The latest from the SKYGLOW project captures the Grand Canyon during a full cloud inversion.

Cloud gazing is no longer an activity reserved for the outdoors, thanks to these life-like but surreal indoor clouds created by artist Berndnaut Smilde.

Loud restaurants are a big source of complaints. But what's the source of the problem?

A California restaurant asks families with loud children to leave.

What ever happened to that Internet of Things? We outsourced it.

The male white bellbird attracts a mate by singing louder than a jackhammer.

Aflac’s vice president and corporate secretary makes sure the company goes above and beyond to create and maintain a culture of purpose.

Bacteria can help solar panels convert sunlight to energy, even on overcast days.

The Natural History Museum, London, announced the finalists for its 53rd Wildlife Photographer of the Year contest.

Beautiful phenomenon of noctilucent blue clouds may be growing due to greenhouse gas emissions.

At first glance, you might assume this image is the result of some elaborate Photoshop trick, but trust us, it's 100 percent real!

CDL’s Nigel Phillips considers why early adopters of technology are poised to lead as we learn to cope with social distancing during the Covid-19 pandemic.

Citation Twitter For more about this, go here. Find out more at this site. Keywords: Washington dc server hosting, Cloud solutions, It managed services, Dedicated managed hosting, Boston business phone system, Seattle server hosting. Graphics: Share This Image

The post The Three Most Prevalent Cloud Computing Myths Debunked appeared first on RSS News Feed.

Called the MWE Cloud, the new hosting service - offered by leading healthcare web development company Medical Web Experts - allows for faster development of mobile and web applications and an enhanced level of security.

Ob/Gyns Can Now Use An EHR Specifically Designed With Their Workflows In Mind

IndSoft.net Cloud is committed to supporting such small and medium enterprises during these difficult times has launched Free Cloud Credit Program.

The patented technology for cardiac and fatigue risks monitoring was named the most promising for the insurance sector.

The newest version of QuickBooks 2019 comes loaded with updates tools, features, and functionalities, which have been designed to simplify accounting and bookkeeping complexities.

Isolated Data Tier Service Launches Today with an Exclusive Approach to Storage

Annual listing profiles 10 companies at the forefront of providing cloud communications consulting services and impacting the marketplace

Everyone wants to have more clients. But, when you actually start onboarding more resellers — from all over the world — you start realizing just how hard it is to manage and how much you need an automation solution for your CSP busines!

Cocktail Cloud 4.0 is a digital platform (PaaS) that enables companies to use and implement the cloud-native platform. It was based on the experience of building multi-cloud, artificial intelligence (AI), and smart city platforms.

LiberCloud's content and collaboration learning platform expands to serve corporate training industry in U.S.

Caregivers can now manage video counseling and coaching sessions directly from a patient or member record

For the third year in a row as exhibitors, the interworks.cloud team wants to say a huge thank you to all its prospects and customers for helping make this year the greatest success, so far!

Today, Acquisition International Magazine named Denny Cherry & Associates Consulting [DCAC] the "Best Full-Service Cloud Technology Consulting Company California 2019" at their Global Excellence Awards.

Procuring SeamlessDocs just got even easier

The platform provides end-to-end capabilities and multiple features to enable small and medium size enterprises' easier access to tax credits for hiring eligible employees.

Series To Premier On The All New Reach TV Network Spring 2020.

