And welcome again to yet another OpenShift Commons gathering. And today we're doing this session at an ACPAC-friendly time for once. And I'm really pleased to have Clyde Sugiyama from our Red Hat Technology Office, who is going to talk today about multi-access edge computing and OpenShift. And we're going to go for about 40 minutes of talking. If you have questions, please ask them in the chat. And then there'll be some live Q&A at the end. But this is a new topic for most of us, so I'm really pleased that you're going to get Clyde's introduction to it. And then hopefully you'll join us again at the OpenShift Commons gathering, where some of the folks from NTT are going to be joining us as well with Clyde to talk about this in more depth. So Clyde, please welcome and please take your time. Thank you for having me, Diane. Hello, everybody. My name is Clyde Sugiyama. I'm a Senior Principal Technologist at Red Hat. I'm now working, I'm now driving the several projects for the OpenSAC-NAV Edge Computing and Edge Pass with OpenShift Container Platform or Cloud Suite. We have a plan for the joint session with NTT Network Technology Laboratory at the OpenShift Commons Gathering in Austin to talk about Tech Edge Pass strategy for cloud-native service in their Edge Computing infrastructure. Prior for that event, I will share today with you about the design for Tech Edge Pass in NAB Edge Computing infrastructure. So in this session, I'll cover the concept of the Edge Computing and the idea of how to adapt OpenShift Edge Pass in Tech Edge infrastructure. And lastly, I will share with you Pocuse case, including NTT Edge Pass Poc, that has the capability to provide platform service for industrial IoT, such as IoT robotics and connected car, VTX, on which running in the Edge Computing infrastructure. With that, let me start. There are several activities relating to the Edge Computing development. In early 2014, NTT R&D announced Edge Computing Technology concept, in which can reduce cloud application left for time in 10 milliseconds by locating the Edge server at telephage node. Cisco is also spending many times to develop the whole computing since 2013 for Internet of Everything, as you know. This also covers Edge Computing. They established OpenPhone Consortium in 2015. Also, its European Telecommunications Standard Institute launched MEC, Mac Industry Specific Group. Initially, they called the mobile Edge Computing, and they changed the name to the March Edge Computing. The spec is relating to the mobile Edge infrastructure. Mac aims to place the compute and storage resources like NAB in the 4G radio access network to improve the delivery of the content and application to end users. And this summer, Automotive Edge Computing Consortium has been established. This is a new sign. We have to aware of telecom industry and other industry have to work together for Edge Computing technology innovation. This consortium will focus on increasing the network capacity to accommodate automotive big data in the reasonable fashion between the vehicle and the Edge computing infrastructure and more efficient network design. In most of the case today, IoT Edge device, Automotive Edge device, mobile user equipment, and many other device users have to send the data to cloud or big data center and get response from them. IT workloads are running in the cloud data center, which is far from the user side. In most of the case, when we are facing two scalable issues to handle the hundreds of thousands of devices and when it comes to execute action in real time, telecom Edge Computing architecture can slow the challenge of latency, scalability, and security. We put Edge Computing system in telecom central office between customer device side and the data center side. Edge Computing system can reduce latency and the bandwidth and provide data cache, real-time complex event processing, and data preprocessing in the event that are coming out of the device. Edge Computing system can drive the communication between the device and the back end system. There are many use cases, such as industrial IoT, V2X, video analytics, and the CDN, AR, VR. It's also possible to integrate some of enterprise cloud service at telecom Edge node. Edge Computing system is structured like other data centers technology, and they have some of the same requirements. They need runtime environment, containerization, compute power and virtualized storage, and lightweight messaging technology. They need business rule processing and data analytics to process the huge volume of the data in which they are being generated by the device themselves. In addition to the network service entity in OpenSack NIV, telecom carriers will be able to provide a common service entity and to allow the user to run the real-time application service in OpenShift container platform at the telecom central office nearest to the customer side. So primary target location to run the Edge Computing is telecom central office. The telecom central office typically use multiple access technology to serve diverse customer in residential, enterprise, and mobile market segment. For residential Edge service case, customer optical access line are created at OLT, Optical Line Terminal, and carried IP traffic to the BNG, Global Network Gateway, to manage each customer's IP session. Edge Computing server can be placed behind the BNG. For mobile Edge service case, Edge Computing server running the mobile Edge platform can be placed behind the BBU, Baseband Unit. As you might know, there is a project called the CORD or VirtualCO. To virtualize the network function and to disaggregate network access technology in central office, both CORD and VirtualCO can help to save the colocation space in central office and can add additional value-added service, such as Edge Computing service, into the central office. The colocation space for the Edge Computing service in telecom central office is not unlimited like a big data center. It's depending on the location. These are the sample pictures of the telecom node that's posting at the website, denwakeok.jp. Primary target to develop the Edge Computing service is a typical central office. It is a small data center size in most of the case. You can find more than 2,000 central office