people in the company working on many different areas in open source innovation. We have a very comprehensive approach to open source. It starts with enabling open source technologies, releasing code. Earlier this week we talked about ASP.NET Core, ASP.NET Core, and the support on Red Hat Enterprise Linux in particular, and then also, obviously, contributions to open source, but also integration of open source technologies into first party solutions like Azure Container Service and others. Yeah, it's interesting, the keynote started out with this whole space aspects of what you're doing. We had one of the JPL guys on today talking about the HoloLens type stuff, so how does that fit into some of the things you're doing? Well, I think we talk a lot about the next revolution, next industrial revolution, and what role open source, open data, artificial intelligence, big data plays. I think all of the space theme helps illustrate what you do when you have those vast amounts of things to process and how the theme of open can help you achieve that, but also the cloud, right? Because it offers you that flexible fabric, a scalable fabric, an acrostic lobe, Azure operates today in 32 different regions, 24 of them are online now, so it's really exciting times, but participating at Red Hat Summit, I think it has been critical to think ahead in terms of what our customers want. Customer choice and customer demand is driving a lot of the innovation that we see in the market, and as Joseph said at the keynote, and you know, there are areas where we truly believe that open source R is going to be where statisticians and data scientists are going to be at in fact out today. Yeah, would you walk us through some of the announcements that you guys made this week? Yes, so in the context of Red Hat Summit, we had a number of announcements this week that you'll find in the official Microsoft blog, so I already mentioned .NET Core 1.0 and ASP.NET Core 1.0 and their availability in Red Hat Enterprise Linux. We also announced a template for OpenShift that's available just to easily deploy OpenShift in Azure. So today it's an OpenShift origin template that you can deploy on Red Hat Enterprise Linux. That's actually what we use for today's demo where we demoed SQL Server running on a container at the keynote. We also now support in China, so it's a very interesting partnership milestone. Our partnership started in November, but we're bringing it to the regions where we operate in Azure China. It's a very interesting one. You know that in Azure, we have nearly one in three VMs run on Linux today. In China, actually more than half of our VMs run on Linux. So it's very strong demand, especially in the enterprise for those type of solutions. So those are some of the interesting areas and obviously I think that something that people are really excited today was that we actually demoed the installation process of SQL Server on Red Hat Enterprise Linux. Yeah, you talked about a third of the VMs on Azure, to half the VMs. Last week we were at DockerCon. I mean, huge number of demonstrations with Docker. Showing open source integration. What's the things that you're doing to get people to go? In the keynote today they made a statement. They said Azure's the most open public cloud. What are you doing to educate people, to help them understand that Microsoft is really committed to open source, to Linux, to open data. How is that kind of getting out into the world? I think participation in the ecosystem is critical and it's been an incredible year. One year ago we were at LinuxCon in Seattle and since then it can recall a number of events including all things open in Raleigh, actually Red Hat's headquarters. It's participating and committing to that participation I think has been critical, getting out there, getting from the community. Get a lot of our engineers, get a lot of our program managers out there engaging with customers, with partners and with project leaders as well. So those things have been really critical and I also think that communicating and openly discussing our approach to open source in the cloud has been important but also helping customers navigate the open source world has been important as well. If you think of .NET and SQL for example, products that are traditional Microsoft products for the enterprise now increasingly getting closer to Linux in the open source world. Customers are starting to look for the organizations that can help them understand and navigate that world. The other area that you mentioned and you're absolutely right is containers. We have seen since January about the number of customers in containers in Azure has quadruplegated and our approach or portfolio of solutions now is really broad. We started with this little thing. If you have a VM, we'll attach Docker to it and just recently we announced GA of Azure Container Service and in between of that journey we have done partnerships with many things that we have in marketplace with companies like CoreOS. We have full pass solutions like OpenShift available in Azure. So providing that full spectrum lets us talk about the use cases of containers in the cloud. You want to start easy, you have Azure Container Service. Does that mean that you have to give away choice? Absolutely not. You have your choice of swarm DCOS to implement the orchestrator. Do you already have a strategy in place with something like OpenShift and that's perfectly fine. It supports Azure as well and you can move your work. Let's do it. But what are you seeing in terms of uptake? I mean we heard a lot this week about containers. We're doing a lot of work with OpenShift. What are you seeing from your customers especially say the .NET customers in terms of them wanting to build these more sort of modern cloud native applications? Are they comfortable with the idea? Are they beginning to use the tools more and more? Well in the .NET world is still early days. In fact the .NET support in OpenShift is still a few days out. It's one of the things that we were talking about this week. Generally speaking, I think the key has been to offer architectural choices. So you have containers, you want to approach microservices that route, you want to do it with a platform like OpenShift, you want to do it with something else like ServiceFabric for example, you have that route. But if you're still thinking in terms of IS, you're still thinking in terms of VMs and you find you have a sophisticated image management practice. You have images and BHTs that are really stateless if you will then we have things like scale sets. And so with scale sets you can realize a kind of modern next generation applications without necessarily going all in containers. In fact things like Azure Container Service are built on those core capabilities of Azure like scale sets. So I would say that we have a continuum of customers in different stages of sophistication when it comes to those cloud native applications. Jose, talking about applications, one of the things that I think had the biggest ripple effects in the communities I watch is how Microsoft has allowed the movement of some core applications either to cloud enable them and or to support them on Linux. Can you talk a little bit about some of the reasons why Microsoft's doing that and what you see is kind of the future of applications there? Well it certainly is customer demand and what customers, one organizations that support enterprise use cases like Microsoft do. There are many areas where it, like IoT like containers like big data where you definitely see Linux and open source driving innovation. I think it's been a big topic here at Red Hat Summit for sure. And obviously the ability to offer products that the enterprise really like like SQL Server and .NET is only gonna bring good things to the ecosystem. And again, it's a journey, we're learning a lot as well. We've been over 10 years engaging with the open source community in one or another, but I think we're learning a lot for this participation with the ecosystem and the way of doing things and we have so many anecdotes. Through our engagement here at Red Hat Summit, the demo that we showed of OpenShift and how we work with the OpenShift team at Red Hat to make the demo of the keynote happen is just one of many examples. Yeah, earlier this year, Microsoft made an announcement something called Azure Stack, essentially taking Azure, the public cloud being able to instantiate that on premises. Azure cloud is obviously again, like you said, very focused on open source. Will we see that open source focus extend out to Azure Stack as well as it becomes GA later in the year? It is certainly our intention. There are already, just think of it this way, things like Azure Resource Manager templates. We host hundreds of them on GitHub today. Most of them because of the, it's very easy to distribute open source based images for the community. So most of them that are provided by the community already open source solutions. So you want to deploy a data stacks cluster, do you want to deploy a MariaDB cluster? You can do those with ARM templates today. Now with Azure Stack, the promise is that you'll be able to point those templates out to your Azure Stack deployment. Now the question is, where is the image coming from, right? Because in the public cloud is easy to understand. You have a marketplace, there's a billing integration, it's easy for a partner to offer that image. In Azure Stack it's a little bit more nuanced. So customers will have to navigate a little bit of that world of providing your own images from a technology standpoint that is absolutely our intent. In fact, we do have an interesting demo with one of our partners Canonical, just pointing out the Azure CLI, the command line tools, pointing out to public cloud, pointing out to an Azure Stack cluster, it's currently in preview, and it works exactly the same. Partially it's also because all of our SDK and tool strategy has also moved to an open way of doing things. Now we no longer publish the SDK and you hope that it matches the API. We just public a spec for the API and we auto-generate the SDKs for things like .NET and OJS, et cetera, it's called auto-rest. So that lets us have that feature parity across tools that a few years ago it was a lot of customer demand for that for sure. So Jose, I'm curious, what's your take now that you've been working on open source for a while to be able to be out in public more, you're in action with the users? Tell us what that's been like. Well, our participation at Red Hat Summit has surpassed all of our expectations in terms of the excitement that customers, partners, and project leaders have. As I said, it's not only about the squishy penguins that are certainly something that people like or the Microsoft Linux stickers that are also really popular. And I was asking them, what are you doing with those stickers? And they're giving it out to their windows counterparts in the enterprise and just, you know, so we definitely think that's great and that we have more of that pure to pure education on this open source capabilities too. But the engagement has been fantastic. I think we've learned a lot. We've learned a lot about, you know, what enterprise open source needs really, what customers in the enterprise really, really need from an open source provider. And I think what's clear is that in our approach, the partnerships are going to play a key part of it, right? Like Jim Whitehurst said, there's no single vendor that can fulfill all of this needs today. Ask open source, drive that innovation and decision makers to start looking at open source as a critical part of the digital transformation, literally quoting an analyst. I think that they're going to start looking more at vendors like Microsoft and partners like Red Hat to make sure that we deliver on that promise. Well, the only last piece of feedback I'll give you is if you can get those hoodies in the Microsoft store, I think you've got a winner on your hands there. Awesome, we'll do that. All right, we're getting towards the end of three days of coverage here from Red Hat Summit 2016. Thank you to our guests from Microsoft and you're watching theCUBE. Yeah.


