Learn how to sell strategy... Jacob Cass & Matt Davies give different perspectives on how to approach sales & the brand building process. Tune in to episode 4!

We kick things off with Rob talking about his favorite albums of the year. We then discuss the shocking news...

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We kick things off talking about the Jewish holiday of Yom Kippur. We then discuss David D Rainman's recent request...

The post METAL INJECTION LIVECAST #536 - Sinema with Chase from GATECREEPER appeared first on Metal Injection.

We have a very special guest, Jinjer vocalist Tatiana Shmayluk called into the show. She talked about the band's upcoming...

The post METAL INJECTION LIVECAST #537 - Hootie and the No Fish with JINJER's Tatiana Shmayluk appeared first on Metal Injection.

Former host of MTV Headbangers Ball, Riki Rachtman, called into the show to share memories of Headbangers Ball, working at...

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We're excited to welcome back Busted Open radio producer Alex Metz to the show, to talk about all things pro...

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We kicked things off with an update on Rob's marijuana abstaining, or lack thereof. We then spend a good amount...

The post METAL INJECTION LIVECAST #540 - Eight Iota Ripper with Kenny Hickey of SILVERTOMB / TYPE O NEGATIVE appeared first on Metal Injection.

On this week's episode, we were joined by Stray From the Path guitarist Tom Williams. We talk about band's recently...

The post METAL INJECTION LIVECAST #541 - Thank You For Your Cervix with STRAY FROM THE PATH's Tom Williams appeared first on Metal Injection.

A special treat for Livecast fans, we are giving you a preview of the type of content you can expect...

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We kick things off talking about the Motley Crue reunion. Darren shares a story from work. Rob talks about going...

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We kicked things off with Rob recapping his experience at the Tool concert. We then discussed Dave Mustaine's recent interview...

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This week, we had a very special guest, our Livecastard of the Month, Eric, who actually signed up for our...

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MetalSucks' Axl Rosenberg was back to sit in on the show. We kick things off talking about Chanukah and our...

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We kick things off talking about annoying holiday commercials. We discuss Christmas music this episode, and why Hanukkah lands on...

The post METAL INJECTION LIVECAST #546 - Grandma Smoothie appeared first on Metal Injection.

We kick things off talking about how we spent the holiday break and previewing the bonus Patreon episode coming next...

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It's the first show of the new year and the new decade. We kick things off with a little math...

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We kick things off with our New Year's resolutions. Noa explains her future vision board. We discuss climate change and...

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We kick things off discussing our Tad's Patreon episode, and our fast food preferences. We then discuss the sad status...

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We're so excited to have a huge guest on the show – big time comedian and noted metalhead, Brian Posehn,...

The post METAL INJECTION LIVECAST #551 - Where Nickelback Shines with special guest Comedian Brian Posehn appeared first on Metal Injection.

What's with all the good drummers dying? We kick things off discussing the sad news. Noa discussed locking herself out...

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What an eventful edition of the Metal Injection Livecast! We kick things off talking about the new Dave Mustaine memoir...

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We kick things off talking about the Rage Against the Machine reunion. We then discuss the summer touring season and...

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By Jessica Corbett Common Dreams “This is a wake-up call,” says one Australian marine biologist. “Given sea temperatures usually increase as we get towards March, this is probably conservative.” Delivering yet another “wake-up call” after recent studies have shown that … Continue reading →

By Jessica Corbett Common Dreams “This is a wake-up call,” says one Australian marine biologist. “Given sea temperatures usually increase as we get towards March, this is probably conservative.” Delivering yet another “wake-up call” after recent studies have shown that … Continue reading →

According to the DHS document, along with the 11 active cases there are 23 members of the Secret Service who have recovered from COVID-19 and an additional 60 employees who are self-quarantining. No details have been provided about which members of the Secret Service are infected or if any have recently been on detail with the president or vice president.

In this episode of the Smashing Podcast, we’re talking about building apps on a tight timeline. How can you quickly turn around a project to respond to an emerging situation like COVID-19? Drew McLellan talks to Phil Smith to find out. Show Notes CardMedic React Native React Native for Web Expo Apiary Phil’s company amillionmonkeys Phil’s personal blog and Twitter Weekly Update Getting Started With Nuxt Implementing Dark Mode In React Apps Using styled-components How To Succeed In Wireframe Design Mirage JS Deep Dive: Understanding Mirage JS Models And Associations (Part 1) Readability Algorithms Should Be Tools, Not Targets Transcript Drew McLellan: He is director of the full-stack web development studio amillionmonkeys, where he partners with business owners and creative agencies to build digital products that make an impact.