in the website. Many central office has been operated by the fixed network operator who have provided fixed telephone service from long ago. Some of them still have many central office nearest to the customer side. As for mobile network operators, their primary target of Edge Computing service will be in the urban area, especially for the 5G mobile broadband service. This picture of the tower is a Dockon base station in Shinjuku, Tokyo. It's a nice building. There are many radio network controllers and baseband units in that building. Edge Computing server can be installed in Doa. But in rural area, there are many outdoor implementation in current 4G LTE infrastructure. Outdoor implementation is out of scope at this stage because no space to install Edge Computing code server. At least indoor implementation is needed for code server implementation. This slide summarizes an example for the deployment option of the Edge Computing system in teleco-central office. Small port system, mini-port system, and micro-port system. Small port system needs 5 to 10 rack space to install. Mini-port system needs 1 or 2 rack space to install. And micro-port system needs half rack space to install. In case of a micro-port system, hyper-converse node that's integrating the compute node and the storage node will be needed. In addition to the colocation space, distance from customer side is also key point that Edge Computing can deploy. This slide illustrates a hierarchical location of the central office based on the distance from the customer side. Historically, fixed network operators' central office have been located based on the consulate on the physical copper loop length, which generally means that the number of locations is determined primarily by the topology consulate, by the maximum distance, typically 2 or 4 kilometer depending on the operator. And the size of the central office is determined primarily by the type of the area service and the associated population density, urban, or suburban, or rural. Basically, it's tiered structure from access to the core. This way, the CEO aggregates the customer access line and the consulate CEO aggregates the distributed CEO. Distance from customer side is about less than 20 kilometers. Because latency in fiber optics cable is about 1 micro-second per kilometer, so it will be less than 0.2 millisecond round trip latency in 20 kilometer optical fiber network. For mobile network, it is depending on the deployment architecture of RAM, radio access network. These future runs are created by the EPC mobile packet core in main CEO that is far from RAH, remote radio head. Centralized RAM for 4G LTE advanced pro over 5G in future is aggregated by the BBU hostling site. Distance from the RAH and the BBU baseband unit, the CPRI front form is about 20 kilometer in case of the 4G LTE. And the BBU hostling sites are aggregated by the main CEO. So comparing to the fixed network operator, mobile network operators don't have many central office now because of the cost efficiency for wireless access. Instead, mobile network operator have many base station outdoor. This slide shows a candidate for the edge computing server co-location site. Mobile network operators can install edge computing server at the BBU hostling sites. And MVNO site is also available to run edge computing service. But the BBU hostling site is nearest to the customer and the device via 4G wireless. This network operators also can install the edge computing server at the edge aggregation CEO site. So each candidate central office needs space for edge computing service. As I mentioned before, there is a virtual CEO project use case in the open daylight. Virtual CEO architecture can virtualize edge function on top of OpenSec NAV and manage edge traffic with OpenDirect SCN controller. We demonstrated a virtual CEO residential service at OP NAV summit this year. In the demo, we integrate virtual VNG, virtual virtual and virtual firewall on top of the Red Hat OpenSec NAV platform and manage edge traffic by the OpenDirect SCN controller. We can use this virtual CEO software stack to integrate edge computing function. Here is the idea to integrate edge computing function in virtual CEO software stack, which is based on the edge NAV reference architecture. We can run OpenShift container platform on top of OpenSec NAV and containerize edge computing service in each port in OpenShift North. In this essential access service, user's IP session is managed by VBNG and transfer specific user traffic to OpenShift North. VNG's controller of OpenShift needs enhancement to meet each TELCO-H environment. TELCO-H environment is not the same as the internet data sender environment, which placing the load balancer in front of OpenShift. But DevOps environment can keep the same process to develop the real-time containerized application in port and provide real-time service to specific user or device through OpenShift container platform at TELCO-H. There are many open source that you can use to develop the container application and run in the edge pass environment on top of OpenSec NAV edge platform for residential access. For example, the EGYPS IoT project has a kind of edge computing project, such as Kura, Kapua, Forno, EGYPS Kapua provides a service required to manage IoT gateway and the smart edge device through a Kura integration framework. EGYPS Forno provides a remote service interface for connecting a large number of IoT devices to back end and interacting with them in a uniform way regardless of the device communication protocol. Fixed network operators have many opportunities to provide edge computing service running in the OpenShift container platform on top of the OpenSec NAV now. As for the edge computing architecture in mobile infrastructure, its MacISG is working on. The spec is still not finalized, but there are many you might know online. This slide shows the edge Mac different draft reference architecture for development of the Mac in NAV environment. The major component in the Mac architecture are mobile edge platform, mobile edge orchestrator, mobile edge platform manager. And mobile edge application and virtual infrastructure manager, which is OpenSec controller. Mobile edge system consists of a set of Mac server and the