All right, today is something new. We're gonna do reviews and I got to pick between Monday Tuesday Wednesday. So let's do review Tuesday Today, I'm gonna take a look at hundred Tuesday tips by gris and norm It's actually volume one and two and an extra book That was loud and why am I picking those? Well on Twitter every now and then I see tweets from artists with screenshots and pages From this book So I was wondering well Is there maybe a way to have this as a collection and actually there is I'm gonna link in description a link to Etsy Where you can buy these you can buy them separately you can buy them as a bundle as I did and that's why you got that extra book So I'm gonna give you a little bit of a page through of the things that are really we like about this book And I think as an animator is super super helpful. So let's go through those books here So as we go through It's really really neat how immediately it starts into animation related material You can see how it asks you to push your poses and it kind of goes back and forth between Sketching and form and silhouette and also color. There's some really cool stuff. It talks about clear silhouette line of action This is all very very appropriate To animators and it goes through straight against curve again color stuff Hands there's lots about posing It's interesting back and forth between different topics and you would see stuff like that posted on Twitter So they could be something about a flower sack, right? Which is really cool because that's one of the classic assignments as an animator It's actually really helpful to have just that in there. There's more about palettes again gesture drawing composition drawing line exercises Tangents one thing I'm constantly complaining about tangents very very cool that that's in there. I'm not alone Silhouette and sorry telling film study. There's so much awesome stuff in there I can go I mean I want to go every page, but let's just kind of thumb through here Straight versus curves Just brought a value eyes and ears. So I poses super important More specific drawing things Stylized objects boards. This is so good. So good type of shots for storyboarding We're shading about all contrasting characters. It's great to there's so much good stuff again I don't want to you know spoil everything and go through the whole thing But this is just volume one then you have volume two Tuesday tips volume two oh So good I love that in terms of how you could set up a scene composition if you have something where it's not just one shop But it's more about a sequence It's very cool already starts in an awesome way. There's so much good stuff in this book It's absolutely bananas, but hold on. Let me continue. So as you continue on going with twisting and your posing Body talk capes and stuff pushing poses But your face but your eye line especially again here. How far can you push your poses? There's so much in there. That's helpful. So if you're looking for something specific like posing asymmetry, right? It's just right in there. It gives you quick little tips. There's more about color lines and shapes and value perspective Posing for your spine and what to push in terms of your shoulders So good, this is volume two So again, I got the bundle volume one and volume two This came as well. This was an added little thing super cute cute style nice colors There you go That was the bonus you can buy these separately this one or two or the bundle now You might not need this as a book you can go online I can imagine Pinterest has a ton of those pages or I don't know where you go and Google it and you can probably see a lot of Examples there that's fine But I also like things just in book form so I can decide where to go I want to bookmark things and I can have this everywhere where I go So you don't always have to be online or you have maybe your thumbnail saved on your phone where it is So it's kind of up to you, but I think this is pretty cool to have this in book form. They're not too big Not too heavy Now on the picky side, you might say that it's a bit disjointed in terms of subjects So it goes from color to some only shapes about hands and then about shoulders and then value and then storyboarding So it's a bit all over the map and there is technically no index. So if you look at this here It basically just starts. So if you want it to be a bit more organized It's just kind of there and there's nothing at the beginning or at the end I will tell you where what is so if you want to be a bit more organized and find things quickly You're gonna have to be old-school and do some bookmarking Hacking there and for shoulder acting just do this, but again, I mean come on shoulder acting is it. It's so awesome So I think that would be the only drawback. It's a bit all over the place. There's no index It's nothing where you can just immediately go I want this right there you have to kind of page through it to find it But then again, there are ways where you can just do it on your own with Post-it notes or whatever your method is But I think in general it's just kind of meant as a nice collection of all the tips and not as a go to here Is the topic blah blah blah the next topic blah blah blah, but maybe that could be volume three I don't know but me as a whole I really like it I have this bookmarked online as well, but it's just really cool to have this in physical form So if you're interested in this again, link in the description you can go and buy it That's it. You will see another review on Tuesday It might not be every Tuesday, but on Tuesdays there will be reviews from now on. All right As always, thank you for watching until the very end if you watched this whole thing I really do appreciate it and if you like this a like if you have suggestions Drop a comment if you want me to review things Leave me a comment and let me know what you want to get reviewed If you have something that you want me to review and you can send it to me If you are a company or whatever there is also an email in the description if you want to contact me And that is about it Thanks for watching and I will see you in another clip


In this lecture we are going to speak about fault diagnostics and prognostics as we already know that in this course we are focusing mostly on CBM that is condition based maintenance. We will see what are the definitions of fault diagnostics and what is prognostics and how do we estimate the remaining useful life of a machine because of the fact that you know once we maintain a machine we would like to see or predict by certain tools how long this machine is going to last before we totally remove it out of service. So the essential elements of CBM or the prognostics health management cycle are as follows. As you all know the most important features are the sensors around a machine and then sensors are going to provide us data which has to be analyzed and all our decision is based on this analysis. But in the modern days CBM the trend is towards that the sensor whether I can do with single sensor whether I should have a multiple sensor whether the sensors are fault tolerant etc. Because as you know everything in this CBM depends on the data collected by the sensor. In the to begin with if the sensor itself is faulty and it is providing us wrong data our analysis will be totally wrong. So the most important feature of what the sensors nowadays are used in CBM are what is known as smart sensors and topic like sensor fusion whether a single sensor will do or a multiple sensors have to be used and then of course towards the end of this lecture I will give in a short case study on sensor fusion and how we will see the remaining useful life of a cutting tool can be predicted by using sensor fusion. Now once we have the data coming from this sensor we can classify the faults and also then try to predict how the fault is going to evolve and then if necessary we will go for maintenance. So the prognostics or estimation of the remaining useful life depends on my data analysis. So before we move to the next sections I would like to give you a definition of fault diagnostics which is detection, isolating and identifying an impending or incipient failure condition the affected component subsystem system is still operational even though at a degraded mode. So the fault diagnosis encompasses detection, isolation and identification so fault diagnosis has three important components one is detection, other is isolation and other is identification and also and fault diagnosis is also used to detect isolate and identify a component or system that has seized to operate. So in one case we have the machine still running, machine running in another case we have machine sees to operate as I was telling in the last class you know CBM is not good for a machine which is not operating so we will use mostly CBM for a case when the machine is running. So to define fault detection it is known as an abnormal operating condition which is detected and reported. So this is the definition of fault or failure detection that is an abnormal operating condition which is detected and reported. We will see the mathematical techniques how such faults can be detected can be isolated can be identified and so on in the subsequent sections. Next is the fault failure isolation so determining which component subsystem or system is failing or has failed. Next is the fault failure identification that is estimating the nature and extent of the fault. Now question is how do we diagnose these faults? Diagnosis traditionally are done by two important methods one is the model based method and other is data driven or signal based method. In model based methods people use certain mathematical models like the from the physics of the problem in model based techniques they have a mathematical technique known as for example I will give you a simple example here. Suppose I have a system a simple mass spring dashboard system and I have got certain response because of a fault in it. So I can write the equation of motion of this system and because of some force I am going to get a response though I have written as a vector and shown a single degree of freedom system but you could generalize that a system having a lot of m and k's and c's and it can be written in such a matrix form and this force is what is creating the response in which we are measured response which is measured and once I have the response measured and if I have some estimate of this m c and k I can through this equation find out this force. If this force is abnormal force is more than what is necessary I can say a fault has occurred in the system and this could be done by what is known as the residue generation. In the model based system one such method is the residual generation technique. However in the present course on CBM our focus will be towards mostly data driven or which is also otherwise known as signal based because this is very easy to understand in the sense I have a machine I put a sensor and I get my signal and everything is the total FDI is done based on the signals and that is traditionally people do such kind of FDI or CBM in the industry and this is very easy to do compared to the model based technique wherein in the model based technique you require lot of computation, lot of physical understanding of the system. For complex large systems this becomes very difficult to model the entire complex system. So traditionally people have been using mostly the data driven or the signal based technique and in this course we will be focusing our attention mostly towards signal based techniques. Though while we are on this topic I will also tell you some of the