Let $1 le r < n$ be integers. We give a proof that the group $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$ of automorphisms of the one-sided shift on $n$ letters embeds naturally as a subgroup $mathcal{h}_{n}$ of the outer automorphism group $mathop{mathrm{Out}}(G_{n,r})$ of the Higman-Thompson group $G_{n,r}$. From this, we can represent the elements of $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$ by finite state non-initial transducers admitting a very strong synchronizing condition.

Let $H in mathcal{H}_{n}$ and write $|H|$ for the number of states of the minimal transducer representing $H$. We show that $H$ can be written as a product of at most $|H|$ torsion elements. This result strengthens a similar result of Boyle, Franks and Kitchens, where the decomposition involves more complex torsion elements and also does not support practical extit{a priori} estimates of the length of the resulting product.

We also give new proofs of some known results about $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$.

We study a problem concerning parabolic induction in certain p-adic unitary groups. More precisely, for $E/F$ a quadratic extension of p-adic fields the associated unitary group $G=mathrm{U}(n,n)$ contains a parabolic subgroup $P$ with Levi component $L$ isomorphic to $mathrm{GL}_n(E)$. Let $pi$ be an irreducible supercuspidal representation of $L$ of depth zero. We use Hecke algebra methods to determine when the parabolically induced representation $iota_P^G pi$ is reducible.

Large transformer-based language models have been shown to be very effective in many classification tasks. However, their computational complexity prevents their use in applications requiring the classification of a large set of candidates. While previous works have investigated approaches to reduce model size, relatively little attention has been paid to techniques to improve batch throughput during inference. In this paper, we introduce the Cascade Transformer, a simple yet effective technique to adapt transformer-based models into a cascade of rankers. Each ranker is used to prune a subset of candidates in a batch, thus dramatically increasing throughput at inference time. Partial encodings from the transformer model are shared among rerankers, providing further speed-up. When compared to a state-of-the-art transformer model, our approach reduces computation by 37% with almost no impact on accuracy, as measured on two English Question Answering datasets.

This paper considers the multi-group multicast beamforming optimization problem, for which the optimal solution has been unknown due to the non-convex and NP-hard nature of the problem. By utilizing the successive convex approximation numerical method and Lagrangian duality, we obtain the optimal multicast beamforming solution structure for both the quality-of-service (QoS) problem and the max-min fair (MMF) problem. The optimal structure brings valuable insights into multicast beamforming: We show that the notion of uplink-downlink duality can be generalized to the multicast beamforming problem. The optimal multicast beamformer is a weighted MMSE filter based on a group-channel direction: a generalized version of the optimal downlink multi-user unicast beamformer. We also show that there is an inherent low-dimensional structure in the optimal multicast beamforming solution independent of the number of transmit antennas, leading to efficient numerical algorithm design, especially for systems with large antenna arrays. We propose efficient algorithms to compute the multicast beamformer based on the optimal beamforming structure. Through asymptotic analysis, we characterize the asymptotic behavior of the multicast beamformers as the number of antennas grows, and in turn, provide simple closed-form approximate multicast beamformers for both the QoS and MMF problems. This approximation offers practical multicast beamforming solutions with a near-optimal performance at very low computational complexity for large-scale antenna systems.

Recent beyond worst-case optimal join algorithms Minesweeper and its generalization Tetris have brought the theory of indexing and join processing together by developing a geometric framework for joins. These algorithms take as input an index $mathcal{B}$, referred to as a box cover, that stores output gaps that can be inferred from traditional indexes, such as B+ trees or tries, on the input relations. The performances of these algorithms highly depend on the certificate of $mathcal{B}$, which is the smallest subset of gaps in $mathcal{B}$ whose union covers all of the gaps in the output space of a query $Q$. We study how to generate box covers that contain small size certificates to guarantee efficient runtimes for these algorithms. First, given a query $Q$ over a set of relations of size $N$ and a fixed set of domain orderings for the attributes, we give a $ ilde{O}(N)$-time algorithm called GAMB which generates a box cover for $Q$ that is guaranteed to contain the smallest size certificate across any box cover for $Q$. Second, we show that finding a domain ordering to minimize the box cover size and certificate is NP-hard through a reduction from the 2 consecutive block minimization problem on boolean matrices. Our third contribution is a $ ilde{O}(N)$-time approximation algorithm called ADORA to compute domain orderings, under which one can compute a box cover of size $ ilde{O}(K^r)$, where $K$ is the minimum box cover for $Q$ under any domain ordering and $r$ is the maximum arity of any relation. This guarantees certificates of size $ ilde{O}(K^r)$. We combine ADORA and GAMB with Tetris to form a new algorithm we call TetrisReordered, which provides several new beyond worst-case bounds. On infinite families of queries, TetrisReordered's runtimes are unboundedly better than the bounds stated in prior work.