associated management entity. The Mac server is a logical entity that contains a mobile edge platform and the NAV infrastructure on which the mobile edge application run. The mobile edge platform contains a set of baseline functionality that enabled mobile edge application to run on the particular server, as well as to discover and provide mobile edge service through the service registry. The mobile edge platform is also responsible for enforcing the traffic rule to transfer the data packet to the mobile edge application, as well as to maintain the necessary DNS to discover the mobile edge application. Mobile edge application run on the Mac server as a virtual machine and designed to provide the mobile edge service. Mobile edge computing is designed to provide a multitenant hosting environment for edge application. The hosting environment consists of hardware resource and virtualization infrastructure, which is OpenSec NAV and associated management service for Mac application. There's no spec for edge pass in Mac architecture yet, but we can run OpenShift container platform on OpenSec NAV for containerize some of the Mac application. Mobile edge platform sets policy and configuration rule for forwarding user-plan traffic to Mac application by traffic off-road function. It also can provide radio network information service and other real-time context information to authorize Mac application. OpenShift ingress control needs to enhance for interworking the mobile edge platform. In terms of the logical network architecture, edge-specified Mac can be a part of ENOD-B in run radio access network or can be run on the external edge computing server like this slide. Mobile edge platform on the OpenSec NAV, in which Mac server can deploy in between run and the APC mobile core on the S1 interface. The user-plan over the S1 interface is GTPU base. Usually, without the Mac server, user's IP application traffic is carried through the GTPU tunnel. And the user traffic can be reached to the GI run or MVNO side. So OpenShift container platform can receive the user application traffic at the GI run or MVNO. This is a current feasible solution. But the GI run and MVNO is 4G mobile in more GI run and MVNO in the 4G mobile, not the real-time service. Because they are far from the radio access network, in most of the case. So what we are trying is in this diagram for edge computing service in 4G radio access network, Mac server should be deployed inline. And mobile edge platform should be transparent to the GTP and run the traffic off-road function without impacting the mobile core network. Once mobile edge service has been applied, this termination traffic pattern is an edge path model that OpenShift container platform can be run in the Mac server. As long as OpenShift can receive the specific user's application traffic controlled by the mobile edge platform in Mac server, OpenShift can handle the user's application within each isolated user network and can provide real-time response at the Mac server to a specific user or device. Usually, telecom carrier cannot modify the user's traffic in transit to telecom domain due to telecom regulation issue. So edge termination traffic pattern is right model for telecom edge path because user traffic already terminates the user's enterprise domain in this case. So we can run the virtual edge platform in front of OpenShift node on top of OpenSack NMV platform in each telecom access environment. This slide illustrates based on the edge reference architecture. And we can put VNF in front of OpenShift container platform. The challenge is OpenShift ingress controller enhancement. We have several options for ingress controller, such as HAProxy, NGX, F5, and so on. But all of them don't cover the interworking between edge platform and OpenShift service yet. Because current ingress solution is mainly for the public cloud. Telecom edge infrastructure are basically private access point. For edge computing service in 4G mobile access network, we need interworking with mobile edge platform to handle mobile session and specific data from device for specific edge computing service. For edge computing service in the residential access network, we need interworking with VVNG to handle the specific IP session from device for specific edge computing service. Another challenge to develop the telecom edge path in is multi-site deployment. As I mentioned before, telecom central office is hierarchical located in each area. You can imagine from telephone number assignment, local number, area number, and country number. It's hierarchical. Telecom carrier needs deployed distributed OpenSqt NAV in each area, like a two-tier multi-site model in this area. On top of the distributed OpenSqt NAV infrastructure, they can build Cloud OpenShift platform like a single data center across multiple central office in each regional area. OpenSqt NAV distributed compute deployment will be ready in near future, since self storage for multi-site deployment is ready. But some of the telecom carrier don't need to wait for the distributed OpenSqt NAV feature. If they can design optical fiber transport network between two CEO sites within minimum latency, this is dependent on the optical fiber network resource. Basically, if you can ask an optical fiber transport engineer to keep five millisecond latency between two CEO sites, they will design fiber route if they have an optical fiber network resource. Some telecom carriers have many optical fiber transport network resource in country, so they can design a computing infrastructure like a single data center. The key point is to build infrastructure like a single data center. Optical fiber transport engineering is important to build telecom edge cloud computing infrastructure. On top of the optical fiber network infrastructure, telecom carrier can build multi-site self storage and OpenSqt NAV. Inter-data center SDN solution is also needed. Our SDN partners like Cisco, Juniper, and Nuage have an inter-data center SDN solution. On top of OpenSqt NAV, OpenSqt's personal storage can use the OpenSqt Cinder or SafeRVD storage. As for the isolating network between each port in each node per each software project, we have many SDN partner solution with CNI paralleling. Telecom carrier can work