(Bloomberg) -- Kingsoft Cloud Holdings Ltd. rose 40% in the first major trading debut by a Chinese company since the accounting scandal at Luckin Coffee Inc.The affiliate of Hong Kong-listed Kingsoft Corp. raised $510 million in its initial public offering, pricing its shares at the midpoint of a $16 to $18 targeted range. The shares closed at $23.84 in New York trading Friday, giving the company a market value of $4.77 billion.The Beijing-based cloud computing service company, which had marketed 25 million shares, increased the sale to 30 million American depositary shares.The IPO is the biggest by a Chinese company in the U.S. this year, according to data compiled by Bloomberg. It’s a tricky time for Chinese companies listing in the U.S. after the poster child of Chinese startups, Luckin, was accused of accounting fraud. Luckin’s shares had fallen 74% from its IPO price last year when trading of its stock was suspended in April.Read: Luckin Coffee Scandal Deals Blow to China Inc.’s Reputation“Given the context regarding China ADR, it’s actually good for quality companies,” Henry He, Kingsoft Cloud’s chief financial officer, said in an interview Friday evening in Hong Kong. “The capital has to be deployed and quality long-only investors will pay more attention to quality companies like us.”Tense MomentFinancial performance of Kingsoft Cloud has been consolidated with its Hong Kong-listed parent since its inception and there are publicly available track records for investors to analyze, he added.Its IPO comes at a tense moment for the U.S.-China relationship, after President Donald Trump and Chinese state media have exchanged heated criticisms regarding the origin of coronavirus responsible for the pandemic that has killed more than 269,000 and brought much of the world’s economy to a standstill.China Liberal Education Holdings Ltd., a Beijing-based educational company, fell 18% in its U.S. trading debut Friday after raising $8 million in its IPO. A third company that went public Friday, Ayala Pharmaceuticals Inc., rose 0.2% after its $55 million offering.Kingsoft Cloud is the third-biggest cloud services provider in China by revenue with a market share of 5.4%, according to its filings with the U.S. Securities and Exchange Commission. Last year, it lost $160 million on revenue of $568 million. Its chairman, Lei Jun, was a co-founder of smartphone-maker Xiaomi Corp., which will own about a 14% stake in the company after the offering, according to the filings.The offering was led by JPMorgan Chase & Co., UBS Group AG, Credit Suisse Group AG and China International Capital Corp. The company’s shares are trading on the Nasdaq Global Select market under the symbol KC.(Updates with closing share price in second paragraph)For more articles like this, please visit us at bloomberg.comSubscribe now to stay ahead with the most trusted business news source.©2020 Bloomberg L.P.

Cloud security company Ermetic emerged from stealth mode this week with a platform that automates detection and remediation of identity and access-based risks.

read more

Aaron Levie, cofounder and CEO of Box.

It's important not to immediately dive into using any cloud service without investigating what type of security measures are built into the platform.?

The latest piece rounding up the week's notable writing and videos in games includes pieces on new games from Cloudpunk to Industries Of Titan, plus a bunch of neat historical writing & research. ...

TBWAWorldwide uses content services platform as foundation for "cloud-first" directive

Hospital network moves finance, procurement, human resources, and supply chain applications to the cloud to increase efficiency and improve business insights

National non-profit expedited the launch of an online early childhood development community in wake of COVID-19 pandemic?

Is a Fire Alarm System Too Loud? aconstanza Mon, 05/04/2020 - 12:29

We manufactured a crisis much before the pandemic hit the financial world.

Morning Star Tribune Local Twin Cities (Minneapolis/St. Paul) Weather Video Forecast

Reports suggest that Cheryl is pushing for Girls Aloud to get back together after The Greatest Dancer was axed by the BBC

The price by which RICKI LEE and AARON ISHMAEL's LOUD MEDIA (SARATOGA RADIO LLC) is purchasing AC simulcast WNYV/WHITEHALL, NY and WVNR-A and the construction permit for W242DF/POULTNEY, … more

LEIGHTON BROADCASTING Country KZPK (WILD COUNTRY 99)/ST. CLOUD, MN has launched the “Books with BROOK” YOUTUBE series in conjunction with SCHOLASTIC. MD/afternoon personality … more

There are so many different types of hosting that it can be overwhelming to choose the right one for your WordPress site, but at the same time, it just means there are enough options so you can choose the perfect fit.

In the classic loudness war, music and radio producers have been trying to create their recordings as loud as possible and loudness normalization was introduced to stop that. Now one can see the start of a new loudness target war, where podcasters set their loudness targets higher and higher, mainly triggered by high target recommendations of platforms like Spotify or Amazon Alexa.
In this article, we will show how to resist the loudness target war and still be compliant with major platforms.

Resist the loudness target war! (Photo by Nayani Teixeira)

What's the problem?

“Two or three years ago it seemed that many stations were finally realizing that better radio could improve ratings. And the major myth brought over from AM radio – that a louder signal, regardless of quality, attracts more listeners – appeared to be losing its strength,” writes Robert Orban. The times of excessively compressed audio, putting loudness over sound quality, were coming to an end. We were hoping the same when we wrote about the CALM Act and EBU R128 in 2012. Those measures were meant to make programs sound more evened out and set a standard for a reasonable loudness level.