Recent studies have confirmed a growing trend, especially among youngsters, of using Online Social Media as favourite information platform at the expense of traditional mass media. Indeed, they can easily reach a wide audience at a high speed; but exactly because of this they are the preferred medium for influencing public opinion via so-called fake news. Moreover, there is a general agreement that the main vehicle of fakes news are malicious software robots (bots) that automatically interact with human users. In previous work we have considered the problem of tagging human users in Online Social Networks as credulous users. Specifically, we have considered credulous those users with relatively high number of bot friends when compared to total number of their social friends. We consider this group of users worth of attention because they might have a higher exposure to malicious activities and they may contribute to the spreading of fake information by sharing dubious content. In this work, starting from a dataset of fake news, we investigate the behaviour and the degree of involvement of credulous users in fake news diffusion. The study aims to: (i) fight fake news by considering the content diffused by credulous users; (ii) highlight the relationship between credulous users and fake news spreading; (iii) target fake news detection by focusing on the analysis of specific accounts more exposed to malicious activities of bots. Our first results demonstrate a strong involvement of credulous users in fake news diffusion. This findings are calling for tools that, by performing data streaming on credulous' users actions, enables us to perform targeted fact-checking.

In encoder-decoder neural models, multiple encoders are in general used to represent the contextual information in addition to the individual sentence. In this paper, we investigate multi-encoder approaches in documentlevel neural machine translation (NMT). Surprisingly, we find that the context encoder does not only encode the surrounding sentences but also behaves as a noise generator. This makes us rethink the real benefits of multi-encoder in context-aware translation - some of the improvements come from robust training. We compare several methods that introduce noise and/or well-tuned dropout setup into the training of these encoders. Experimental results show that noisy training plays an important role in multi-encoder-based NMT, especially when the training data is small. Also, we establish a new state-of-the-art on IWSLT Fr-En task by careful use of noise generation and dropout methods.

Cassava a major food crop in many parts of Africa, has majorly been affected by Cassava Brown Streak Disease (CBSD). The disease affects tuberous roots and presents symptoms that include a yellow/brown, dry, corky necrosis within the starch-bearing tissues. Cassava breeders currently depend on visual inspection to score necrosis in roots based on a qualitative score which is quite subjective. In this paper we present an approach to automate root necrosis scoring using deep convolutional neural networks with semantic segmentation. Our experiments show that the UNet model performs this task with high accuracy achieving a mean Intersection over Union (IoU) of 0.90 on the test set. This method provides a means to use a quantitative measure for necrosis scoring on root cross-sections. This is done by segmentation and classifying the necrotized and non-necrotized pixels of cassava root cross-sections without any additional feature engineering.

Fashion trend forecasting is a crucial task for both academia and industry. Although some efforts have been devoted to tackling this challenging task, they only studied limited fashion elements with highly seasonal or simple patterns, which could hardly reveal the real fashion trends. Towards insightful fashion trend forecasting, this work focuses on investigating fine-grained fashion element trends for specific user groups. We first contribute a large-scale fashion trend dataset (FIT) collected from Instagram with extracted time series fashion element records and user information. Further-more, to effectively model the time series data of fashion elements with rather complex patterns, we propose a Knowledge EnhancedRecurrent Network model (KERN) which takes advantage of the capability of deep recurrent neural networks in modeling time-series data. Moreover, it leverages internal and external knowledge in fashion domain that affects the time-series patterns of fashion element trends. Such incorporation of domain knowledge further enhances the deep learning model in capturing the patterns of specific fashion elements and predicting the future trends. Extensive experiments demonstrate that the proposed KERN model can effectively capture the complicated patterns of objective fashion elements, therefore making preferable fashion trend forecast.

Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users' demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model comparison and selection with different levels of details. Besides, it shows the difference in model performance on similar products to reveal the risk of model selection and increase users' confidence in choosing a forecasting model. Two case studies and interviews with domain experts demonstrate the effectiveness and usability of DFSeer.