with the SDN partner to deploy DevOps awareness network across multiple ports. And that OpenSqt SDN needs to interact with inter-DC SDN solution. Here is a part what we are working with NTT network technology level three. They implemented Red Hat OpenSqt NAV multi-site and RAND OpenSqt. Actually, it's cloud suite product that is included in OpenSqt and OpenSqt. And they developed IoT robotics controller prototype with OpenSqt and RAND IoT robotics container application import to control robot remotely. Also, they are adding the common service entity such as IoT gateway, DNS, and authentication service into OpenSqt container platform. They are now working on the Ingress design. IoT device traffic is agreed by the Virtual CPE in front of OpenSqt. Virtual CPE covers many access functions, including BNG. As for the SDN controller, they are now just using Ansible. It's not full automation with SDN controller because they want to check each network behavior at this stage so that they can design. Between two sites, they built an EVVM and managed network configuration by Ansible so far. I believe that they will start to work with SM vendor once new architecture for telecohpast model is finalized. So for further detail, we have a session in OpenSqt Commons Gathering. You can discuss with entity network technology laboratory at Austin. Please join the OpenSqt Commons Gathering. Thank you, Hyde. That's a great segue to do this. And also, there will be many more Pog opportunity to run IoT application in telecohpast infrastructure. In Ingress IoT project, I found that there are many several Pogs should be done in the edge computing infrastructure in sheet of cloud infrastructure for real-time service. I'm now starting to work with our IoT team and try to invite some party for starting cross-industry Pog on top of edge computing infrastructure that some of telecom carrier are working with us. The through that cross-industry Pog, telecom carrier will be able to get no real requirement from IoT industry. And the last thing I'd like to mention is that about automotive industry activity. This is a new sign that automotive industry is wanted telecohpast computing infrastructure. Toyota presented the 5G requirement for B2X at Empress Japan last year. In the B2X, currently, the vehicle on-board IoT gateway device sends the car's device data to the Toyota big data center through the 4G mobile coordinate. It is estimated that data volume between vehicle and data center will reach 10 hexabyte per month around 2025. This will trigger the need for the new architecture of the network and the computing infrastructure to support the distributed resource and topology-aware edge computing storage capacity. They are exploring the design for geo-distributed deployment in 5G mobile infrastructure. OK. This is a radar enemy software stack. In summary, telecom carrier can provide network resource and storage resource in addition to the edge computing to run OpenShift for edge parts. BNG as a virtual network function also can place in front of OpenShift for residential access. And the mobile edge platform as a virtual network function also can place in front of OpenShift for mobile access. Also, service provider can provide a common service entity to many third party who deploy the application entity in OpenShift container platform. So key takes away from this session or two things. We better to keep flexible architecture so that we can implement edge parts in each telecom access infrastructure by endless enhancement to interact with each edge platform. By using OpenSack NAB and OpenShift container platform, we can place mobile edge platform in front of OpenShift for mobile edge network infrastructure. And for the residential access network, we can place BNG function in front of OpenShift on top of OpenSack NAB platform. Through the collaboration activity with telecom carriers R&D, I'm feeling that the sum of telecom carrier transforming to new normal. They are going to be an ICT platform provider for new service provider who provide new edge service to users, machine and cars and everything. We have a plan for the joint session with the entity network technology laboratory at OpenShift Common Gas Line in Austin. We can discuss detail of how tech should provide the telecom edge parts on top of edge computing infrastructure at the event. I think that's all in this session. Thank you for listening. Awesome. I thank you very much for this introduction because I think this has set the stage really nicely for folks who are in the telco and the automotive interface. But also for people who are going to be in the audience for the OpenShift Common's gathering in Austin this coming December 5th. And we're really looking forward to having an ICT presentation on their great use case. I think that one of the things that I like about the gatherings is that it opens up lots of conversations. Especially the stuff you're talking about around the automotive industry because I know a large number of the big automotive BMW and Volvo and other folks are already using OpenShift extensively. So it'll be interesting to get their feedback on how this works and might work and play into what they're thinking around what's coming down in the next 10, 5, or maybe even just two years down the path. You've got all the IoT and automotive and huge networks that we're going to have to be working with and supporting. So thank you very much for this talk. If people want to get a hold of your hide, perhaps you could put your very first slide on. I think it had your contact information on it. Oh, yeah. I think it had contact. There we go. There we go. Live interactive demo. That's the demo part for here. So if you want to get a hold of hide at Red Hat and maybe connect with folks at NTT who have been listening to this and want to find out more before December 5th, actually, it takes time to get a hold of it. So hide, your speaker has just at the very end decided to put. Yeah, regarding the demo, actually, NTT and NTT have the demo tool to control the mini robot. It's a nice demo, but it takes time to prepare the demo. We can discuss with NTT and NTT prior for the common gathering. That would be cool. All right. Well, I'm going to say thank you and sign off now. And thank you.


