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    Jolie sélection multiple
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    14 novembre 2010, par

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  • Data Privacy in Business : A Risk Leading to Major Opportunities

    9 août 2022, par Erin — Privacy

    Data privacy in business is a contentious issue. 

    Claims that “big data is the new oil of the digital economy” and strong links between “data-driven personalisation and customer experience” encourage leaders to set up massive data collection programmes.

    However, many of these conversations downplay the magnitude of security, compliance and ethical risks companies face when betting too much on customer data collection. 

    In this post, we discuss the double-edged nature of privacy issues in business — the risk-ridden and the opportunity-driven. ​​

    3 Major Risks of Ignoring Data Privacy in Business

    As the old adage goes : Just because everyone else is doing it doesn’t make it right.

    Easy data accessibility and ubiquity of analytics tools make data consumer collection and processing sound like a “given”. But the decision to do so opens your business to a spectrum of risks. 

    1. Compliance and Legal Risks 

    Data collection and customer privacy are protected by a host of international laws including GDPR, CCPA, and regional regulations. Only 15% of countries (mostly developing ones) don’t have dedicated laws for protecting consumer privacy. 

    State of global data protection legislature via The UN

    Global legislature includes provisions on : 

    • Collectible data types
    • Allowed uses of obtained data 
    • Consent to data collection and online tracking 
    • Rights to request data removal 

    Personally identifiable information (PII) processing is prohibited or strictly regulated in most jurisdictions. Yet businesses repeatedly circumnavigate existing rules and break them on occasion.

    In Australia, for example, only 2% of brands use logos, icons or messages to transparently call out online tracking, data sharing or other specific uses of data at the sign-up stage. In Europe, around half of small businesses are still not fully GDPR-compliant — and Big Tech companies like Google, Amazon and Facebook can’t get a grip on their data collection practices even when pressed with horrendous fines. 

    Although the media mostly reports on compliance fines for “big names”, smaller businesses are increasingly receiving more scrutiny. 

    As Max Schrems, an Austrian privacy activist and founder of noyb NGO, explained in a Matomo webinar :

    “In Austria, my home country, there are a lot of €5,000 fines going out there as well [to smaller businesses]. Most of the time, they are just not reported. They just happen below the surface. [GDPR fines] are already a reality.”​

    In April 2022, the EU Court of Justice ruled that consumer groups can autonomously sue businesses for breaches of data protection — and nonprofit organisations like noyb enable more people to do so. 

    Finally, new data privacy legislation is underway across the globe. In the US, Colorado, Connecticut, Virginia and Utah have data protection acts at different stages of approval. South African authorities are working on the Protection of Personal Information Act (POPI) act and Brazil is working on a local General Data Protection Law (LGPD).

    Re-thinking your stance on user privacy and data protection now can significantly reduce the compliance burden in the future. 

    2. Security Risks 

    Data collection also mandates data protection for businesses. Yet, many organisations focus on the former and forget about the latter. 

    Lenient attitudes to consumer data protection resulted in a major spike in data breaches.

    Check Point research found that cyberattacks increased 50% year-over-year, with each organisation facing 925 cyberattacks per week globally.

    Many of these attacks end up being successful due to poor data security in place. As a result, billions of stolen consumer records become publicly available or get sold on dark web marketplaces.

    What’s even more troublesome is that stolen consumer records are often purchased by marketing firms or companies, specialising in spam campaigns. Buyers can also use stolen emails to distribute malware, stage phishing and other social engineering attacks – and harvest even more data for sale. 

    One business’s negligence creates a snowball effect of negative changes down the line with customers carrying the brunt of it all. 

    In 2020, hackers successfully targeted a Finnish psychotherapy practice. They managed to steal hundreds of patient records — and then demanded a ransom both from the firm and its patients for not exposing information about their mental health issues. Many patients refused to pay hackers and some 300 records ended up being posted online as Associated Press reported.

    Not only did the practice have to deal with the cyber-breach aftermath, but it also faced vocal regulatory and patient criticisms for failing to properly protect such sensitive information.

    Security negligence can carry both direct (heavy data breach fines) and indirect losses in the form of reputational damages. An overwhelming 90% of consumers say they wouldn’t buy from a business if it doesn’t adequately protect their data. This brings us to the last point. 