model based techniques other than the residual generation techniques which are used in the industry or are practiced by maintenance engineers to do a fault detection or identification in a machinery. Before I go to the model based fault diagnosis I should mention to you that this data driven fault classification is actually done by many methods. One is stored fault written library and then we have a fault classification. For example something like a lookup table we compare in a database signals already stored with the measured signal. If the deviations are large we can pretty safely say a fault has occurred. Another is this feature vectors now we can in this signal what are the features to be studied. I will focus more on this when I talk about the time domain and frequency domain analysis but to do a fault classification there are nowadays many techniques one is the neural network based methods which is very widely used in the industry the fuzzy logic and the Bayesian system and then these are mostly reliability and probability based models and then defaults can be diagnosed. So in a data driven fault classification there are techniques wherein this signal are analyzed based on certain neural network based on fuzzy logic and a decision is made on the fault classification. Could be by fault classification I mean whether fault are of two different types one is severe one is normal or one is something which we can live with. So such decisions can be made by a neural network systems and I will give you an example as to how this kind of study can be done for different machines. We have a case study for a cutting tool monitoring situation which I am going to tell and this data diagnostic methods there are many ways by which this data can be diagnosed. One simple is say for example with time we have a certain signal parameter which we are monitoring say for example line now with time these are my upper and lower bounds. So what could be happening that my system parameter etc. So this is the upper bound and this is the lower bound. I can set the limits of this upper and lower bound within the plus minus 3 sigma values of the measured parameter and I can be only alarmed that a fault has occurred in such situation fault has been detected. So simple alarm bounds can be used and then in fact fault can be detected and traditionally or historically in the industry people were used such people were using such alarm bounds and then you know you can detect a fault but nowadays the availability of many algorithms and fast computers many new methods of fault diagnostic methods have evolved and we will discuss few of them here. Many statistical techniques are available I will give you one simple example of regression analysis for example with time I know that this is the signal parameter and this is my alarm level that means if the signal will increase beyond this level I will be alarmed about the condition of the machinery. For example what I could do is suppose I have measured with time that these are the condition of my signal. So statistically what I could do is I could do a simple regression analysis and suppose my measurement has been done only at these points looking at the past data and taking the present data I could do a straight line fit where you know y is equal to m x plus c is the equation to this curve here this is y and this is x but this is a single component I could have multiple coefficient but the most important parameter of this is had I known this condition of this machine and I know the equation to the straight line I can always find out the remaining useful life from the past data and this has been also known as what is known as the trend analysis in the industry that means looking at the past data measuring the present data I can come up with regression and then estimate when this machine will have a failure. So there are many software available with lot of database where this kind of data are stored people do simple regression analysis and can predict the failures and even in industry if this kind of measurements are done this is going to give us a lead time before I do my maintenance so that I know the remaining useful life. So I have this kind of a lead time before the failure occurs to take corrective measures I could perhaps now you know because of this trend I could increase my maintenance activity increase the maintenance activities such that I can reduce the failure and subsequently maybe this levels could come down and with time you can take corrective measures and that was just a simple example using the straight line regression analysis or linear fits but nowadays when multiple parameters are involved it becomes impossible to find out a straight line fit and many of the relationships between the input to the system. So such an analysis it becomes very difficult humanly to measure know what are the input parameters output parameters so people use what is known as a neural network or artificial neural network to find out a relationship between the input and output and come up with models as to what kind of output levels will be predicted with as a function of time and then we can estimate the remaining useful life by such a technique there are many methods of RUL estimation one is the fuzzy logic classification other is the neural network classification and next one is wavelet neural network in this course we will not be focusing into more in more on model based for diagnostics or using neural network and other tools but mostly since it is a very basic course on machinery for diagnostics and signal processing we will be mostly spending our time on the fault detection through the looking at the alarm levels looking at the past history looking at the lookout tables looking at the historical data and then try to correlate the fault condition with the present signature and that is what we are going to focus in this course. Now that we have some idea regarding the data based fault detection methods I will also tell you about the certain physical model based methods which are used in well CBM may be in large sophisticated systems for example an Airbus A380 there are many many systems it is a very very complex systems and what kind of fault detection strategy is to be used so this could be a combination of data driven and also a model based. Some very fundamental problem in engineering is be it cement mills be it gear boxes casings etc is the development of fatigue crack and its propagation so once a crack has developed on a machinery component say some crack on a machine component the next question is always people have in their mind is how long is this crack going to be there can my machine still run under this crack condition etc and the most important equation to this is this crack growth parameter with the number of cycles of operation C0 is a material property NAN is also a material property and this is known as the famous various equation from such an equation we can always estimate the crack length or dimension for crack this is the number of cycles the material property this is the stress intensity level and this is again a material property we can decide on how many number of cycles this machine can be loaded before a crack grows from an initial length to a final length. And then once N is estimated we can then decide on the RUL for a crack component this being a basic course I will not go into details of all this because this will require lecture on fatigue failure and fatigue fracture mechanics but I will just want to mention to you that such techniques are available for the crack growth development and then once we know the final crack length which our machine can be subjected to we can decide and we can estimate the number of loading cycles and thus know the time remaining useful life of the machine. Another very important model based techniques which people use is the FEA. So, FEA has been used in model based diagnostics so what we can do you know if you go back to that same equation I was talking about simple FEA model of the system can be developed and this force can be estimated and then the model based fault diagnostic procedure or strategy can be developed for the fault detection. Now once we know have an idea regarding the fault detection, fault diagnostics, fault solution identification and once we have understood our system the most important parameter is the RUL and what is actually known as the fault prognostics. So, prognosis is the ability to predict accurately and precisely the remaining useful life of a failing component or subsystem because once the fault has been detected and isolated the next question is this prognostics to estimate the remaining useful life and all these mathematical tools of you know trend analysis artificial neural network etc could be used to predict RUL. Now with this what I would like to do is I will show you an example as to how this model based or data driven based technique can be used for fault detection in a machine. So we are going to talk about toolware monitoring case study in fact and this was the project which we did in IIT about a decade ago and this was sponsored by the department of information technology here. This project was to estimate the effect of multiple sensor based fusion using neural network to determine the useful life of a single point cutting tool. In fact in this example I mean this work has actually been published by the in the journal of mechanical systems signal processing and the details of this could be found in that reference. But here let me tell you what this tool condition monitoring is about. We have a phase milling operation being done on a machine. We used two cases or work material one was a steel and another was the aluminum. There were no cutting fluid use it is a dry cutting condition there is a single cutting tool in this insert and the cutting speed approximately was at 140 meters per minute or 557 rpm of the spindle. Feed and depth of cut were maintained less and the approximate toolware was 75 in such a condition this instrument or this milling machine was instrumented with a cutting tool force dynamometer was instrumented with the acoustic emission sensor with a vibration sensor with a microphone etcetera and also the current driving current being supplied to the spindle motor was also monitored. So, I will show you this current which was being supplied to the spindle motor was measured using an hall effect sensor because this had a variable frequency drive and one this rpm was 557 rpm the corresponding to a frequency of 18.56 hertz and if you look at the current which is being measured by the hall effect sensor which is driving the spindle motor you will see this current to be a sinusoidal signal and then a single frequency is shown in this current. Next is when we try to mill aluminum with dry cutting conditions and try to measure the vibration the cutting force and also the current and current also gets modulated because the load on the spindle motor and then you can see the side bands of the current. I will not go into details, but these are the features which could be extracted from this signals around this machining process being current force and vibration and once we try to machine steel in the same conditions the cutting forces the vibration levels and the current modulations are high and which is reflected in such a plot here. Now with this kind of analysis we thought that why not we instrument this machine with many more sensors which are more than required like voltage acoustic emission vibration cutting force in x y z direction sound pressure level and then we have a data equation system where when we do a signal processing