Except, Orban's article was published in 1979 (PDF, p. 60 ff.), and he concludes: "The loudness war has escalated, and quality is once again being sacrificed." 40 years later, a new loudness target war is emerging. While, yes, radio and TV stations have widely adopted the new standards, prominent competitors in the audio market are pushing for higher loudness targets once again.

Loudness war: the trend of increasing audio levels in recorded music over time. (Screenshot delamar.de)

Why LOUDER is not better

Historically, the loudness war has escalated with the advent of digital technology. Peak level normalization and quasi peak program meters (QPPM) encouraged producers to push audio signals to the limit. Just shy of clipping, signals could now be compressed to the highest possible levels, using multiband compressors and limiters. While this lifted quieter signals up, transforming a waveform into a brick, marketers thought that the louder songs on CDs and almost yelling voices on FM radio would attract listeners. On the other hand, reduced dynamics makes audio less interesting and can lead to listener fatigue, as Rip Rowan pointedly illustrated in his 2002 article "Over the Limit":

WHY IS THE LOUDER IS BETTER APPROACH THE WRONG APPROACH? BECAUSE WHEN ALL OF THE SIGNAL IS AT THE MAXIMUM LEVEL, THEN THERE IS NO WAY FOR THE SIGNAL TO HAVE ANY PUNCH. THE WHOLE THING COMES SCREAMING AT YOU LIKE A MESSAGE IN ALL CAPITAL LETTERS. AS WE ALL KNOW, WHEN YOU TYPE IN ALL CAPITAL LETTERS THERE ARE NO CUES TO HELP THE BRAIN MAKE SENSE OF THE SIGNAL, AND THE MIND TIRES QUICKLY OF TRYING TO PROCESS WHAT IS, BASICALLY, WHITE NOISE. LIKEWISE, A SIGNAL THAT JUST PEGS THE METERS CAUSES THE BRAIN TO REACT AS THOUGH IT IS BEING FED WHITE NOISE. WE SIMPLY FILTER IT OUT AND QUIT TRYING TO PROCESS IT.

Hence, many spoken word producers and broadcasters luckily wisened up and committed to new standards, based on loudness normalization instead of peak normalization. LUFS, Loudness Units relative to Full Scale, is a unit that measures an audio track's average loudness. All segments of a program can then be normalized to a certain LUFS value. As we have discussed before, -23 LUFS is standard now for broadcasters of the EBU, which for example has led to advertising segments no longer being much louder than the rest of any particular program. For a short while, it seemed like a peace agreement, or at least a truce had been achieved in the loudness war.

Human loudness perception is based on average levels instead of peak levels. (Screenshot theproaudiofiles.com)

Loudness Targets and Dynamic Range

However, while LUFS adoption is increasing across the industry, this doesn't mean that people have stopped trying to be louder than everybody else. And indeed -23 LUFS is not the one-size-fits-all value. We have recommended -16 LUFS for podcasts ourselves. The loudness of a production played in a cinema should be different from one made for earphones and noisy listening environments. Some headphones expect a louder signal and don't have enough gain to work with -23 LUFS under all circumstances.

The closer a production gets to 0 LUFS though, the less dynamic range can be reproduced. However, the dynamic range also depends on the dBTP, the maximum True Peak level, which indicates the level of the highest possible peak value. For instance, the aforementioned EBU R128 standard of -23 LUFS also defines a -1 dBTP. The difference between the LUFS and dBTP levels is called Peak to Loudness Range, PLR. For EBU R128 the PLR would be 22 LU (Loudness Units), a podcast with -16 LUFS and -1 dBTP has a PLR of 15 LU. Thus, the PLR is a measure of the maximum possible dynamic range of an audio production.

Platforms: Apple, Google, Amazon, and Spotify

Our already pretty high recommendation of -16 LUFS, -1 dBTP for mobile listening was also adopted by Apple's best practices for podcasts and recommendations for Google Assistant. Some are pushing it too far, though. A daily updated analysis by podnews shows that many podcasts are much louder than -16 LUFS.

Distribution of loudness across a selection of podcasts. (Screenshot podnews.net)

This might in part be due to specs published by other competitors in the audio space:

Amazon, for instance, recommends -14 LUFS at -2 dBTP for Alexa skills, meaning a PLR of only 12 LU. While this might work for Alexa's synthesized voice, which doesn't have much variability, it produces a dynamic range too low for spoken word content.
However, Amazon also says that a skill may be rejected if the program loudness is lower -19 LUFS or higher -9 LUFS, therefore a target of -16 LUFS is perfectly fine, which means that Alexa's robot voice leads by 2 LU compared to the audio content.