    3. Reputational Risks 

    Trust is the new currency. Data negligence and consumer privacy violations are the two fastest ways to lose it. 

    Globally, consumers are concerned about how businesses collect, use, and protect their data. 

    Consumer data sharing attitudes
    • According to Forrester, 47% of UK adults actively limit the amount of data they share with websites and apps. 49% of Italians express willingness to ask companies to delete their personal data. 36% of Germans use privacy and security tools to minimise online tracking of their activities. 
    • A GDMA survey also notes that globally, 82% of consumers want more control over their personal information, shared with companies. 77% also expect brands to be transparent about how their data is collected and used. 

    When businesses fail to hold their end of the bargain — collect just the right amount of data and use it with integrity — consumers are fast to cut ties. 

    Once the information about privacy violations becomes public, companies lose : 

    • Brand equity 
    • Market share 
    • Competitive positioning 

    An AON report estimates that post-data breach companies can lose as much as 25% of their initial value. In some cases, the losses can be even higher. 

    In 2015, British telecom TalkTalk suffered from a major data breach. Over 150,000 customer records were stolen by hackers. To contain the issue, TalkTalk had to throw between $60-$70 million into containment efforts. Still, they lost over 100,000 customers in a matter of months and one-third of their company value, equivalent to $1.4 billion, by the end of the year. 

    Fresher data from Infosys gives the following maximum cost estimates of brand damage, companies could experience after a data breach (accidental or malicious).

    Estimated cost of brand damage due to a data breach

    3 Major Advantages of Privacy in Business 

    Despite all the industry mishaps, a reassuring 77% of CEOs now recognise that their companies must fundamentally change their approaches to customer engagement, in particular when it comes to ensuring data privacy. 

    Many organisations take proactive steps to cultivate a privacy-centred culture and implement transparent data collection policies. 

    Here’s why gaining the “privacy advantage” pays off.

    1. Market Competitiveness 

    There’s a reason why privacy-focused companies are booming. 

    Consumers’ mounting concerns and frustrations over the lack of online privacy, prompt many to look for alternative privacy-centred products and services

    The following B2C and B2B products are moving from the industry margins to the mainstream : 

    Across the board, consumers express greater trust towards companies, protective of their privacy : 

    And as we well know : trust translates to higher engagement, loyalty, and – ultimately revenue. 

    By embedding privacy into the core of your product, you give users more reasons to select, stay and support your business. 

    2. Higher Operational Efficiency

    Customer data protection isn’t just a policy – it’s a culture of collecting “just enough” data, protecting it and using it responsibly. 

    Sadly, that’s the area where most organisations trail behind. At present, some 90% of businesses admit to having amassed massive data silos. 

    Siloed data is expensive to maintain and operationalise. Moreover, when left unattended, it can evolve into a pressing compliance issue. 

    A recently leaked document from Facebook says the company has no idea where all of its first-party, third-party and sensitive categories data goes or how it is processed. Because of this, Facebook struggles to achieve GDPR compliance and remains under regulatory pressure. 

    Similarly, Google Analytics is riddled with privacy issues. Other company products were found to be collecting and operationalising consumer data without users’ knowledge or consent. Again, this creates valid grounds for regulatory investigations. 

    Smaller companies have a better chance of making things right at the onset. 

    By curbing customer data collection, you can : 

    • Reduce data hosting and Cloud computation costs (aka trim your Cloud bill) 
    • Improve data security practices (since you would have fewer assets to protect) 
    • Make your staff more productive by consolidating essential data and making it easy and safe to access

    Privacy-mindful companies also have an easier time when it comes to compliance and can meet new data regulations faster. 

    3. Better Marketing Campaigns 

    The biggest counter-argument to reducing customer data collection is marketing. 

    How can we effectively sell our products if we know nothing about our customers ? – your team might be asking. 

    This might sound counterintuitive, but minimising data collection and usage can lead to better marketing outcomes. 

    Limiting the types of data that can be used encourages your people to become more creative and productive by focusing on fewer metrics that are more important.

    Think of it this way : Every other business uses the same targeting parameters on Facebook or Google for running paid ad campaigns on Facebook. As a result, we see ads everywhere — and people grow unresponsive to them or choose to limit exposure by using ad blocking software, private browsers and VPNs. Your ad budgets get wasted on chasing mirage metrics instead of actual prospects. 