This research explored the evolution of trust between public and private sector partners in the context of Project Last Mile, PLM. Trust was seen as essential to the success of the project, which seeks to translate the business acumen of the Coca-Cola company to strengthen public health systems in Africa. Through qualitative analysis of interviews with key stakeholders, the authors identified five domains that were foundational to building trust, reputational context, team composition, tangible outputs, shared values, and effective communication. These findings suggest that trust can be fostered through careful consideration of these factors when designing and implementing global health partnerships. This article was authored by Sarah Christie, Teresa Shaheen, Leslie A. Curry, and others.


In a modified form with clearly defined geometrical proportions, this quadrilateral may now serve as a reference model for the definition of the articulation of further vowels. The proportions of this reference model or coordinated systems are clear and this is how to construct it. First we need a top line which is four measures in length and it is drawn horizontally. Then we need a second line which is the right hand vertical line which is three measures in relationship to the four measures of the top line and the angle between the two lines is 90 degrees. The bottom line is half as long as the top line and again we have an angle of 90 degrees between the vertical right hand line and the bottom line. And finally we now link the three ends of the two horizontal lines so that we get the basic dimensions of the cardinal vowel chart.


Hi, I'm Witold Wiencek. I'm a statistician. I work on applied research in health and in development economics. I'm a consulting director at the Development Innovation Lab at University of Chicago. And this is a short talk where I'll be showcasing Bagger, which is an R package for Bayesian meta-analysis, which is a stand, the most popular Bayesian modeling platform. In this talk, I want to talk a little bit about motivation behind creating the package, show a few simple examples of how it's used, and along the way, highlight why meta-analysis and Bayesian inference make for a good combination. Before moving on, I want to give credit to my friend and co-author, Rachel Meager. She's an assistant professor at London School of Economics. In fact, the package was motivated by our shared interest in real-world applications of Bayesian methods, especially meta-analysis. As Bayesian statisticians know very well, all kinds of meta-analytic methods have already been implemented and implemented very well even 20 years ago, for example, in Weedbox. So I personally think that the market gap in terms of Bayesian tools for meta-analysis is less in building new capabilities and more in avoiding errors and increasing access. What I mean by this is that we live in a world, I think, where meta-analysis is more and more used as a kind of a simple plug-and-play tool. And this means that there are more users who will have wrong interpretations of models, overconfidence in models. And generally, we end up seeing all kinds of garbage in, garbage out problems. And because Bayesian models are more technically sophisticated, this problem compounds when we move to Bayesian meta-analysis. So this package is built for a particular group of people with particular goals in mind. People who understand the advantages of using Bayesian models, but they might not have technical skills. And they might not be statisticians. They might be casual R users. The four goals, therefore, are to implement all of the basic models, focus on making them accessible and allowing people to criticize models, help them avoid Bayesian mistakes when they're likely to occur, and still keep this framework flexible enough so that we can extend it to as many models as feasible. However, the goal is not to build a power tool for people who would already be able to build their models by hand, as it were. So moving on to an example, I will use a very simple one. Bagger also has methods for working with binary event data or quantiles or zero-inflated data, although some of those things are still work in progress. But I want to use a canonical Bayesian example from Donald Rubin's 1981 paper on SAT improvement in eight schools. And this is a nice way of highlighting how a meta-analysis model is also a form of Bayesian hierarchical model. So as is typical, we only have aggregate data. Each study measures mean and a standard error, Y-I-S-E-I. And then at the upper level, though, the true effects, tau-i's, may come from a common distribution. How they relate to each other is regulated through sigma parameter heterogeneity. So sigma equals zero, Bayesians would call full pooling. That is the fixed effects case of meta-analysis. Sigma equals infinity means no pooling. That's no meta-analysis, no borrowing of information across studies, and anything in between is partial pooling or random effects. Our objective as Bayesian statisticians would be to derive posterior distributions for tau and sigma, sometimes also for distributions for tau-i's effects in individual studies, which means that we always need to specify a prior on sigma and tau. Before showing this in action, a quick recap for why we might choose to go Bayesian in this meta-analysis. There are some typical arguments for going Bayesian instead of frequencies. I won't cover those here, but few specific ones for meta-analysis. First, incorporating prior beliefs I think is a unique strength for meta-analysis because they are always conducted in data-rich environments. So for example, for a medical RCT, one can borrow information from thousands of other meta-analysis to have a prior on how much heterogeneity across studies there might be in a particular domain, for example, in an oncology trial. Secondly, Bayesian methods avoid problems with underestimating variance across studies when there are a few studies especially. And while doing that, they also emphasize uncertainty in parameters. So it's not that heterogeneity is often big or small, but it's also that very often meta-analysis it's very imprecisely determined. So Bayesian models bring this fact to the forefront. In general, Bayesian models allow us to create predictive distributions, so the distributions that tell us what would happen in another study that wasn't observed much more easily than other methods. And in general, they allow us to create any