A catalog server provides a single point of access that allows users to centrally search for information across a distributed network. In other words, it indexes databases, files and information across large network and allows keywords, Boolean and other searches. If you need to provide a comprehensive searching service for your intranet, extranet or even the Internet, a catalog server is a standard solution.
Deep tomographic reconstruction
Deep Tomographic Reconstruction is a set of methods for using deep learning methods to perform tomographic reconstruction of medical and industrial images. It uses artificial intelligence and machine learning, especially deep artificial neural networks or deep learning, to overcome challenges such as measurement noise, data sparsity, image artifacts, and computational inefficiency. This approach has been applied across various imaging modalities, including CT, MRI, PET, SPECT, ultrasound, and optical imaging == Historical background == Traditional tomographic reconstruction relies on analytic methods such as filtered back-projection, or iterative methods which incrementally compute inverse transformations from measurement data (e.g., Radon or Fourier transform data). However, these approaches are not sufficient for certain imaging techniques such as low-dose CT and fast MRI, or scenarios involving metal artifacts and patient motion. == Use in imaging modalities == === Computed tomography (CT) === In CT, deep learning models can be particularly effective in reducing radiation exposure while maintaining image quality. Deep neural networks can also be able to reconstruct images of fair quality from sparsely sampled data without sacrificing diagnostic performance. Deep learning-based generative AI models can reduce CT metal artifacts. === Magnetic resonance imaging (MRI) === In magnetic resonance imaging (MRI), deep learning can lead to reduced MRI motion artifacts, and increased acquisition speed, referred to as fast MRI. Despite suffering from disadvantages such as lower signal-to-noise ratio (SNR), deep learning can enhance image quality in low field MRI, making these systems clinically viable. === Positron emission tomography (PET) and single-photon emission CT (SPECT) === For PET imaging, deep learning models can provide substantial improvements in low-dose imaging and motion artifact correction. Also, deep learning can help SPECT for generation of attenuation background. A notable technique for PET denoising involves integrating MR data through multimodal networks, which use anatomical information from MRI to enhance PET image quality. === Ultrasound imaging === Deep learning can enhance ultrasound imaging by reducing speckle noise and motion blur. For ultrasound beamforming, deep neural networks can allow superior image quality with limited data at high speed. === Optical imaging and microscopy === Diffuse optical tomography, optical coherence tomography and microscopy can be improved by deep neural networks beyond traditional methods. Furthermore, deep learning can also enhance Photoacoustic imaging (see Deep learning in photoacoustic imaging), addressing challenges like high noise, low contrast, and limited resolution. Deep learning has also been applied to label-free live-cell imaging, where convolutional neural networks predict fluorescence labels from transmitted light images, a technique known as in silico labeling. This method can enable high-throughput, non-invasive cell analysis and phenotyping without the need for traditional fluorescent dyes.
Cyber-Duck
Cyber-Duck is a digital transformation agency founded in 2005 and based in Elstree, United Kingdom. The company specialises in user experience (UX), software development and digital optimisation. The company employs over 90 staff in the UK and Europe. It works with clients from the financial, pharmaceutical, sport, motoring and security sectors, among others. These include the Bank of England, Cancer Research UK, GOV.UK Verify partner CitizenSafe, The Commonwealth of Nations and Sport England. == History == Cyber-Duck was founded in 2005 by Danny Bluestone in his flat in Mill Hill, United Kingdom. After a few months, the firm moved into its first office in Borehamwood. Projects with Ogilvy, London Creative and Wisteria followed before Cyber-Duck moved to offices in Devonshire House, Borehamwood. In 2010, the firm was commissioned to develop a website for the European Commission in the UK. In 2011, the company moved to a self-contained premises in Elstree, Hertfordshire. Shortly afterward, Cyber-Duck was listed on the Deloitte Technology Fast 500 EMEA in recognition of its substantial revenue growth over the previous five years. As the company grew, its expertise also broadened. This resulted in guest spots on several television shows. Cyber-Duck was featured in an episode of the Gadget Show in 2011, and Chief Production Officer Matt Gibson appeared on BBC Watchdog in 2013 to assist in researching websites and their checkout processes. The firm continued to attract business from companies in London, so