Wheelabrator Technologies Inc. and DB Riley, Inc. | Date: 2011-08-08
A steam generator includes a furnace configured and adapted to generate a stream of furnace exit gases from the combustion of municipal solid waste fuel. At least one superheater is disposed within an upper portion of the furnace or backpass. The superheater is configured and adapted to superheat fluids within the superheater by facilitating heat transfer between fluids within the superheater and furnace exit gases outside the superheater. At least one waterwall furnace platen is disposed within the furnace upstream from the superheater, the waterwall furnace platen is configured and adapted to lower furnace exit gas temperature at the superheater by facilitating heat transfer between fluids within the waterwall furnace platen and furnace exit gases outside the waterwall furnace platen.
Sellahennedige K.,DB Riley, Inc. |
Lee J.,DB Riley, Inc.
American Society of Mechanical Engineers, Power Division (Publication) POWER | Year: 2015
In order to understand how a boiler is performing/ operating, it is critical to obtain data throughout its operation. Data collection and storage methods have evolved through the years improving the quality and quantity of the data. Data is valuable for tracking current unit performance, troubleshooting and helping to narrow down any potential issues/ concerns with performance. Proper use of data collection and analysis may minimize the need for scheduled performance testing except when specific data points are required. This paper will discuss how sensitivity analysis can be utilized to determine the effect lack of/poor quality data has on the desired analysis. It discusses data collection and evaluation for various cases and the relevant ASME codes. Other key features of the paper are the various methods available for data representation, allowing the engineer to easily track key operating parameters. © 2015 by ASME.
DB Riley, Inc. | Date: 2013-05-02
A trunnion seal assembly for joining a stationary inlet/outlet box of a ball tube mill to a rotational interior of the ball tube mill includes an outer ring component configured to be mounted to an outer wall of the stationary inlet/outlet box. An inner ring component is joined to the outer ring component substantially concentrically with the outer ring component. A flexible pad seal is configured to be joined to the outer wall of the stationary inlet/outlet box proximate outer ring component. The pad seal includes a first annular sealing surface. A mill head extension ring configured to be joined to a rotational mill head is located proximate to and substantially concentric with the inner ring component. The mill head extension includes a second annular sealing surface sealingly engaged with the first annular sealing surface of the flexible pad seal.
DB Riley, Inc. | Date: 2013-02-14
DB Riley, Inc. | Date: 2012-01-11
Devices and systems for transporting a material suspended in a fluid, e.g., pulverized coal, that can be assembled about a rotary element are disclosed. The devices and systems comprise a first portion or half of a fan wheel assembly, a second portion or half of a fan wheel assembly, and a plurality of splice plates for connecting the first portion of the fan wheel assembly to the second portion of the fan wheel assembly about the rotary element. Methods of manufacturing and assembling the sectionalized devices and systems are also provided.
DB Riley, Inc. | Date: 2012-05-08
DB Riley, Inc. | Date: 2012-02-13
News Article | June 29, 2015
The more connected we are, the more we are all just pixels on a screen. And we crave more pixels, pixels talking to us, responding to us, acknowledging us—as often as possible. “It’s just a reality that social life is moving through screens,” says Eric Klinenberg, director of the Institute for Public Knowledge at NYU and the author of Going Solo: The Extraordinary Rise and Surprising Appeal of Living Alone. “There’s research showing that people who stay off of social media are more prone to isolation because they’re missing out on the place where the action is.” At any moment in time, that action could stall out. Your friends might all be busy, unable to provide that quick rush of dopamine you get from a Like, a fav, or comment. But you don’t need them—you can outsource communication to an automated archetype that approximates their role in your social sphere. Say for instance, if you’re doing a little late-night booze-fueled shopping. Drunk Shopping is not a person, it’s just a phone number—but it’s your best, tipsy friend when you want some companionship during your online shopping sessions. You simply send a text to a phone number, initiating the conversation with “heyyyyyy,” and it replies with a ridiculous message and a link to a weird item on Amazon. From there, you’re free to continue to chat. It’s a bot, but it doesn’t feel like one. It was created by the three-person team of Chris Baker, Mike Lacher, and Tiger Wang, and it makes them absolutely no money. Baker wrote the copy, Lacher programmed the service, and Wang handled the design. Using the API from a service called Twilio, the team programmed a script that serves up one of about 400 responses from their database, many of which are driven by keywords within the sender’s SMS message. “We have no grand plans for this thing,” Baker says. “We launched it about a month ago, and it was an idea that was tossed around for the longest time. We didn’t know the proper form to give it. We started with, well, what’s the Web experience? And we had a bunch of funny ideas like would you have to slur to get in. At one point, we had built a Captcha that you had to get wrong in order to get in. But doing it through a website never really felt right.” Once SMS and app-based shopping services such as Magic and Alfred became trendy, the team decided a text-message chat bot was the way to go. The big difference, Baker explains, is that it’s “like you’re talking to some insane guy.” “We’ve got more than 10,000 people who have used [Drunk Shopping], and we honestly had to shut down new signups after the first week. Too many people were flocking to it and our bill was starting to skyrocket,” says Baker. “…We’ve had a great deal of people using it, but I haven’t looked at the analytics of how many people have texted in various responses—like how many people are engaged in the rabbit hole of talking to this bot. It’s probably a fair amount.” So why, in a Web full of ways to connect with real people, do we love the bot (even one that sounds like an insane guy)? And of all the ways we could interact with them, why is a plain old texting screen so entertaining? The business of helping developers develop these apps is a thing now. Chatbots are not new; they’re almost as old as the Internet itself. But suddenly, amidst an infinite amount of flashy, niche social apps, the humble bot-texting-app has become trendy. Every morning Product Hunt is littered with them: There’s Text Riley for finding a new apartment, Happy Now