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With this outlook I realize I've been the bully. For example, icing out that one annoying girl and being rude to people that have done nothing to deserve it is on the spectrum. I also have the perspective now to realize that bullies come on a spectrum. In turn I think being mistreated has given me more compassion for my fellow human. Looking back as an adult I realize the silver lining to being treated like you're disposable, is never forgetting how it makes you feel. She was infinitely important to me in that moment and we're still close today. I was lucky, I had one friend out of that group that realized she had fallen into the "I'm not the one bullying, I'm just a by-standard" trap. I felt isolated, totally vulnerable and worthless. This helped continue dialogue on a hashtag on social media, #OscarsSoWhite.Īt eighteen the same feeling I had when I was eight came back. For those of you that don't know, Stacey Dash is also known for making many anti-feminist remarks, as well as remarks about why Black History Month shouldn't exist. Stacey Dash was selected as the Academy Director of Diversity Outreach, and made an appearance on the academy award stage, proclaiming, "Happy Black History Month," which was met by an awkward silence from the entire crowd. Stacey Dash wishing everyone a happy Black History Month at the Oscars (2016) Outrage ensued when Miss Colombia was stripped of her newly placed crown, when Miss Philippines barely received any screen time, and when it was suggested that two titles be awarded. At the 2015 Miss Universe pageant, TV host Steve Harvey announced Miss Colombia as the winner, instead of Miss Philippines. There's nothing more uncomfortable than thinking that you've won, when you actually haven't. Steve Harvey announcing the wrong winner of Miss Universe (2015) In: Proceedings of the 2012 Winter Simulation Conference (WSC), pp. Onggo, B.S.S.: BPMN pattern for agent-based simulation model representation. In: Nurcan, S., Proper, H.A., Soffer, P., Krogstie, J., Schmidt, R., Halpin, T., Bider, I. Szimanski, F., Ralha, C.G., Wagner, G., Ferreira, D.R.: Improving business process models with agent-based simulation and process mining. In: Proceedings of 2nd International Conference on Business Process and Services Computing (BPSC 2009), Leipzig, Germany, 23−24 March 2009) Pascalau, E., Giurca, A., Wagner, G.: Validating auction business processes using agent-based simulations. Zambonelli, F., Jennings, N.R., Wooldridge, M.: Developing multiagent systems: the Gaia methodology. Workflow Management Coalition: Workflow Standard Process Definition Interface - XML Process Definition Language, WFMC-TC-1025. Spanoudakis, N., Moraitis, P.: Using ASEME methodology for model-driven agent systems development. In: Proceedings of the 11th International Conference on Enterprise Information Systems (ICEIS 2009), 6–10 May, Milan, Italy, vol. 20, 251–273 (2006)Ĭernuzzi, L., Zambonelli, F.: Gaia4E: A tool supporting the design of MAS using gaia. Moraitis, P., Spanoudakis, N.: The GAIA2JADE process for multi-agent systems development. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems part 1 – AAMAS 2002, pp. Juan, T., Pearce, A., Sterling, L.: ROADMAP: extending the gaia methodology for complex open systems. Wooldridge, M., Jennings, N.R., Kinny, D.: The Gaia Methodology for Agent-Oriented Analysis and Design. ACM, Barcelona, Spain (2000)ĭumas, M., La Rosa, M., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management. Rana, O.F., Stout, K.: What is scalability in multi-agent systems? In: International Conference on Autonomous Agents. Model checking agents and multi-agent systems.This way, engineers, analysts and managers can configure the processes’ parameters and identify and resolve risks early in their project. Simulations of the defined agent roles can be used to (a) validate the system requirements and (b) determine how it could scale. The tool usage is demonstrated through a running example, based on a real world project. This tool uses a recursive algorithm for automating the transformation process and guides the user to dynamically integrate two or more agent roles in a process model with multiple pools. The method includes a tool for aiding the engineer in the transformation process. Thus, the software engineer can employ available tools to validate specific properties of the modeled system before its final implementation. In the future we may expect bidding for factions, as you could argue the player who gets first dibs on factions could have the best advantage.This paper presents a method that aims at assisting an engineer in transforming agent roles models to a process model. Playing the automa i draw a random card for it first before i choose mine. I feel all this has the best balance and the illusion of control over your decisions. The the ivits(?) Place their acedemy(or is it institiute) if applicable.