the decision was made to open a new office in central London. The Farringdon office opened in 2015, and was followed by a rebrand. In 2016, Cyber-Duck went on to work with the Bank of England. Ahead of the launch of the new polymer £5 note, featuring Winston Churchill, the company was tasked with creating a user-friendly website to showcase the new banknote and promote public awareness. The success of the campaign led to further commissions, including 2017's website the New Ten and a redesign of the Bank of England's main website. The firm underwent significant growth in 2020, beginning working partnerships with Sport England and the College of Policing. During this time they also launched DevOps as a new service. In 2022, the Farringdon office closed and was relocated to a new office space in Holborn. The Laravel, Drupal and DevOps teams expanded, and Cyber-Duck became the lead Digital Agency for Worcester, Bosch Group. Several members of the team appeared on The Digital Society on Sky UK. == Awards and accreditations == Cyber-Duck is known for its focus on process accreditation as a driver of creativity. In 2011, the company obtained its first ISO 9241 accreditation in Human Centred Design for interactive systems. Two years later, Cyber-Duck obtained a further certification, the ISO 9001 for Quality Management Systems. It acquired another certification in 2016 with the ISO 27001 – the focus of this accreditation was Information Security Management. In 2022, Cyber-Duck gained the ISO 14001 certification in Environmental Management. Cyber-Duck's digital products have won numerous Wirehive 100, BIMA and Webby awards. Notably, the company's UX Companion, a free iOS and Android app that is a glossary of UX theories, featured in Usability Geek and Smashing Magazine. In 2021 they were awarded as one of the UK's 100 Best Small Companies to work for, and BIMA10 shortlisted for their work with Sport England and This Girl Can.
IBM Retail Store Systems
This article describes IBM point of sale equipment from 1973 with the introduction of the IBM 3650 till 1986 with the introduction of the IBM 4680. IBM continued to announced new retail products until the sale of the IBM Retail Store Solutions business to Toshiba TEC, announced on 17 April 17 2012. == Background == IBM began selling retail point of sale systems starting in 1973 with the IBM 3650 Retail Store System aimed at department and chain stores and the IBM 3660 Supermarket System designed for supermarkets. The IBM 3650 was announced alongside other IBM vertical industry systems such as the IBM 3600 Finance Communication System, and the IBM 3790 communications system, the combination of which IBM described as a "revolution in terminal based systems". All of these systems relied on a significant number of developments across IBM: New chips: Large Scale Integration allowed advanced Field Effect Transistor logic chips that packed far more transistors onto a new metalized one-inch square ceramic substrate Gas panels: Developed as an alternative to cathode ray tubes, the neon argon gas panel provided clear and flicker-free images. Modem communications: Synchronous Data Link Control provided lower-cost communications over telephone lines New disks: The "Gulliver" disk file that supplied a hard drive smaller than three cubic feet and also the "Igar" diskette drive Smaller printers: A disk printer system called "spica" that used a rotating disk print element with engraved print elements that are struck by a single hammer as the disk rotates Belt printers: A new system, known as "Lynx," using a removable belt that was significantly cheaper, quieter and simpler than earlier chain printers Keyboards: New keyboard technology called "Calico" that could build a wide variety of keyboards using common manufacturing facilities Power supplies: Transistorised Switching Regulators or TsRs: compact power supplies that are one third to one-fourth the size of previous generations === Store Loop (SLOOP) architecture === The 36xx retail terminals are connected to the store controller via a loop also called a Store Loop, similar to that used by the IBM 3600 Finance System. If a terminal detects an error, it runs a self-diagnosis routine, displays an error code to the operator, and uses bypass circuitry to remove itself from the loop and allow the loop to continue operating. If the loop fails, the most downstream terminal transmits an error code to the controller. Intermittent errors are written to disk on the store controller. === Supplies Manufacturing === While IBM's Data Processing Division created the retail store systems, it's Information Record Division (IRD) also saw signifiant opportunity in manufacturing supplies for retail systems. As an example in their Dayton NJ plant they used a high-speed Webtron press to create up to 1 million magnet merchandise tags per shift. == IBM 3650 Retail Store System == The 3650 System is a family of products designed to computerise a retail store, both at the point of sale and for back office store management functions. It includes a method