for home assistance, Text Miley for job hunting. Texting with these services definitely has an A.I. air to it, but the comfort of those green and blue bubbles does something to offset the absurdity of it. What likely helped pave the road for this sudden slew of digital SMS friends were Twitter bots. The often strange, but ultimately beloved automated accounts have long been one of the best parts of the platform. While your conversations with them might be inane, something sends you back. For whatever reason, tweeting with @tofu_product feels strangely familiar. It’s almost like it took the words right out of your mouth, because that’s essentially what it does. Launched in 2013, @tofu_product scans your recent tweets, then responds to you with a mish-mash of your own words a few seconds after you send it a message. The account’s creator, 32-year-old Joe Toscano, describes the bot’s output as “linguistic salad creation.” Toscano has tweaked tofu’s algorithm over time. He says the original formula was written in Objective-C against the Apple Core Data framework, but there were scaling issues with that codebase once @tofu_product became so popular. He rewrote the code about a year ago, and now it’s based on Go with a Redis database backend. “When someone talks directly to him, a choice is made,” Toscano explains. “If tofu doesn’t know the person, he reads a little bit of their tweet backlog in order to get some material to work with. If he already knows the person, he jumps right into the generation function. After the generation function runs its course, the result is run through a sanity check of a kind and then posted to Twitter as a reply.” Basically, the results are as if your own tweets have been chopped up into poetry magnets and then reassembled by Crispin Glover. And the responses are fast—sometimes too fast for Twitter’s rate limits. When that happens, @tofu_product gets temporarily banned from posting tweets, also known as “getting thrown in Twitter jail.” (He’s a little quieter now, so he managers to stay out of “jail.”) Toscano says he’s been approached by companies to develop @tofu_product into an algorithm that analyzes the sentiments in peoples’ Twitter feeds, but he’d rather it remain just a fun side project. He says he may eventually open-source the reply-generation algorithm, but that may have its drawbacks. “Only having one tofu around makes him kind of a novelty, which is fun,” says Toscano. “People tend to talk to tofu for about five to 10 messages, and then they leave him be… There have been people who have talked to him at great lengths, though, sometimes for hours and hours, spanning hundreds of tweets. Those events are pretty rare, though, and frankly they make me worry about the general mental condition of the human participant.” So what about the condition of the users who are besotted by Invisible Girlfriend and Invisible Boyfriend? The concept is simple: You pay to bae. The apps are run by Matt Homann and Kyle Tabor, who cooked up the idea during a hackathon in 2013. The service began as a chatbot simulation wherein you would text a “boyfriend” or “girlfriend,” but now, actual human beings are doing the talking. Tabor says more than 70,000 fake girlfriends and fake boyfriends have been created since the service launched in January, proving there is an economy of loneliness. The basics to the service (picking a name, a photo, an age, etc) are free. If you want to take things any further, it’ll cost you. For $25 per month, you get 100 text messages, 10 voicemails, and a handwritten note from your fake boo. $15 per month gets you texts only. “My co-founder Matt, he was recently divorced and his parents were bugging him,” Tabor says. “At Thanksgiving, his parents were asking him if they should set another place at the table, awkwardly suggesting things like ‘you need to date again.’ He has these ideas, buys domains, and eventually does nothing with them. It wasn’t until we went to a hackathon where we met, he pitched the idea. We ended up building a very simple chatbot over the weekend.” Ultimately, that chatbot wasn’t very convincing, and they decided the service would have to depend on real people to communicate with subscribers. According to Tabor, there are now roughly 600 people writing for the company through Crowdsource. “They do the hiring, the quality control, they train, they do all of that,” Tabor says. “We just pay a fee for each task. They have many different clients, and we’re probably the smallest client they’ve ever had. They usually work with Fortune 500 companies. They thought it would be very entertaining for some of their workers to break up the monotony of just doing random tasks—checking some spelling of this or just checking if something is adult content, something like that. This is a much more engaging task for them.” According to Tabor, no real relationships have grown out of the service since it launched in January, as none of the writers get to see any of the users’ information other than how they “configured” their invisible other. All the incoming messages are filtered so that they can block out any adult content, as well. “This is a completely asexual relationship, because we don’t allow sexting on the service,” Tabor says. “We flag any adult content and we don’t allow it to go through… We thought of this of a way to live your life confidently without people trying to set you up on dates or coworkers hitting on you. A conversation can be friendship or companionship, and we’re trying to make it less reactive and more proactive, just like a friend would be or a companion.” According to Tabor, there are possibilities for expanding the role of Invisible Boyfriend and Invisible Girlfriend in the future. Because it’s basically a digital pen-pal service, he says they’ve thought about creating an Invisible Life Coach or Invisible Therapist service as a spin-off. But the more interesting idea is playing matchmaker based on subscribers’ preferences and messages. While the invisible significant other scheme hired some humans and found a payday, not every text-bot app has such ambitions. The Drunk Shopping team at one point planned to make money off the service, but things didn’t really pan out: The creators realized that people aren’t using Drunk Shopping to actually shop while drunk. Instead, they just want to talk. “We applied for the Amazon affiliate program, but they rejected us,” says Baker, laughing. 1 “I’m not too sure about how many people are just signing up because they’re bored or lonely. Looking at how people are talking about it, at the end of the day you’re not really looking to buy anything. You’re looking for a funny picture, some funny copy, and it’s just fun knowing that that interaction is always in your back pocket.” 1UPDATE 12:00 PM ET 7/13/15: Drunk Shopping’s Chris Baker was referred to as Chris Davis in the last paragraph of this story. That paragraph has been updated to correct his name.
News Article | August 2, 2015
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