and feature extraction by certain software and then also try to in the offline stage measure the tool wear condition by a microscope. So, we have the actual conditions and then they have an offline condition of the tool cutting tool wear and then we through artificial neural network we could try to estimate the tool wear and then try to find out at what tool wear and at what is the remaining useful life of the tool when we say a tool fails about in a 500 microns etcetera. So, how much time it would take for the tool to fail and this analysis was done through all the sensors taken together in the artificial neural network because it would be humanly impossible or physically impossible to have a mathematical model based system where in all these parameters are taken in and compared to the tool wear rather we thought of using artificial neural network and which is very powerful in the sense it is a black box which relates pretty well to the output level condition and the input level to the system. These experiments were done also the same tool used at a very very higher cutting tool depth of cut to bring in failure quickly and such levels were done in an industry where the actual the force level the cutting speeds the depth of cut etcetera were very very high and then you can see in the same industry how this spindle is being sensor is being monitored through and vibration sensor here through a force sensor sitting on here below behind the just below the work piece and this three phases you will see the detailed experimental conditions for such an estimation cutting speed depth of cut and then and you see there are these three phases which were done in the laboratory and then the severe phases were done in the industry and these are the typical values of the forces which we are measured in the laboratory force in the x component y component because this was a milling operation every cut there is to be a force increase and decrease vibration of the spindle in x y z direction and then the sound level and the spindle current once we also measure the spindle voltage and current we could multiply them to get the spindle power and these are all functions of time once the signals are obtained we could do some sort of a feature extraction and this is entirely done in a data driven method where you can do a time domain analysis or a frequency domain analysis but right now we will focus our attention into the signals in the time driven only and typical signal we may do some sort of a feature extraction by having a typical signal we have you filter it to remove the high frequency noises and then we have the loops brought together segmented signal we will remove this and this processes and bring in these loops and then we can again filter it so feature can be extracted from the signal low filtered signal and then this condition we tried to monitor the machining features being affects in this condition for different conditions of the machining time and how the for different conditions these forces varies according force affects as a function of time for the all the different conditions and these are actually estimated by a neural network similarly for F y prediction in the laboratory and then prediction in an industry similarly for the vibration in the x direction we have again machining time because once we know that the levels are higher or not allowable then we can also always predict the remaining machining time by which this curtain tool has to be replaced and this is for the current again machining time and for different phases this is for the machining features of the voltage so all these features could be extracted and it is up to you or us how to decide and what kind of signal features to extract or use for our data driven fault detection and this is for the power and similarly for the sound pressure level now once we have all this data and the features extracted we now will decide on what to do with this kind of data as I was telling you in the artificial neural network based for distance system we have certain amounts of inputs and certain amount of output in this case the inputs were the RMS force in x y direction the process parameters like the depth of cut the machining time cutting speed etc spindle rotation and then the spindle power and then we used artificial neural network with these conditions and try to develop an model and just to predict the force features we took number of data sets and the inputs are fx fy vcs0 we could estimate the tool where in the sense certain amount of training were done test data were used and then validation were also done and we can estimate that what is the this is the training with the test data and we have a good sort of training data with the measured values so we have established an allowable or I would say a reliable neural network model for doing such prediction and just to tell you that the filtering was done through a 4th order filter and in for the raw signal and the feature space it was a 2nd order filter so raw signal filtered signal and then single low filtered signal. So once the filtered features were used we in phase 1 phase 2 phase 3 and these are the cutting forces and there is a current and we could have the training of the neural network by these inputs so once we have the laboratory and industry results I we could estimate the tool were microns in microns for the laboratory case and for the case of the industry okay and we will know at what levels that this tool is to be replaced only through a such a model again we did again the sensor fusion in the sensor not relying on just only on fx fy or current but taking all of them together okay and then we are trying to estimate the tool where for the different cases the different parameters have been used and then we could do a better estimation of the model with unfiltered features somehow sometimes the stator is more so while using artificial neural network for a data driven for detection techniques it is always necessary that we do some amount of signal tree processing before applying such models and once we do the filtering you see this variations are much smoother and then we have a better prediction. So in this ANM this systems developed different strategies were implemented and force based strategies and for all the five phases gave us a prediction error of we have sensor fusion we could have cutting force we could have the vibration and we have the current okay. Now right in the beginning I had told you that we are also using parameters like acoustic emission overall sound because for a machine while we are trying to assess its condition we were pretty liberal in the time in terms of the sensors and instruments to be used and then during the process of measurements we saw that some of the parameters which are being provided or measured did not correlate well with the observations and there were certain random fluctuations okay. Now to avoid real estimation errors we did couple of things we did signal feature extraction in one case there was filtered data unfiltered so once we have the filtered data it eliminated the high frequency noise okay and then we once we have the unfiltered data the prediction was very good and we had a better prediction and we also avoided using the acoustic emission and the overall sound in the measurement method because the predictions were not up to the mark and in fact I will go back to one of the slides before. For example I focus my attention here there are wide amount of variations in the sound level with machining time and there is not a strong correlation between the measured sound level of course in a voltage level given here to the machining time and such a feature was actually not used because as you know sound gets easily contaminated from the background noise because of high presence of background noise SPL contamination occurs. So the signal to be monitored or to be carefully chosen that is very important so in this experiment of ours actually we though we measured acoustic emission and overall sound and in the latest stages we did not use them for the estimation of the artificial neural network because of the fact that they were contaminated and then we are not giving in signals which are only representative of the machine or the process because as I was telling you an ANN model if certain levels of inputs are given and I obtained an output if certain inputs are very erratic having lot of random errors I would not say that ANN model will not be able to predict the output correctly but I would like to have a robust model which would eliminate certain random errors so in this case we decided not to use the SPL and the acoustic emission signal and then if you go back to the cases of when we used FX, FY, current and voltage the predictions are much better compared to just measuring just the forces. So sensor fusion is also very important in the sense in this example you will see when the force based strategy test where for all 5 phases are conducted the prediction was 8% within 8% but only when current based strategies were used the prediction error was 14% which is very high but when we used sensor fusion using force, current and voltage the prediction was within 6.5 so prediction error is reduced okay. So in summary to do fault detection isolation and identification two important strategies are used one is the model based fault detection method another is the data driven or the signal based detection technology and in the example we saw that sometimes a combination of them is used sometimes just an feature extraction followed by a data analysis and then using a mathematical tool like an neural network can be used to predict the remaining useful life of the machine component. The example which we discussed we talked about the cutting tool single point cutting tool and then we decided that this single point cutting tool can have a remaining useful life predicted on the neural network model and in the case of cutting tool and now we used to the remaining useful life as 350 micron for example I always get this question posed by friends in the industry which is the right time to remove a cutting tool from the machining operation because sometimes people do this from the workers experience the operator they know their experience that the workpiece parameters the workpiece surface finish is not up to standard so then they are saying that something is wrong with the cutting tool it is time to change the cutting tool out of experience out of the machining time people have developed the strategies but if such simple neural network based models could be developed wherein we just monitor the machining parameters or the tool vibration or the cutting tool force put it in a neural network chip in fact nowadays modules are available with programmable functions for neural network wherein all this data which has been measured by signals can be put into this chip and this chip is going to give you a periodic warning as to know when this cutting tool is to be replaced and so on. So, fault prognostics or diagnostics has come a long way than the historical data from just an overall alarm level and the today's world we talk about using model based fault detection techniques using artificial neural network using wavelets and other signal processing techniques for doing a more robust detection of faults in systems and of course estimating the remaining useful life. And then in this example which we saw so a sensor based fusion for filter data also gives you the best value unfiltered and filtered so sensor fusion is another area which is being used for a robust fault detection and identification in machineries thank you.