kind of derived quantity and describe them probabilistically. So for example, what is the probability that out of every study in the meta-analysis each of them had a true effect greater than X. Those are very relevant to real-world decision-making. And lastly, they also allow for easy and formalized model comparison, for example, choice between fixed and random effects. The cost of this is of course higher technical sophistication and we should be clear about this. And this is exactly what we're trying to solve here. One last advantage, which is not covered by the package, in some sense, is that Bayesian models are much more flexible in terms of meta-analysis models that we can specify, but then one would have to do this by hand. OK, so now quickly on to an example. We load in the package, take a quick peek at data. You only need R standard bugger packages in R. No extra software is needed, but you do have to have R tools installed alongside R. This is the aggregate data in eight schools. If our input data was one line per pupil in each classroom, the model would be minimally different because we have to estimate the treatment effects and standard errors jointly in this meta-analysis model. But the code that I'm going to present would look practically the same. And now this is the entire analysis in bugger. So quickly, segment by segment, we fit some kind of a default model in the first couple of lines. That's the meta-analysis random effects partial pooling model. Then typically, an analyst might consider some alternative modeling assumptions. So here, I just made up some extra assumptions about the amount of heterogeneity in data using different priors and also some completely made up example on where the mean effect might be. Once we have the models, we typically plot them. That's also one liner. We use a very plain syntax everywhere. So we use generic functions like plot and print. The specification of prior distributions, Bayesian prior distributions is done using plain text like Cauchy, Normal, Uniform, Student, et cetera. And then once we have a number of candidate models, we can compare them using specialized functions. This one is called bugger compare. We can plot or print those comparisons. We can also compare the model conclusions. So those predictive distributions I mentioned a second ago, those are also encoded through one line commands. And a very typical comparison that meta-analysts will decide to do is to compare fixed versus random effects. So one line comparison like this is done here at the end. And to formally choose between partial and full-pulling random effects and fixed effects, in other words, models we can also conduct leave one out cross-validation, which I'll explain right at the end. So now let's take a peek at the results and what the outputs look like. This is the default output from a fitted model. I didn't show the fitting process, but it only takes a second. And the user would get all kinds of automated prompts about the decisions made by the algorithm when necessary. And what we see here are group-specific estimates at the bottom. And then at the top, we have summary statistics. So where is the true effect? What is the amount of heterogeneity? What is the amount of pooling? A pooling statistic is a complement of I squared statistic that is known to anyone, probably in evidence synthesis. And alongside each statistic, we see not just the mean, but also how precise each of those estimates are. So as I mentioned, it is very typical in smaller meta-analyses to for heterogeneity to be imprecisely estimated. And this is to some extent true here as well. If we look at the 95% interval for this default analysis. Here is one of the examples of plots that we have in bugger. It could be a forest plot just as well. This is just a slightly different visual flare. Here we can see that, in fact, in this random effects model, all of the estimates are pooled very strongly toward the hyper mean, which is at the bottom of this plot. If we have different candidate models, we can compare them using all kinds of visual styles as well. This is just one of them. So here we can see that in two liners, once we have several models, we can just name them and try to plot them alongside or print them alongside each other and see how they differ in the results. Another type of comparison is to compare the predictive distributions. And here you can, by the way, see that all of the syntax for the plots is done using ggplot. So there is a lot of interfacing between our package and quite standard R tools for working with data. And here we see that there are actually some practical differences to those made up models. More practical example of model selection, I think, or the most typical one is when we consider differences between fixed effects and random effects, or again, the full and partial pooling. So here is an example of how we can do this using a one liner in the package. It's a bugger compare function again. We just say what equals pooling. And when I plot this, I can see the thing that I've seen a couple of slides back that for this simple example, random effects look quite similar to the fixed effects model, especially if we consider the bottom row here, the pooled estimate. And here, as a gratis, we also have plots of what happens under no pooling model, so no meta-analysis. But it also makes sense to test for this formally. So here are three lines where we build leave one out cross validation models, which are metrics of predictive performance. They're closely related asymptotically to information criteria that you might know from other modeling tools and from outside of meta-analysis. In this case, I measure leave one out cross validation for partial pooling model and full pooling model, and then I do a one liner comparison, which tells me that there is indeed a slight preference for fixed effects model, which we just so visually. This model has fewer parameters and fits similarly to data. There is, of course, much more, and all of it is written in pretty plain syntax. So the things that I could have been doing to examine my model here are comments such as treatment effect, group effects, draw effect draw, which is draw from predictive distribution, forest plots, other pooling and heterogeneity statistics using pooling or heterogeneity command, et cetera, et cetera. But that's the basic outline of the package. The package in its beta version is available on GitHub. And yeah, thanks for listening.