Īfter that you are good, but its recommended to do the alternate passing turn order card for higher level play. Xenos place their 3rd mine if applicable. Then the last player places a mine, continue counterclockwise. The first player places a mine, continue clockwise. The first player looks at everything and decides what faction will be best. Setup up everything, the random fed token on the tech track, all the techs, bonus tiles. two orange or two blue), swap tiles, or rotate. If two faction planets are adjacent (i.e. Randomly place them, usually with the arrows in the middle of the hex tiles all facing the same direction. For slightly higher level pkay, i believe this is the intended order:Ĭhoose white number or black number map tiles. “VicinityBrew will enhance our current financial system, while adding new tools and better visibility throughout our brewing operations. Implementation will take place later this year to equip Allagash with the tools necessary to meet their growing production demands. Like many other American Craft Beer producers, Allagash is very conscious of their operations, utilizing renewable energy and local sourcing around Portland, Mane in addition to responsibly disposing of their production waste such as donating used hops to local farmers for feed. Keg Tracking saves most breweries thousands of dollars per year.īrew Ninja includes these features into each of our plans and you can see our pricing here.VicinitiyBrew will integrate with Allagash’s current financial software Microsoft Dynamics┬« GP to provide the benefits of a compete Brewery ERP system including: production control, automated excise tax and TTB reporting, yeast analysis, batch yield, centralized recipe management, quality control, scheduling, compliance, lot traceability and recall. TTB reporting saves breweries 10+ hours per month. The truly valuable features of Brewery management software are having ALL of the features. In summary,we believe that Vicinity Brew does offer a brewery software solution, but usability by your team is truly limited. Unless you're a brewery owner/manager who wants to manage everything from a Desktop PC by yourself, then don’t consider Vicinity Brew because it isn’t team based or mobile friendly. Vicinity Brew doesn’t publish their pricing on their website, but in this case we don’t think it matters much. Every person on your team can use Brew Ninja so that your brewery is successful. Your work environment will never need paperwork that later needs data entry. It also means that your sales team and delivery drivers can use the system without needing printouts. This means that you can access data from your PC or MAC desktop, Android or iOS tablet or phone. To scan barcodes you would need to purchase specialty hardware separately.īrew Ninja is a full-featured, team based, cloud software that is available on ANY device. This means that while your brewery may have graduated from using Google Sheets and Microsoft Excel, your staff will still be tied to a computer and may still need to use paper-based sheets to collect data in the work environment. Vicinity Brew but we believe that there is one killer feature that makes Vicinity Brew much less appealing than other brewery management software packages: Vicinity Brew is Desktop PC Based. We could write a longer comparison of Brew Ninja vs. This means that your brewery can take advantage of 1000’s of brewer’s recipes and opinions to easily experiment with new styles without the risk of doing it yourself. Vicinity and Brew Ninja both have recipe management functionality, however Brew Ninja allows importing from BeerXML files created from Beer Tools, Beer Smith and Brewer’s Friend. Vicinity Brew’s website really focuses on the brewing process, while Brew Ninja holistically looks at the whole business including brewing. From a “Big Picture” perspective, Vicinity Brew and Brew Ninja are both self identified as Brewery Management Software. As you can see in the chart above, there are a some similarities between the two software programs. 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If enabled it is not necessary to use Integral Tiles for avoiding the last column/row to be cropped. Added new advanced option Adjust Tile Size. Added two new patterns: Landscape (7 rows) and Landscape (10 rows). Added Advanced option on OS X to disable native file open dialog. New main option Adapt Size which replaces Integral Tiles and Adjust Tile Size. Tiles can be copied in a subfolder or linked to the original location. New advanced option for Web Page creation. Tile Layers option in Photoshop File Format. Option in TIFF and Photoshop File Format. Updated Librares and Development Environment. Added Turkish translation and minor UI changes.ġ2 January 2018 - New Release 3.37.4 Beta Updated Build System and latest Libraries Added List of Unused Images in the Text Report.Ģ1 February 2019 - New Release 3.38.3 BetaĢ4 January 2019 - New Release 3.38.1 Beta Added Tile# and Image# in the Text Report. Added List of Unused Images in Text Report. Fixed Windows XP compatibility (libcurl.dll). 