    Case in point : In 2017 Marc Pritchard of Procter & Gamble decided to first cut the company’s digital advertising budget by 6% (or $200 million). Unilever made an even bolder move and reduced its ad budget by 30% in 2018. 

    Guess what happened ?

    P&G saw a 7.5% increase in organic sales and Unilever had a 3.8% gain as HBR reports. So how come both companies became more successful by spending less on advertising ? 

    They found that overexposure to online ads led to diminishing returns and annoyances among loyal customers. By minimising ad exposure and adopting alternative marketing strategies, the two companies managed to market better to new and existing customers. 

    The takeaway : There are more ways to engage consumers aside from pestering them with repetitive retargeting messages or creepy personalisation. 

    You can collect first-party data with consent to incrementally improve your product — and educate them on the benefits of your solution in transparent terms.

    Final Thoughts 

    The definitive advantage of privacy is consumers’ trust. 

    You can’t buy it, you can’t fake it, you can only cultivate it by aligning your external appearances with internal practices. 

    Because when you fail to address privacy internally, your mishaps will quickly become apparent either as social media call-outs or worse — as a security incident, a data breach or a legal investigation. 

    By choosing to treat consumer data with respect, you build an extra layer of protection around your business, plus draw in some banging benefits too. 

    Get one step closer to becoming a privacy-centred company by choosing Matomo as your web analytics solution. We offer robust privacy controls for ensuring ethical, compliant, privacy-friendly and secure website tracking. 

  • Writing A Dreamcast Media Player

    6 janvier 2017, par Multimedia Mike — Sega Dreamcast

    I know I’m not the only person to have the idea to port a media player to the Sega Dreamcast video game console. But I did make significant progress on an implementation. I’m a little surprised to realize that I haven’t written anything about it on this blog yet, given my propensity for publishing my programming misadventures.


    3 Dreamcast consoles in a row

    This old effort had been on my mind lately due to its architectural similarities to something else I was recently brainstorming.

    Early Days
    Porting a multimedia player was one of the earliest endeavors that I embarked upon in the multimedia domain. It’s a bit fuzzy for me now, but I’m pretty sure that my first exposure to the MPlayer project in 2001 arose from looking for a multimedia player to port. I fed it through the Dreamcast development toolchain but encountered roadblocks pretty quickly. However, this got me looking at the MPlayer source code and made me wonder how I could contribute, which is how I finally broke into practical open source multimedia hacking after studying the concepts and technology for more than a year at that point.

    Eventually, I jumped over to the xine project. After hacking on that for awhile, I remembered my DC media player efforts and endeavored to compile xine to the console. The first attempt was to simply compile the codebase using the Dreamcast hobbyist community’s toolchain. This is when I came to fear the multithreaded snake pit in xine’s core. Again, my memories are hazy on the specifics, but I remember the engine having a bunch of threading hacks with comments along the lines of “this code deadlocks sometimes, so on shutdown, monitor this lock and deliberately break it if it has been more than 3 seconds”.

    Something Workable
    Eventually, I settled on a combination of FFmpeg’s libavcodec library for audio and video decoders, xine’s demuxer library, and xine’s input API, combined with my own engine code to tie it all together along with video and output drivers provided by the KallistiOS hobbyist OS for Dreamcast. Here is a simple diagram of the data movement through this player :


    Architecture diagram for a Sega Dreamcast media player

    Details and Challenges
    This is a rare occasion when I actually got to write the core of a media player engine. I made some mistakes.

    xine’s internal clock ran at 90000 Hz. At least, its internal timestamps were all in reference to a 90 kHz clock. I got this brilliant idea to trigger timer interrupts at 6000 Hz to drive the engine. Whatever the timer facilities on the Dreamcast, I found that 6 kHz was the greatest common divisor with 90 kHz. This means that if I could have found an even higher GCD frequency, I would have used that instead.

    So the idea was that, for a 30 fps video, the engine would know to render a frame on every 200th timer interrupt. I eventually realized that servicing 6000 timer interrupts every second would incur a ridiculous amount of overhead. After that, my engine’s philosophy was to set a timer to fire for the next frame while beginning to process the current frame. I.e., when rendering a frame, set a timer to call back in 1/30th of a second. That worked a lot better.