In today's video, we're going to be seeing how Rainbow Friends become Garden of Band-Band. And with that being said, let's go ahead and jump straight into the video. Oh yeah, and shout out to GameTunes. This is Band-Band's kindergarten. Oh. Once a bustling education center for the best and brightest of the city, now an abandoned dump. Which means it is the perfect place to rob. Everyone split up. Oh, okay. The newest way the place for stuff we can use. So the Rainbow Friends are at the Kindergarten. So loud and noise. Oh. Seems like Band-Band got red. Both of you are monsters. Oh. Wait, they're both scientists. The pirates have a similar backstory. Got it. In fact, I want myself. It's like they were meant for each other, dude. Nice. Are you still- does Grain turn into a big Jumbel Josh? Cause that would be sick. He's never been better. Damn. You're awake. Perfect timing. Right. What's happening? Don't worry. Great. I made us a new friend. And I'm about to change your life forever. Band-Band. Damn. Man, this place really is abandoned. There's basically nothing. Why do we- Was that green jumbo jumbo green? This isn't nothing. They're up to it, but I think we better run. Okay, so we turned them into a Jumbel Josh. Okay, so who is Blue going to turn into? Maybe it's a Captain Fiddle. Okay, so Orange is going to be Flynn, right? Disgusting. Look at it this way, Orange. It's a fun-changer pace. Nice try, Blue. We got you now. Oh, they got him cornered. Make a run for it, Blue. We must have lost him. And the naval scientist.  Oh, no, he shot him. He shot him. Yes, we get it. Band-Band. Look. Excellent work, Red. You weren't lying about your skills, so I'll give you that. Except he's purple, but okay. Oh, it's going to be Tramp. I knew it. Can never trust a math scientist. You're never leaving this place again. And unless you want to be transformed like all your little rainbow friends, you'll follow me back to the lab. I don't know what happened to me. I can't even see. I just hope the other guys are okay. You. This is all because of you. What is it? Who are you? They're blaming each other. You helped Red and that guy turn us into monsters. What are you talking about? Dude, why are they fighting each other? They're like, they could have fired their way out together, you know? Okay, so they didn't know the way? Then from monsters to monsters. You. No, it's me, Red. Ben-Ben transformed me as well. Why would he do that? Oh, he was just leaving. And it worked. Come on, everyone. Our new forms are remarkable after all. We should just stay here. Then the kindergarten can open back up and we'll all be happy. Right? Oh, nice. It didn't fall to the trick. Is it all right? I'm sorry, okay? If you're so sorry, then change us back. I, I don't know how. What? I was only able to transform you with Red's help. Then where's Red? He managed to escape after our experiments in the laboratory. I think he's in the back hallways. Please, just let me live. Fine, but there's something we got to do first. Sorry, Ben-Ben. You've been quite the bad kid. And the bad kid's going the right way. Okay, cool. I wouldn't trust this guy loose, you know? Wait. The end is here. Oh, yeah. Wait. You should never have heard you. Save your apologies for later and just turn us back. Release me and I'll do it. No way. How could we trust you? If you don't, then we'll all be stuck this way forever. Link of an eye. Now let's get out of here. Okay, cool. So he managed to reverse them. Oh, wait. That's it? What? All right. I didn't see that ending coming in so quick into it. Well, it seems like everybody got up. They managed to turn themselves back into the Rainbow Friends, which is awesome for them, because they were trapped inside of the bodies of the monsters from the Garden of Ben-Ben, which resembled their colors from each game. Which, by the way, was a cool video idea, you know? So shout out to GameTunes. I'll link the original video down below in the description. If you guys want to check it out for yourselves. And yet, thank you all for watching. Thank you all for the main support, as always. And I will see you guys in the next one.


Hello everybody, E here. Welcome back to another Retro Book Review. Today we are talking about Dean Koontz's The Fun House. This, in case you do not know, the history of this book is based on a script by Larry Block. So it is a novelization of the Toby...Toby? Is it Toby? I think it's Toby Hooper's movie The Fun House. The odd thing about this is the movie was delayed so long that the novelization came out before the movie did, and Dean Koontz published it under his horror pseudonym Owen West. I loved this book when I was a kid. This version came out in...19...June 1994. So I was 14. I remember buying it off the rack at Lucky's grocery store in Fontana, California. Either that or it was San Bernardino. I can't remember which one. I don't even think Lucky's is around anymore. Any California folks want to let me know if Lucky's is still around? I remember Stater Brothers and Lucky's and a couple other places. Instead of end caps, I remember they had these wire racks in gas stations. And I remember seeing it going, ooh, Dean Koontz, and buying it off the rack with some of my fun money. But my mom wouldn't let me read this stuff. This is still around the time of the great book closet. If you're a fan of the channel, you might have heard me reference that before. She used to keep all of her adult horror novels in a closet.  There was no bookshelves. She kept the bookshelves out in the living room. She kept them all stacked up there in the closet, and I wasn't allowed to go in there to get the books. Those were her adult books.  