to generate encoded tickets for merchandise, rather than use the Universal Product Code (UPC). The key devices for the system were as follows: === Shop Floor === ==== 3653 Point of Sale Terminal ==== Designed for the store floor, it is a loop attached device with: a wire matrix printer with 3 stations: cash receipt, sales-check and transaction journal. a keyboard with 10 numeric keys and 19 function keys an 8 digit display and description lights. in addition to the 8 digits it also displays the following characters: "$", "." and "-" operator guidance panel with 20 backlit captions status indicators a cash drawer a check verification station. Options include a wand magnet label reader with a 4 foot flexible cord, and locks for the journal tape and the till cover. The terminal effectively loads its software remotely from the 3651 over the loop, which IBM calls an IML (initial microcode load). It can also be IMLed locally using a tape cassette recorder. IBM later offered a choice of OEM Wand Attachments that could be ordered by RPQ that could use OCR or scan UPCs, instead of a wand magnet label reader. Only one wand could be attached to a specific 3653. There are two models: Model 1, which is not programmable. Was announced 10 August 1973. Model P1, which is customer programmable. Has 36 KB of storage expandable to 60 KB. Was announced 13 October 1978. === Back office equipment === ==== 3651 Store Controller ==== Controls data flow inside either a single store or multiple stores and sends retail transactions to a mainframe using a modem. For point of sale it performed functions such as: Automatic price lookup from a master price file Automatic distribution of net sales by up to 54 departments Automatic application of applicable discounts and sales taxes Automatic control of food stamp maximums Check authorization facilities For back office it also helped report preparation such as: store summary individual cashier performance store office reconciliation sales by up to 54 departments Current inquiries for department sales; cashier performance & cash position; store cash position. Inquiries and changes to the master price records and operator authorization control records. Setting the time and date for the internal clock. Running the customer checkouts in training mode. Printing of messages received from the host mainframe Entry of messages to send to the host mainframe Reporting of customer stock returns Updating the system with data received from the mainframe Preparing shelf Labels Basic features include: Each loop attaches up to 63 or 64 terminals depending on traffic volumes and desired response times Has an error and operator panel. There were many models including: A25 Has a 5 MB internal disk. Has 60K of memory expandable to 76KB. Supports one store loop. Attaches to 3275, 3653 and 3663. Announced 19 May 1978, withdrawn 19 February 1981 B25 Same as a A25 with a 9.2 MB internal disk. Announced 19 May 1978 C25 Announced 15 May 1981, withdrawn 15 December 1987 A50 Has a 5 MB internal disk. Announced 5 May 1975. Announced 10 August 1973, withdrawn 15 December 1987 B50 Same as B50 with a 9.2 MB internal disk. Announced 5 May 1975, withdrawn 15 December 1987 A60 Has a 5 MB internal disk. Has an integrated 3669. Attaches up to 24 3663 terminals. Announced 11 October 1973, withdrawn 15 December 1987 B60 Same as A60 with a 9.3 MB internal disk. Announced 17 November 1975, withdrawn 15 December 1987 A75 Has 5 MB internal disk. Has 60K of memory expandable to 124KB. Supports one to three store loops. Attaches to 3275, 3653, 3657, 3784 and 3663 terminals. Announced 19 May 1978 B75 Same as A75 with 9.3 MB internal disk. Announced 19 May 1978, withdrawn 15 December 1987 C75 Same as A75 with 18.6 MB internal disk. Announced 19 May 1978, withdrawn 15 December 1987 D75 Same as A75 with 27.9 MB internal disk. Announced 19 May 1978, withdrawn 15 December 1987 There were also two additional models that could be used instead of the 3651: 7480 Model 1: Has a 18.6 MB internal disk 7480 Model 2: Has a 27.9 MB internal disk ==== 3872 Modem ==== Used to attach to a 3659 for remote loops. Each 3872 can attach three 3659s. ==== 3659 Remote Communication Unit ==== Connected to an IBM 3872 and provides a remote loop for up to 64 point of sale terminals. Announced 10 August 1973, withdrawn 15 December 1987 (Model 2, announced 17 March 1976, withdrawn 20 December 1982) Intended to be used in a back office location like the store manager's office or the data entry office ==== 3275-3 Display Station ==== It is a loop attached display terminal with printer attachment hardware ==== 3784 Line Printer ==== A belt printer for higher-volume end-of-day reporting. The maximum print speed is 155 Ipm using a 48 character set. ==== 3657 Ticket Unit ==== Used to print tickets and encoded labels to attach to store merchandise. It is a loop attached device. It prints the following: 1" by 1" adhesive backed labels with up to 11 characters at 500 tickets per minute. IBM sold these in rolls of 9000 1" x 2" tickets with up to 42 encoded characters and