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For given input data - in our case our Blob Ross paintings - it produces a predicted image - what it thinks Bob Ross would make from that input. Instead of just one neural network, the GAN employs two, working in a kind of competition with each other. While GANs build on the concept of the neural network, they also introduce an extremely interesting innovation. GANs are responsible for some of the most exciting, and the most terrifying recent innovations in computer-generated images, including “deepfake” technologies that can seamlessly paste a new face onto an actor’s (often unclothed) body. The GAN was first proposed only a handful of years ago, in 2014. But the technique we’re going to use in this essay is a genuinely recent invention: the “Generative Adversarial Network” or “GAN”. Many of the other techniques used in modern machine learning are even older. Neural networks, like the one I used to identify medieval pole arms, were (arguably) first described in the 1940’s. Most of the techniques and algorithms used in artificial intelligence are, relatively speaking, quite old. Most likely it would produce a khaki smudge. A traditional algorithm attempting to predict this would try to split the difference - it would try to find the colour and shape exactly in the middle of all Ross’s mountains. While they’re all recognisably in his style, they’re also quite dramatically different - they are different colours, they have different patterns of light and shade, and they’re very different shapes. Here are some mountains from a few Bob Ross paintings. We’ll take all of the elements of a Bob Ross painting - majestic mountains, quiet rivers, cosy cabins, sweeping clouds, and happy little trees - and render each of them as simple blobs of colour in vaguely the right shape. To produce that, we’ll need to go through a painstaking process of reverse engineering - taking completed Bob Ross paintings, and creating a blobby equivalent for each of them. What we need is a set of training data - a set of blobby paintings paired with a real Bob Ross equivalent. We’re getting closer to turning this into a solvable problem. It needs to translate, effectively, between my semi-incompetent input, and a Bob-Ross-alike output. In this case, we want an algorithm that, given one of my blobby creations, can predict (and display) what the painting would look like, had it been painted by Bob Ross himself. Given an input, they predict an output that is most likely to meet some desired criteria, to minimise error. What I want is something that can turn my garish blobs into something resembling a Bob Ross painting, without the bother of having to learn to do it myself.Īrtificial intelligence algorithms work, for the most part, on the principle of prediction. I want to short-circuit the process of practice. Can we structure the problem in such a way as to make it solvable for a computer? What does it mean to teach a computer to paint? What I want to achieve is a system where I can, with minimal input, produce a novel painting with minimal effort. This is a tricky problem for artificial intelligence. But can I get an algorithm to do that practice for me? Can I teach a computer to paint? Can I take a shortcut? Bob Ross says if I’m willing to practice, I can paint just like him. I have a lot of work to do, and a lot of essays to write. And Ross seems so at peace while painting, so lost in the tiny bucolic Alaskan wilderness he’s creating on the canvas. I’m a firm believer in hard work and practice over some nebulous concept of “talent”. It’s a hugely appealing idea, and it’s a sentiment I tend to share. Anything that you’re willing to practice, you can do.” - Bob Ross One of the more charming aspects of Ross’s delivery is his assurance that, given enough practice, anyone could learn to paint. His gentle delivery and effortless manner are a soothing balm in a hectic world. Despite, or perhaps because of this complete lack of ability with a brush, I find celebrity TV painter Bob Ross completely enthralling. But break out the oil paints and it’s all over - the best I can produce is some indecipherable blobs in garish colours. I can make a credible effort with a pen or pencil, provided you’re not after something tricky like human hands or horses. I am not, I will admit, a terribly good artist. The Fleshlight Quickshot Vantage feels good. Our Experience with the Fleshlight Quickshot VantageĪbove: the Fleshlight Quickshot Vantage’s opening. This is a reusable toy and should last a long time with proper care. Once fully dry, place it back in the hard care and screw the ends back on. We found that we could carefully turn the sleeve inside-out so that the inner portion could properly dry in the open air (this step is important because you don’t want mildew). To clean, remove the inner sleeve and rinse it thoroughly with warm water. 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