Hi, everyone. Good to see you all again. Really excited about this afternoon's program. But yeah, it's my great pleasure to introduce Holly, Holly Ruth and Gailman. She is of a huge name in civic tech, so I don't really think she needs much introduction. And it's absolutely fabulous to have her here as our kind of keynote in a kind of fireside chat. I was terribly, terribly desperate to get a fireside background, but it really, it didn't work. Basically, my face had the flames on the breast. It looked like the devil. That's scary. So I'm sorry that that little bit of novelty isn't available to us, but no, it's still, I'm so, so pleased we've got Holly. I'm a bit gutted. I would love to have actually sat in a room and had a nice glass of wine in a chat with you. But in the absence of that, yep, so Holly has just written this book, Civic Power, Rebuilding American Democracy in an Era of Crisis. I thoroughly recommend it. It's a great read. And I'm pretty sure I got this off Amazon. I think that's the best place to get it, Holly. Okay, so it's available on Amazon. And so yeah, if you don't mind, Holly, do you want to, is there anything you'd like to kind of do a little bit of an intro before we dive? I just want to say good morning to everyone, and good afternoon, and thank you so much for having me. You know, big thank you to everyone joining this conversation. It's really awesome to be scrolling through the zoom and seeing so many people that I respect and admire across so many different continents. So that's a real testament to this community and a huge thank you to everyone at my society, who really pitched in and made today possible. And a reminder just of, you know, the resilience and agility of our community and the ability for us to be adaptive and to try to respond and learn and grow from this crisis. So I'm really happy to be here. As they mentioned, please add your questions to the Slido. And, you know, I should add, there was just an excerpt of the book that came out in Stanford Social Innovation Review. So you don't even need to buy it. You can just read the excerpt. I'm the worst at selling books. But I'm really delighted and I'm really honored to be a part of this. So thank you so much for having me. Well, absolute pleasure. Okay, so diving in. So the book's called Civic Power, Rebuilding American Democracy in an Era of Crisis. That's a very powerful title. So can you tell us just a little bit more about the book itself and why you felt kind of compelled to write it? Absolutely. So as many of you know, who have, you know, written books, these books start a long time. This one actually started almost seven or eight years ago out of work. That's good. That's the right reaction you want. It was work I was doing as part of the Harvard Gettysburg project, which was looking to bridge academia and practice and think about what we can learn from the scholarly literature, but then how we could actually help organizations on the ground. And, you know, part of what we realized through bringing these organizations together and sort of working with people inside government was the lack of planning and bandwidth to think about these larger structural questions, because that's just the day to day of the reality. And so I think for us, this book was, it started out as a project way before we saw the rise of leaders like Boris Johnson and Donald Trump to think about where are these underlying fissures in our democracy and where are their inaccessible political power and also economic power and how they're related. And then right as we were sort of finishing up the book, we saw in the United States, you know, the rise of Donald Trump. And it really sort of crystallized for us how these sort of right-wing populist moments, they are, they're not just this sort of, you know, quick reaction. They're actually deeper symptoms of this breakdown of democracy that we were sort of already thinking about. And so I think that's why you have this provocative title, because it really, it is an era of crisis and it's so much deeper than any one of these leaders would make it seem. So that's sort of how we got to this title. It turned out to be a good zeitgeisty kind of title. You never know how things are going to go with titles. I think it's an excellent title. I like a punchy title.  Like colon, paragraph, paragraph, paragraph. Absolutely. And yeah, one of the key themes that runs through the book is of civic or community organizing, you know, the kind of importance of that kind of strand of activity. Obviously, this is a kind of civic tech conference. So how do you see digital? What is the role of digital in that? Absolutely. So digital, for me and for my work, has always played an integral role, thinking of where we can find opportunities to really harness the power and creativity of people on the ground and then what are the roles of digital tools. You know, you see this, whether it's sort of, you know, in things like the Arab Spring or sort of movements that you see all around the globe, that when things are really successful online, they have this sort of deep backing that is sort of on the ground and sort of it's sort of the right marrying of the two. And I think, you know, we'll talk more in this fireside chat about the current moment and COVID, but I think it's a great opportunity for us to really reimagine how digital tools can be used in ways that truly build civic power. Right? We all understand because we're sort of in an inside baseball, why, you know, a Twitter hashtag is different than an E-town hall than E-participatory democracy or participatory budgeting to e-voting to any sort of number of collaborative tools. But these are not things that everyone necessarily understands. They're not things that people working inside government on the local level necessarily have a lot of experience with. And in the book, we also talk about on the government aspect, that sort of pipeline problem. And I know many of you have sort of been addressing this in various aspects, but how do you really build the next generation of public sector leaders with that dual literacy in technology and also sort of organizing civic engagement and policy, so that they're sort of integrated from the very beginning. That's I think a huge opportunity. And you're seeing it sort of trickling down in all sorts of places. But, you know, right now, if you look at this current moment, the amount of local officials, at least in the United States that I have spoken to that are just like, what do we do? How do we engage people who want to give their energy? And they want to be a part of collaborative solutions, but we don't even know how to think about it. And so I think that is sort of an opportunity that we talk about in the book. That's, yeah, and that's I think the experience of so many people in the room at the moment is totally, yeah, a very kind of different constituencies with very, very different priorities between those constituencies. You know, I think language really matters there. Different people, you know, I teach in a policy school and it's very clear when I have sort of an economist who's taking my classes and they're like, but, you know, why would you do participatory budgeting, right? It's not the most economically rational and you're like, right, but there are different reasons and different values for different kinds of norms. So you have to think about what do we value? And if you value inclusion, responsiveness, equity, those are their own set of values, but we need to be educating people. Or for example, on this question of digital tools, you know, so many of the people when I was working in the Obama administration on this stuff, you know, they wanted to do engagement, but they didn't have the institutional support, their direct superiors didn't give them enough bandwidth, they weren't given that opportunity or it was tacked on as an additional thing on an already very busy plate. And so I think we have to think about at least on the government side, and I think also on the civil society and social sector side, what are those institutional incentives that foundations, that organizations, that government are creating to really enable more creative deployment of digital tools to engage the citizenry? That's yeah, that's really, really interesting because I mean, definitely in the UK at the moment, we're seeing lots and lots of initiatives about, you know, getting people to participate, getting the kind of, you know, public intelligence into either local government or national government in the form of consultations or citizens assemblies. But then people have, is there a risk of that being hollow because that's actually not plugging into decision making properly? Absolutely. There's so many great experts on this in this, you know, meeting right now who who study this and whose work I really admire and respect. There, people know when they're being given something that is lip service, they know when it's just PR. And so we really need to think about ways that there is some power at the table and that, you know, going back to why this book is called Civic Power, there has to be something at stake. And that can be very challenging, especially what you're seeing in many of the Western democracies is what I call the two-way trust deficit, right? People inside government do not trust their citizens.  