It was fine for her to read it, but it would, I guess, darken me, ruin me as a child. She finally let me start grabbing books out there when I was about 16, I think. I mean, even then, she had to read them first. But with this book, like I said, I loved it. 14-year-old me, he was hot for this book. It was a great book, great experience. Books like this that made me go check out some of my favorites, like Twilight Eyes and Phantoms. I tried to read this last year or the year before at some point in time, and I couldn't finish it. I was trying to read it with my friend Dully. I've been pronouncing her name wrong the entire time. I thought it was D-L-E-L-E, but she says it's like delete, delete, without the T. So I'm saying Dully. I hope that's correct. Dully, if that is not correct, you will let me know, I'm sure, in an email. Sorry, I've been pronouncing it wrong this entire time. So we tried to read it, and I couldn't get through it. It was so bad. The plot holes, the writing, it was just utterly atrocious. Now, I have went back and watched the Tobey Hooper movie again, and I love that. So I'm not exactly sure why I disliked the book so much. Maybe there's some differences in the storyline as far as the internal dialogue and the reasoning for certain characters that you don't get in the movie. I couldn't finish the book, and I don't remember enough about it, about the first time I read it, other than I loved it. But 14-year-old me probably loved it because it was very brutal, very gory. I believe there's a scene where a head rolls up to our protagonist on a roller coaster ride or something like that. Well, the movie, the special effects of the movie are terrible, but it's in a fun way. The monster's head-faced deformation of his cranium is cheesy as hell, but I enjoyed it. In a visual aspect, it was fine. It was great as a film. Because with a film, it only took up an hour and a half of my life, whereas the book is 340 pages long. If I buddy read it, we're only going about 50-60 pages a day, so that's a week of my life. I'm not going to get back. So I just ended up quitting it. If we had started reading it probably later on, when I was bound set and determined to reread all of his stuff, I would have forced myself to finish it like I did with The House of Thunder. Because if any book needed to be quit, that one was. But this one, I would recommend it to people who like cheesy horror novels. I wouldn't pay too much attention to the actual plot or the motivations of the characters. Because if you do, you're probably going to have a bad time. Not Stephen King's, oh, Freudian slip. Just like all of Dean Coons' stuff, his characters are forgettable. The plots are forgettable. In fact, there's no end to the comments on my Dean Coons' reviews that say, hey, that was one I just got for The House of Thunder where the person said, I read this not too long ago, gave it four stars, but I can't remember anything about the book. That's Dean Coons in a nutshell. There's nothing really memorable about his stuff. But if you're just looking for dumb fun, I would say this is the closest thing to a Richard Lehman experience you're going to get from Dean Coons. It really reminded me of that. Richard Lehman stuff was a little bit better than my experience with this. But it's far below the likes of, if you're talking about other paperback horror authors, far below the likes of Bentley Little and Jack Ketchum, that kind of thing. You're well below that. In fact, I would probably put it more on the line of, I don't even know, I would say it's closer to like the indie horror you're getting nowadays without all the errors.   I've worked with some fantastic editors and writers in my day and I just can't do it anymore. That's unfortunate because I enjoyed these books when I was younger. But nowadays, all I can see are the problems with the story and the writing. So if you don't mind that aspect being on the poor to bad side, then definitely check it out. But for me, I mean, I'm going to give it one star. I couldn't even finish it. So it's an easy one star for me. But if you read The Fun House, what did you think about it? Let me know down there in the comments below or in the doobly-doo. I know some of you are like, what are these comments you were talking? I know down there in the doobly-doo. But until next time, I have been E, you have been U. This has been another book review. I'll talk to you guys later. Bye-bye!


Hi everyone, Joe for jaspyscasebreaks.com with a quick 2020 Panini Prison Football Salo Pack Break number 77 with five honors football spots being given away. Nice. First the break, thanks everybody for taking the risk given this shot. I appreciate it. We're gonna do the break first and then a different dice roll for the giveaway spot part. Alright six and a four, ten times for names and teams. One, two, three, four, five, six, seven, and tenth and final time. Six and a four, ten times for the teams and tenth and final time. Alright there's the first half of the list right there and then there's the second half of the list right over here. Let's sort by column B by team. Let's just print this baby out and let's print this baby out and then rip. Here it is. Yeah there could be some surprises in here you never know. Viscous Chinalt Junior, Emergent Green. Nothing crazy here. What about here? Red, white, and blue. Miles Boykin, Amontes Sweat, and rookie Gabriel Davis. Not bad but I was hoping for some of the QB's there. Alright now let's flip back over here and let's grab all the names from Douglas and down to Tom. There's the new dice, there's the new list. Let's roll it and randomize that list seven times. So it's top five after seven. Good luck. One, two, three, four, five, six, and seventh and final time. Once again, top five after seven. So from six on down, sad times. We'll get them next time folks. In fact there is a next time. We have to do break 78 to unlock that honors break so if you didn't make it this time, feel free to try again next time, jaspyscasebrakes.com. We'll get them next time. Alright top five. You're happy because you're in the honors break. PJ, Kym, Tom, Sean M, and Sean O. Congrats to the top five here. We'll see you for that honors break a little bit later tonight, jaspyscasebrakes.com. Bye bye.