    As I was still keen on 8-bit paletted image codecs at the time (especially since they were simple and small for bootstrapping this project), I got to use output palette images directly thanks to the Dreamcast’s paletted textures. So that was exciting. The engine didn’t need to convert the paletted images to a different colorspace before rendering. However, I seem to recall that the Dreamcast’s PowerVR graphics hardware required that 8-bit textures be twiddled/swizzled. Thus, it was still required to manipulate the 8-bit image before rendering.

    I made good progress on this player concept. However, a huge blocker for me was that I didn’t know how to make a proper user interface for the media player. Obviously, programming the Dreamcast occurred at a very low level (at least with the approach I was using), so there were no UI widgets easily available.

    This was circa 2003. I assumed there must have been some embedded UI widget libraries with amenable open source licenses that I could leverage. I remember searching and checking out a library named libSTK. I think STK stood for “set-top toolkit” and was positioned specifically for doing things like media player UIs on low-spec embedded computing devices. The domain hosting the project is no longer useful but this appears to be a backup of the core code.

    It sounded promising, but the libSTK developers had a different definition of “low-spec embedded” device than I did. I seem to recall that they were targeting something along with likes of a Pentium III clocked at 800 MHz with 128 MB RAM. The Dreamcast, by contrast, has a 200 MHz SH-4 CPU and 16 MB RAM. LibSTK was also authored in C++ and leveraged the Boost library (my first exposure to that code), and this all had the effect of making binaries quite large while I was trying to keep the player in lean C.

    Regrettably, I never made any serious progress on a proper user interface. I think that’s when the player effort ran out of steam.

    The Code
    So, that’s another project that I never got around to finishing or publishing. I was able to find the source code so I decided to toss it up on github, along with 2 old architecture outlines that I was able to dig up. It looks like I was starting small, just porting over a few of the demuxers and decoders that I knew well.

    I’m wondering if it would still be as straightforward to separate out such components now, more than 13 years later ?

    The post Writing A Dreamcast Media Player first appeared on Breaking Eggs And Making Omelettes.

  • Grand Unified Theory of Compact Disc

    1er février 2013, par Multimedia Mike — General

    This is something I started writing about a decade ago (and I almost certainly have some of it wrong), back when compact discs still had a fair amount of relevance. Back around 2002, after a few years investigating multimedia technology, I took an interest in compact discs of all sorts. Even though there may seem to be a wide range of CD types, I generally found that they’re all fundamentally the same. I thought I would finally publishing something, incomplete though it may be.

    Physical Perspective
    There are a lot of ways to look at a compact disc. First, there’s the physical format, where a laser detects where pits/grooves have disturbed the smooth surface (a.k.a. lands). A lot of technical descriptions claim that these lands and pits on a CD correspond to ones and zeros. That’s not actually true, but you have to decide what level of abstraction you care about, and that abstraction is good enough if you only care about the discs from a software perspective.

    Grand Unified Theory (Software Perspective)
    Looking at a disc from a software perspective, I have generally found it useful to view a CD as a combination of a 2 main components :

    • table of contents (TOC)
    • a long string of sectors, each of which is 2352 bytes long

    I like to believe that’s pretty much all there is to it. All of the information on a CD is stored as a string of sectors that might be chopped up into a series of anywhere from 1-99 individual tracks. The exact sector locations where these individual tracks begin are defined in the TOC.

    Audio CDs (CD-DA / Red Book)
    The initial purpose for the compact disc was to store digital audio. The strange sector size of 2352 bytes is an artifact of this original charter. “CD quality audio”, as any multimedia nerd knows, is formally defined as stereo PCM samples that are each 16 bits wide and played at a frequency of 44100 Hz.

    (44100 audio frames / 1 second) * (2 samples / audio frame) * 
      (16 bits / 1 sample) * (1 byte / 8 bits) = 176,400 bytes / second
    (176,400 bytes / 1 second) / (2352 bytes / 1 sector) = 75
    

    75 is the number of sectors required to store a single second of CD-quality audio. A single sector stores 1/75th of a second, or a ‘frame’ of audio (though I think ‘frame’ gets tossed around at all levels when describing CD formats).