And citizens don't trust their government. And for especially vulnerable traditionally marginalized populations, there are real concerns and there are real risks here. And so when you begin with that trust deficit, it's very hard, I think, to build genuine modes of engagement that will genuinely empower people and put some decision making at the table. There has to be something up for grabs in order for this to be meaningful engagement. It doesn't have to be the whole pie, but it has to be something. It can be something as small as a park bench, you know, a rec center. I've done a bunch of research in Philadelphia where they leveraged soda tax, the money from the soda tax as part of a huge initiative called Rebuild to reinvest in public libraries and recreation spaces and to really give some of that control back to the community and to think about it through an equity and inclusion lens, how to make sure it's not just the usual suspects who are attending these meetings who tend to be, you know, more white, more affluent. How do you really think about doing engagement differently?  And now take a look, it's the most important public space that we have. So there's sort of a lot of connective tissue here, but there has to be something at the table. And so if you do a consultation, whether it's online or in person, and it's sort of shallow and hollow, you run the risk of furthering that trust deficit that I was just talking about. And I think what we want to build is positive loops, positive cycles, not negative cycles that sort of further erode the trust that people already have. Totally. And I suppose, how is it, how do we actually encourage people then to to kind of organize in their communities and to, you know, make the effort to engage? Because participation, engagement, you know, these are things that in an ideal world, we would all do. And all of our citizens would be interested and enthusiastic about. But I mean, speaking as a private individual, I do not finish work at the end of day and log on to my local government website and think, oh, I can't wait to respond to it, to a consultation.  So I mean, how do, especially people that are working, that have families, that lots and lots of responsibilities that don't feel like they have time necessarily to invest in this a great deal. How can we get those people involved? Because awful lot of the time, those are the people that need these kind of services the most. It's a great question. Now, it's a really important question. And it's, it's a big challenge. And I think there's a, there's a twofold answer to it. You know, one is sort of reducing the barriers to entry. And I often think about offering multiple entry points for people. So we really need to think beyond this one size fits all engagement model.  So then how do you design a process that can plug into that ability? And it's been interesting sort of in this moment of crisis, seeing people who have skills, thinking about can they sort of barter those skills, either to donate, raise money for charity, you know, give 20, 30 minutes of their time in these small chunks, right? To answer your question, part of it is we have to be much more creative with how we're engaging people so that it can't be such a high, it can't just be, this is the only day and you have to come at this time, and you have to stay in this way, it's otherwise you can engage. And that's what we've done by the way in the United States with voting, right? And so it's not, it's not, it's not an accident. It's by design that it's not an inclusive process. You know, you know, God willing, maybe one of the silver linings in the US at least will be sort of a turn to mail and voting. These things don't, the way the processes run now do not have to be the way that they run, right? The way that your ward or your council is engaging you right now does not have to be the only way that they can do it, but we really need to inject creativity. And I think there has to be sort of a demand signal from the constituents that, you know, we actually want to be a part of things. Doesn't mean I can come for two hours every Thursday, but it does mean that I would give, you know, 10, 15 minutes here if I could, right? That's kind of how we have to meet people where they're at. And look, the tech companies have figured out ways to do this, to harness that kind of talent and expertise. I believe that we can do it in the civic and social sector, but it's going to create, going to require new creative solutions and new demand signals. Right. And it's interesting that you kind of mentioned the kind of tech giants as well, because obviously on an institutional level, many governments as you said earlier are massively struggling with upscaling their employees, even thinking about how, you know, in an abstract fashion about how they can do these things differently. Is there a role, do you think, for the tech industry to kind of move into this space a bit more, or is that the worst idea in the world? You know, listen, you know, obviously we're in a community where you could ask 10 people and get 50 different answers on these kind of topics. They are hot topics. You know, I believe personally that there is an opportunity for some of this cross sector collaboration. I was just reading last night, you know, some of the work that Sidewalk Labs was doing to think about how to respond to COVID and how they're now partnering. And I know we have folks from Sidewalk. I see Ariel and maybe others, you know, I think there is an opportunity. I think what at least has happened in the U.S. is that the, I keep on using these very weird analogies of food metaphors. I guess I'm sort of hungry. The pie has been very inverted, right? So it's sort of, there's so much power with these tech companies. And we haven't seen a lot enough, you know, regulation or concerns about privacy. And there aren't public options, right? That's sort of, for me, the missing piece. You know, again, I sort of know the U.S. the best. So I'll stick with what I know, but I'm sure it's relevant to many of the people around the globe here. And it's so awesome to have so many. I love seeing Croatia, Poland. It's fabulous. So, you know, we're moving to online education as schools are shuttering. So in Prince George's County, 20 minutes from, you know, the heart of Washington, D.C., a quarter of the students don't have broadband access. So they're not even giving digital online tools. They're saying we can't even do that. We already face equity challenges. We're going entirely on paper, right? And so what happens when that's one community and then you have other communities that are going to be learning all this great content on Khan Academy and have all this access? So, you know, there is a, there is a say, you know, a stopgap measure to say, you know, can we get, you know, companies to be giving free broadband, but isn't there sort of a deeper fundamental normative policy question of how do we really invest in communities? So we have public options so that we can work in concert across these sectors. So we're not so reliant on one sector that there's other sort of diversification within the ecosystem. That's sort of what I would like to see. And then I think we could really have productive partnerships across these sectors, but with a guiding principle of sort of the public policy norms. And do you think, I mean, at what level, I suppose, of government participation really should, should we be pitching at people and pitching at government? Because I think an awful lot of people tend to start getting interested in policy and engaging when it's something that immediately affects them in their personal life. But again, you know, because of that there are these layers of government, different responsibilities lie in different places. Most people have no idea, you know, where powers lie for what, for instance, which is why my society and other organizations like us primarily exist because people had no idea where to go for help. I mean, is there an ideal kind of level where you can like try and engage people? Or is it just so different that, you know, some people will always be more suited to engaging at these kind of bigger national level policy areas, whereas maybe lower level people skip, sorry, people with lower level digital skills, that might be more of a kind of local thing. It's a great question. For me, it's never an either or it's sort of a yes hand. Improv, wow. Yeah, there you go. You had to leverage all the metaphors. I think there's no doubt to me that we have an opportunity on the local level to really reconnect people to decision makers, in part because it's very visceral. There is much more connections. You're seeing these things.  And, you know, at least in the United States, you're seeing sort of at this moment sort of states and cities really step up in this moment of crisis. That being said, how do you sort of, you know, leverage that power so it's building upon something? There are, of course, opportunities that cannot just be constrained to the local level and policy questions, especially when you're thinking about things like regulation, which is a real international question. These things have to be more federated. I think it needs to start local and then it needs to build. And I also have seen just in my research the sort of, you know, the mouth feel, the visceral experience of working on the local level and how satisfying that can be. And I think especially as we're thinking now, how do we leverage digital tools? How do we really engage people? Starting with what they know and who they know and how they know to do things, to me, makes a lot more sense than starting with these sort of national, hairy problems that are just a little bit further removed from the everyday of people. Cool. One last question for me before I move on to Slido because there's a lot of activity. Great question. Thank you. So you did an article a couple of days ago talking about the current coronavirus crisis. Amazing that you guys read anything I write. I'm so sure.  