Spotify normalizes audio to the equivalent of about -14 LUFS, -1 dbTP, but they still use ReplayGain, which is not exactly the same as LUFS but gives similar results. Spotify mainly decreases the volume of overly loud productions, but can also increase the volume on some playback devices if the audio is much too soft.
For pop music, -14 LUFS is acceptable, but for podcasts or classical music, it is too high. However, (pop) music can always be played a bit louder compared to speech, therefore a loudness target of -16 LUFS for podcasts is fine on Spotify as well.

Make LUFS, not war

If producers just use the highest recommended target and therefore the loudness (target) war goes into another battle, we will hear more compressed, distorted voices once again, lacking emotion and many subtleties that are reflected in the dynamic range of how we speak.

Setting a loudness target higher than -16 LUFS does not improve the listening experience in any way. However, many productions would benefit from sensitively adjusting differences in dynamics throughout the production, lifting up quieter segments, lowering loud segments, and treating speech and music differently. As pointed out in a presentation recently (video, in German), you can do that directly in your DAW or use a leveler to automate dynamics processing.

Instead of just raising the loudness target, adjusting differences in levels can help to make the listening experience much more enjoyable.

Recent album releases suggest that the music industry is still in the middle of the loudness war, often limiting the peak to loudness range to single digit LU values. (By the way, your vinyl-buying friend is right, vinyl records do sound better because they don't work with the highest compression rates.) Hopefully, podcasters, radio producers and other spoken word artists, as well as the platforms that host and publish their productions, can resist the temptation of louder and louder audio.
Make (no more than -16) LUFS, not war!

Conclusion

With some podcasts, smart speakers and streaming platforms trying to be louder than the competition, the listening experience deteriorates. However, podcasts can sound great and loud enough even in noisy environments, when well produced:

• Never set a loudness target higher than -16 LUFS for spoken word audio.
• If your audio is too quiet, try lifting up quieter sections and reducing the volume of louder sections, directly in your DAW or by using a leveler.
• These settings will work fine on all current platforms, including Amazon Alexa and Spotify.

Resist the loudness target war!

When we started Discourse in 2013, our server requirements were high:

• 1GB RAM
• modern, fast dual core CPU
• speedy solid state drive with 20+ GB

I'm not talking about a cheapo shared cpanel server, either, I mean a dedicated virtual private server with those specifications.

We were OK with that,

By Jessica Corbett Common Dreams “We face a stark choice [between] radical, disruptive changes to our physical world or radical, disruptive changes to our political and economic systems to avoid those outcomes.” As people across the globe mobilize to demand … Continue reading →

By Jessica Corbett Common Dreams “We face a stark choice [between] radical, disruptive changes to our physical world or radical, disruptive changes to our political and economic systems to avoid those outcomes.” As people across the globe mobilize to demand … Continue reading →

By Jessica Corbett Common Dreams “We face a stark choice [between] radical, disruptive changes to our physical world or radical, disruptive changes to our political and economic systems to avoid those outcomes.” As people across the globe mobilize to demand … Continue reading →

Data analytics in the cloud has become an integral part of enterprise businesses. Big data analytics systems, however, still lack the ability to take user performance goals and budgetary constraints for a task, collectively referred to as task objectives, and automatically configure an analytic job to achieve these objectives. This paper presents a data analytics optimizer that can automatically determine a cluster configuration with a suitable number of cores as well as other system parameters that best meet the task objectives. At a core of our work is a principled multi-objective optimization (MOO) approach that computes a Pareto optimal set of job configurations to reveal tradeoffs between different user objectives, recommends a new job configuration that best explores such tradeoffs, and employs novel optimizations to enable such recommendations within a few seconds. We present efficient incremental algorithms based on the notion of a Progressive Frontier for realizing our MOO approach and implement them into a Spark-based prototype. Detailed experiments using benchmark workloads show that our MOO techniques provide a 2-50x speedup over existing MOO methods, while offering good coverage of the Pareto frontier. When compared to Ottertune, a state-of-the-art performance tuning system, our approach recommends configurations that yield 26\%-49\% reduction of running time of the TPCx-BB benchmark while adapting to different application preferences on multiple objectives.