    The term “red book” is thrown around in relation to audio CDs. There is a series of rainbow books that define various optical disc standards and the red book describes audio CDs.

    Basic Data CD-ROMs (Mode 1 / Yellow Book)
    Somewhere along the line, someone decided that general digital information could be stored on these discs. Hence, the CD-ROM was born. The standard model above still applies– TOC and string of 2352-byte sectors. However, it’s generally only useful to have a single track on a CD-ROM. Thus, the TOC only lists a single track. That single track can easily span the entire disc (something that would be unusual for a typical audio CD).

    While the model is mostly the same, the most notable difference between and audio CD and a plain CD-ROM is that, while each sector is 2352 bytes long, only 2048 bytes are used to store actual data payload. The remaining bytes are used for synchronization and additional error detection/correction.

    At least, the foregoing is true for mode 1 / form 1 CD-ROMs (which are the most common). “Mode 1″ CD-ROMs are defined by a publication called the yellow book. There is also mode 1 / form 2. This forgoes the additional error detection and correction afforded by form 1 and dedicates 2336 of the 2352 sector bytes to the data payload.

    CD-ROM XA (Mode 2 / Green Book)
    From a software perspective, these are similar to mode 1 CD-ROMs. There are also 2 forms here. The first form gives a 2048-byte data payload while the second form yields a 2324-byte data payload.

    Video CD (VCD / White Book)
    These are CD-ROM XA discs that carry MPEG-1 video and audio data.

    Photo CD (Beige Book)
    This is something I have never personally dealt with. But it’s supposed to conform to the CD-ROM XA standard and probably fits into my model. It seems to date back to early in the CD-ROM era when CDs were particularly cost prohibitive.

    Multisession CDs (Blue Book)
    Okay, I admit that this confuses me a bit. Multisession discs allow a user to burn multiple sessions to a single recordable disc. I.e., burn a lump of data, then burn another lump at a later time, and the final result will look like all the lumps were recorded as the same big lump. I remember this being incredibly useful and cost effective back when recordable CDs cost around US$10 each (vs. being able to buy a spindle of 100 CD-Rs for US$10 or less now). Studying the cdrom.h file for the Linux OS, I found a system call named CDROMMULTISESSION that returns the sector address of the start of the last session. If I were to hypothesize about how to make this fit into my model, I might guess that the TOC has some hint that the disc was recorded in multisession (which needs to be decided up front) and the CDROMMULTISESSION call is made to find the last session. Or it could be that a disc read initialization operation always leads off with the CDROMMULTISESSION query in order to determine this.

    I suppose I could figure out how to create a multisession disc with modern software, or possibly dig up a multisession disc from 15+ years ago, and then figure out how it should be read.

    CD-i
    This type puzzles my as well. I do have some CD-i discs and I thought that I could read them just fine (the last time I looked, which was many years ago). But my research for this blog post has me thinking that I might not have been seeing the entire picture when I first studied my CD-i samples. I was able to see some of the data, but sources indicate that only proper CD-i hardware is able to see all of the data on the disc (apparently, the TOC doesn’t show all of the sectors on disc).

    Hybrid CDs (Data + Audio)
    At some point, it became a notable selling point for an audio CD to have a data track with bonus features. Even more common (particularly in the early era of CD-ROMs) were computer and console games that used the first track of a disc for all the game code and assets and the remaining tracks for beautifully rendered game audio that could also be enjoyed outside the game. Same model : TOC points to the various tracks and also makes notes about which ones are data and which are audio.

    There seems to be 2 distinct things described above. One type is the mixed mode CD which generally has the data in the first track and the audio in tracks 2..n. Then there is the enhanced CD, which apparently used multisession recording and put the data at the end. I think that the reasoning for this is that most audio CD player hardware would only read tracks from the first session and would have no way to see the data track. This was a positive thing. By contrast, when placing a mixed-mode CD into an audio player, the data track would be rendered as nonsense noise.

    Subchannels
    There’s at least one small detail that my model ignores : subchannels. CDs can encode bits of data in subchannels in sectors. This is used for things like CD-Text and CD-G. I may need to revisit this.

    In Summary
    There’s still a lot of ground to cover, like how those sectors might be formatted to show something useful (e.g., filesystems), and how the model applies to other types of optical discs. Sounds like something for another post.