Thank you. Well, you know, it's good preparation for this, but you know, all content is good content at this point, I think. But yeah, so, you know, you had some thoughts in there about the kind of unique challenges that we're facing at the moment and, you know, the role of technology and the risks of using technology in terms of exclusion. Any more thoughts on what we can be doing, what you'd like to see us as a kind of fear doing in that? It's a great question. I mean, I think a lot of the expertise that's just in this conversation alone is super valuable for really helping people position to think about how they can be sort of agile. A lot of people don't even know the tools that they could be using, should be using, how to be using it. And I think the bigger question now, especially for this community is how we then marry that technology with the right kind of problem solving. So for example, I'm working with a community right now in the US and they are trying to think about repurposing some university spaces in this moment of crisis. So is it repurposing the food stipends that students get because the dining hall is closed and then opening up the dining hall as a kind of, you know, essentially shelter for the community, right? And that's a really, that's sort of an example where it sort of lays out the sort of, it's a little bit beyond how I usually think of civic tech. It's really connecting civic tech to local service delivery, but sort of circumventing government. So it's sort of this really interesting mix of a lot of the things that people in this room think about and talk about, but it's very actionable and it's very concrete. And then I also think we need to think big picture, you know, can we think about this moment of crisis as a way to reimagine the kind of communities that we want, the kind of spaces we want, the kind of online spaces, you know, I've done a lot of work on thinking about cities. And I think this moment is sort of showcasing, you know, some of the vulnerabilities of cities, whether it's our car based lifestyle, you're seeing some cities now opening up the car lanes for pedestrians, you know, just thinking about all of these things that we take for granted, because at the end of the day, people do not want to live isolated. They don't want to be atomized. And if this might be, you know, who knows how long social isolation is going to last, we need to think creatively and quickly with some ways to really have people feel connected. And especially for those, you know, for whom they are not digitally literate, you know, I'm thinking here across the spectrum, but I have a lot of friends who are social workers who work with elderly populations who tell them, please still come, I would rather take the risk than be isolated, you know, by myself all day. I have no family. My social worker is the only person who comes in my life. And so if that's sort of our there's a lot of different constituencies in this moment, but how can we sort of be responsive to a lot of these different groups? It's a very big question, but I do think it's an opportunity to learn from crisis to kind of rebuild the kind of civic tech, democratic infrastructure that we want.  And it's, it's, it's not a very, very short term thing that kind of in the long term, you've, you've touched on it a little bit there, you know, in terms of reimagining how we might do things. Is this the kind of almost perfect time for us as a community to be, you know, throwing all our kind of energy and all our innovation behind that so that kind of it might have a longer term impact on changing how democracy works on how institutions respond to citizens, that kind of thing. I do. I really think so. I think what you're seeing in this moment is how much people want that responsiveness, how they want to be able to trust their leaders, and they're frustrated and they're scared when they can't, you know, they want more inclusive systems. They want to be a part of the process. People really, I feel like they want to help their neighbors. They want to pitch in. There is this sort of civic spirit that has been maybe dormant, maybe, you know, I also love my Netflix, you know, maybe we sort of, you know, just, you know, we got accustomed to a lot of things. And this moment is a way to say, let's, let's break out of some of these molds. And there was so much expertise, you know, in this call alone and in our community. I do think it's an opportunity. I also want to be sensitive that people have a lot of things going on in their own personal lives that, you know, can make this moment challenging. But I think, and I'd be happy, you know, after this conference, or, you know, to keep this conversation going of how we as a community can engage, because I do think it's really important and I do think it's of value right now. Hey, just looking at some of the other questions, I've tried to build some of the Slido questions into the questions I've been asking, but there's one here, which is quite got a few votes. What can we learn about motivation and psychology when designing participation tools? So Danielle Kahneman brought psychology to economy. Should we as a community be using that too? It's a great question. You know, I think there's always sort of a push and pull. I have often had heated conversations with folks and the sort of thinking about how much we want to be pushing these behind the scenes levers versus, you know, more engaging people in a sort of participatory way. So I think it can be a yes and my own inclination is to think about what the right mixture is, sort of not only just thinking of sort of engineering in the back end, but also making things visible, because I think on a very meta level, one of the big challenges, and you sort of spoke to this is that people don't know what is public and what the public does for them. They don't know what their government does for them. They don't have a sense of where civil society or philanthropy plays a role. Don Kettle, who's a political scientist, he calls this sort of the interweaving of the public and the private. I'm using this graphic here. So it's sort of very blurred. And so my always, my always, my concern is just sort of, we want to make things more visible. We want to showcase to people. So we don't want to only be using things that are sort of hidden back end tools, we want to also show them that they can be a part of co designing, collaborating solution. So I think it is definitely a tool in the toolkit. But I also am I personally am interested in a holistic set of tools that also engage people so they can actually be deliberating and co deciding and co designing. Great. And just maybe one final one. And as we did say yesterday, there's always more questions than we have time to answer live. But if we can forward them to you afterwards and maybe in the next few days, you can get to them and we can send them around the community, that'd be great. I think yeah, just one last one here. And this was quite, I really like this question actually is working on the local level, a good way of making change while sidestepping the kind of person or people in charge at a national level. Whatever do you mean, why would someone want to do that? I think it is important at the local level, because I think you can develop these bonds sort of in three ways, right, with your community members.  You can develop bonds with your elected officials and your and your public bureaucrats, which sort of can really change the way you that things operate. And you can develop new appreciation and engagement with your public spaces, with these physical spaces. So I think on those three levels, there's kind of an ability to create these sort of, you know, connective tissue and build those ties that I think are really valuable. It's always not an either or ideally you're building your civic muscles. And then those muscles can sort of, you know, help you on a variety of levels. But in my mind, it has to start and the local has to be a component of it. Great. Okay.  What's what's next for you? What's consuming you for the foreseeable future? Well, so it's a lot of this work. So I'm doing a big project right now with mayors from all around the globe, 130 mayors and their staff. It was originally about, you know, reimagining civic engagement in these cities. And it's sort of it's still going to be that, but it also is taking on a flavor of COVID-19. So really thinking about where are the digital opportunities? What are the tools? What are we learning about our cities? And how does this really affect I mean, these mayors there, I mean, I'll be, you know, in and out on that today, like these mayors are in a crisis of leadership, it's a crisis right now, and it's a leadership opportunity. And they really want to tap into their constituents and engage residents in new ways. And so this is sort of what I'll be working on and then how do you build from this crisis to really learn what the lessons are for deepening civic engagement in the day to day operations of city government and working really closely with community organizations. You know, that's and that's part of the book too, is that we have this hooks and levers, which is about, you know, civil society and government and how you create hooks and levers so that things coming from civil society actually change the way government operates. And then it sort of goes back with a feedback transparency loop. So that'll be what I'll be up to for the near and the long term, I guess. Well, sounds fascinating with the flavor. I love that with the flavor of COVID-19. The secret ingredient for this research. Right, I would happily stay and chat and ask you those more questions for the next hour, but we have we have to keep schedule. I will get. The schedule is amazing. I'm super jazzed. Thank you. This is wonderful. And these questions were great. Well, thank you so much for joining us. I know it's a lot earlier where you are than it is here. And you already made so many difficult arrangements to get Iceland to be here in person. So we do appreciate it. Thank you so much. We'll be in touch. And yeah, we hope you can stay with us and enjoy the rest of the afternoon. Thank you very much, Holly. Thank you so much.