ON INLANDER.COM WORLD: Roughly two weeks after Canada's deadliest mass shooting, Prime Minister Justin Trudeau introduced an immediate ban on what he called “military-style assault weapons.”…

Northern Quest Resort & Casino is set to reopen Tuesday, albeit with strict social-distancing and other safety protocols in place, becoming the second regional casino to reopen after closures caused by the coronavirus. Resort officials expect a crowd due to pent-up interest in the community for getting out of the house (not to mention Cinco de Mayo).…

The Showcase celebrity golf tournament attracts big-time athletes and pop stars each year.…

You could say that SpoKast winning Best Podcast was about quality, about personality and charisma, about the chemistry the three hosts have, about the way they capture what's so great about Spokane.…

Novel compounds of formula (1) wherein: A is especially a linear or branched divalent alkylene radical having between 1 and 10 carbon atoms, and Y is especially a hydrogen atom.

A firmware update method and apparatus of a set-top box for a digital broadcast system is provided. A firmware update method of a set-top box for a digital broadcast system includes determining whether a newly received Code Version Table (CVT) following a public CVT which has been previously received and stored is the public CVT or a filtering CVT; and updating, when the newly received CVG is the filtering CVT, the firmware of the set-top box with a filtering firmware indicated by the filtering CVT.

The watch case of this invention includes a caseband (2) made from sintered material and a back cover (10) secured to the caseband by means of at least two pins (12). Each pin passes through a first hole (14) provided in a first projection (16) formed in the caseband and two second holes (13, 15) provided respectively in two second projections (17, 18) formed in the back cover, said second projections being arranged respectively on either side of said first projection. Each pin being axially retained in its holes by the elastic effect provided by the seal when the caseband lies on the back cover.

A cap (2) is made of sintered hard metal and has on the inside a cylindrical surface (20) and a frusto-conical surface (21) that are true ground. The cap's cylindrical surface (20) is fitted with radial play around an outer cylindrical surface (9) of an underlying middle (1) and the cap's frusto-conical surface (21) has the same inclination as a subjacent frusto-conical surface (14) on the outside of the middle. The cap (2) and the middle (1) are secured to one another by a ring of deformable material sandwiched between their cylindrical surfaces (9, 20). On the outside the cap (2) is formed over its thicker main portion (18) with a trued and polished surface (22) having the same inclination as its inside frusto-conical surface (21) such as to provide the thicker portion (18) with a parallelogrammatic cross-section.

A watch case back opener is provided having a base. A vise is rotatably mounted on the base for securing a watch case to the base. The vise includes a first jaw and a second jaw movable between an open and closed position. Holes are formed in the jaw. They are adapted to receive a plurality of posts to secure a plurality of different sized and shaped watch cases to the vise. An opener unit including an opening blade is mounted on the base for separating a watch case back from the watch case by twisting the lever relative to the base and then lifting the blade relative to the base.

A time-locked cigarette case has time-controlled locking mechanism which is manually adjustable by the user and also has a first latch rod which normally retains the case in a closed condition and a second latch rod which moves to retain the case in a closed condition if the first latch rod is jolted to an open position so as to prevent the case from being opened by jolting before the manually set time delay has expired.

A fluid flow is simulated by causing a computer to perform operations on data stored in the memory to compute at least one eddy of a fluid flow at a first scale and perform operations to compute at least one eddy of the fluid flow at both the first scale and a second scale. The second scale is a finer scale than the first scale, and the computation of the at least one eddy of the fluid flow at the second scale is constrained by results of the computation of the at least one eddy of the fluid flow at the first scale.

A system and method is taught to substantially automate forecasting for a hydrocarbon producing reservoir through integration of modeling module workflows. A control management module automatically generates static and dynamic offspring models, with static and dynamic modeling software, until a performance objective associated with the forecasting of the reservoir is satisfied. The performance objective can include an experimental design table to determine a sensitivity of a particular parameter or can be directed towards reservoir optimization, i.e., ultimate hydrocarbon recovery, net present value, reservoir percentage yield, reservoir fluid flow rate, or history matching error.

Systems and methods are provided for evaluating performance of forecasting models. A plurality of forecasting models may be generated using a set of in-sample data. Two or more forecasting models from the plurality of forecasting models may be selected for use in generating a combined forecast. An ex-ante combined forecast may be generated for an out-of-sample period using the selected two or more forecasting models. The ex-ante combined forecast may then be compared with a set of actual out-of-sample data to evaluate performance of the combined forecast.

In a gas turbine engine that includes a compressor and a combustor, wherein the combustor includes a primary fuel injector within a fuel nozzle and a secondary fuel injector that is upstream of the fuel nozzle and configured to inject fuel into a flow annulus of the combustor, a method for detecting a flame holding condition about a fuel injector. The method may include the steps of: detecting an upstream pressure upstream of the secondary fuel injector; detecting a downstream pressure downstream of the secondary fuel injector; determining a measured pressure difference between the upstream pressure and the downstream pressure; and comparing the measured pressure difference to an expected pressure difference.