Hi there, I'm Sandy Alnok, artist and paper crafter here on YouTube, and I'm going to show you how to draw your own bird using a stamp as a guide in Prismacolor pencil. Sometimes you need a specific kind of bird for a card and you can use a really great generic bird like this one from the Life is Lovely stamp set from Flora and Fauna. And I'm stamping in walnut and manatee from Lawn Fawn. You can use any dye inks. They don't dry really quickly. They don't set up on the surface and you don't even have to do anything other than stamp them straight onto the card base. And I have the walnut for the sentiment and the lighter color. You can use any light color. You can use a yellow or a blue or especially something that's related to the bird that you're coloring and the flowers that you're coloring and stamped your images across your cardstock. I'm using some plain old Nina cardstock, but you can use any cardstock that you've got because pencil works on a lot of different things. And I'm going to make my bird blue. You can make your bird any color you want and you can change the markings because you see how well this blue goes right over top of that light ink and here I can use the basic shell of the bird to adapt and make it whatever bird I want. If I wanted to do a bird with certain kinds of stripes on it, I could adapt it. The only thing you wouldn't be able to do would be to put white tips on them unless you're gonna make your white really really bright. You could actually use a little bit of acrylic if you want to paint a little a few spots of white on top of it after you're done. But I'm gonna make my bird mostly blue and I'm gonna use a couple different blues to add some shading to it. And I'm adapting his body a little bit, making him a little bit fatter as I go. And I'm giving him some shading around the wing so I can give some just some dimension to that instead of just doing a solid color. If you want to do this with other mediums, if you want to do this with Copic markers, you can easily go right over top of this as well with your Copic markers. Here I'm adding a little fuzziness to the bird's head. If you're gonna use watercolor, you'd have to use a really good light color because watercolor if you use an ink that's not going to run, I guess, then it's going to stay there. Otherwise, you could use Distress Inks and and be able to move some of that color. And that way you can adapt and do the same kind of thing.  Adapt the shape of his shoulder. So pull up whatever bird you want to make him into, pull it up on Google and find one that's at the same angle as your stamp. Like this is just a really generic side view that we've got going here and follow along. This particular bird that I found and it was some sort of a blue bird in the south. I don't remember exactly what bird it was. It was just a really pretty little one and I've attached his eye to his beak. So look for little details like that because those will carry the realism of what the bird is going to look like on your card. And he's got a little white underbelly. So I'm going to get lighter and lighter with my pencil as I get down to the base. And then I need to make sure that there's not a whole lot of dark color down there. That sort of thing. This bird also doesn't have any feet, which is great because you could draw them in if you need them. And what I decided to do was pull one of the leaves in front of the bird.  You can kind of mask it out and cover right over the base of him. So you don't have to worry about where he's sitting. So I'm going to put another one of my leaves right up here on top. Just going to draw an extra one because now I have that shape from the other ones. I can just see exactly what shape it is and I'm coloring it flat. I'll add some dimension later, but I'm going to color in all of my leaves in the same fashion. I'm going to use a brown that's the same kind of a brown as my sentiment. So I'll make my branch that goes in between all these different parts with that brown. And then I'll go back and start really working on the rest of my leaves across the card. And I don't want to bore you with having to watch all the leaves. So we're just going to watch a few of them and then I'm going to take a different green and create a half a leaf shadow and don't stress out about whether or not it's in the right direction from the light when leaves kind of cascade around on a branch. Sometimes they actually are opposite what you would think. So most people, when they look at it, their eye is just going to fill it in and it's going to make it seem like a real leaf just because it's got a little bit of different color on half of it. So no worries there. It's a way to make it simple on yourself, but also get the fun and the joy of coloring. When you do this no line coloring with pencils, it's really fun because people think that you're more of an an artist with a blank piece of paper than you really have to be because you can follow along with these stamps. Hopefully eventually you'll get the hang of how you draw leaves and flowers and things and be able to do those yourself. But stamps are a great help in the meantime. I'm using my brown to add a little detail onto my leaves and look how realistic they look. And all I did was cover half of the leaf and then add a little bit of the the darker color and the the brown. All right, so I'm adding a little bit more detail now onto the bird since I now know where the leaves are going to be sitting up in front of him. I'll color his tail a little bit, give him some darker tail feathers underneath. And then we'll be on to just working on the flower once our bird is set in place. And with the flower, I'm going to make this really simple as well. I'm not going to worry about where the shading goes or anything. I'm just going to put a yellowish color on the inside of the flower, not worrying about where the sun is coming from and where the shadows are going to hit and that sort of thing. But I'm just going to put some color toward the center of my flower and get a little bit darker as I get to the center. Now, one of the things I do with color pencil, if you've watched many of my videos, is I use a very sharp pencil and the pencil sharpener that I use is a quiet sharp. It's a really giant pencil sharpener. Most people, when they get it, they're very surprised by how big it is. So you got to have some space for it. But it's a really good sharpener because it has auto stop, which means it's not going to chew up your pencil.  If you have a nub on the end, it's going to be hard to get down into the fibers of the paper and to make that texture work. So I'll do each one of my flowers kind of the same sort of way, just with some of that yellowish color on the inside. I did pick a duller yellow rather than a bright color because I wanted the bluebird to be the brightest thing on the card. Now this flower is a little different than the others. It has these overlapping lines. And so what I did was try to make it look like they were almost transparent. So I'm coloring every other one. So you have some areas that look like they're laid on top of each other. And it's almost a little bit on the transparent side, which is kind of cool. And now I'm going to take that same brown because it's going to tie the whole thing together if I have a little bit of that brown color in my flowers as well. And I'm going to add a little tiny bit of detail toward the inside of each flower and maybe around some of those outside edges. Just pick a few, don't outline the whole thing because then you've defeated the purpose of hiding your lines. But if you make some of them darker, the other ones almost visually get lighter. They almost start to disappear. And now I'm just going to add some of the little parts on the inside, those little details, and make sort of matching ones on each flower. Even if the flowers in the stamps don't have exactly that pattern to them, you can make the flowers feel like they belong together by adding some features that are the same on each one. Because you can see that the petals are different on each one. So you can make them all very different. But on a branch, they would pretty much be the same flower on one branch because we're not talking about a bouquet here. So I'm going to add a little bit of detail to the inside of this one. And this leaves me with a very simple and beautiful single layer card. I rounded the bottom edges with a corner rounder, corner chomper. And that was it. And it's one of those nice things that you can stamp ahead of time.  You can do this while you're sitting in the car waiting for somebody. Lots of different things you can do by preparing ahead to make a card like this. Feel free to click on my face to subscribe to my channel, watch some other videos while you're here. And I will see you guys later. I hope you have a really great day and go out and color a bird yourself.