two lines of print of up to 21 characters at 250 tickets per minute. IBM sold these in rolls of 2800 1" x 3" tickets with up to 79 encoded characters and two lines of print of up to 32 characters at 167 tickets per minute. IBM sold these in rolls of 1900 It can also batch read the tickets for validation, separating good tickets from bad ones into two cartridges. Announced 10 August 1973, withdrawn 15 December 1987 ==== 7481 Data Storage Unit ==== This optional unit is used to record transaction data and initialize terminals if the store controller is not available. It uses a built in tape drive to store this data. === Early deployments === The first customer installation of a 3650 was at a Dillard's department store in Little Rock, Arkansas, in late 1974. They placed arou
Blocking of Twitter in Nigeria
Twitter was blocked in Nigeria from 5 June 2021 to 13 January 2022. The government imposed a ban on the social network after it deleted tweets made by, and temporarily suspended, the Nigerian president Muhammadu Buhari, warning the southeastern people of Nigeria, predominantly Igbo people, of a potential repeat of the 1967 Nigerian Civil War due to the ongoing insurgency in Southeastern Nigeria. The Nigerian government claimed that the deletion of the president's tweets factored into their decision, but it was ultimately based on "a litany of problems with the social media platform in Nigeria, where misinformation and fake news spread through it have had real world violent consequences", citing the persistent use of the platform for activities that are capable of undermining Nigeria's corporate existence. In January 2022, Nigeria lifted its blocking of Twitter after the platform agreed to establish a legal entity within the country sometime in the first quarter of 2022. == Background == On 1 June 2021, Nigerian President Muhammadu Buhari posted a tweet threatening a crackdown on regional separatists "in the language they understand". The next day, Twitter deleted the tweet, claiming it was in violation of Twitter rules, but gave no further details. Nigeria's Information Minister Lai Mohammed said that Twitter's actions were part of an unfair double standard, as Twitter had not banned incitement tweets from other groups. During the Nigerian Civil War a majority of deaths resulted from the blockade of Biafra which caused the deaths of millions of civilians from starvation, a fact that was not alluded to in the tweet. The Nigerian government has long held concerns over the use of Twitter in the country. The ongoing local End SARS protest began on Twitter and got amplified in 2020 when it had 48 million tweets in ten days. Buhari's government floated the idea of social media regulation on different occasions prior to banning Twitter. Attempts to pass an anti-social media bill in the past have failed majorly due to massive outcry on Twitter. Days before the ban, the country's minister of information called Twitter's activities in Nigeria suspicious, citing its influence on the End SARS protests. == Aftermath == Three days after Twitter was suspended, it was reported that the move had cost the country over 6 billion naira and would also contribute to the worsening unemployment in the country. ExpressVPN reported an over 200 percent increase in web traffic and searches for VPN spiked across the country. In response, Nigeria's Minister of Justice and Attorney General of the Federation Abubakar Malami at first openly threatened to prosecute citizens who bypass the ban using a VPN but then denied saying so after a screenshot of a Twitter deactivation notification he shared on Facebook showed a VPN logo. Nigeria's cultural minister Lai Mohammed stated the ban would be lifted once Twitter submitted to locally licensing, registration and conditions. "It will be licensed by the broadcasting commission, and must agree not to allow its platform to be used by those who are promoting activities that are inimical to the corporate existence of Nigeria." In late June 2021, Twitter announced it would enter talks with the Nigerian government over the platform's suspension. The talks began in July 2021. On 15 September 2021, Mohammed said the Nigerian government will lift the ban on Twitter in a "few days." The Minister said Twitter gave a progress report of their talks with them, adding that it has been productive and quite respectful. On 1 October 2021, President Muhammadu Buhari in his Independence Day broadcast said Twitter must meet the Nigerian government's five conditions before the suspension of the social media platform will be lifted. The conditions are: Respect for national security and cohesion; registration, physical presence and representation in Nigeria; fair taxation; dispute resolution; local content. == Reactions == The ban was condemned by Amnesty International, the British, Canadian and Swedish diplomatic missions to Nigeria, as well as the United States and the European Union in a joint statement. Two domestic organizations, the Socio-Economic Rights and Accountability Project (SERAP) and the Nigerian Bar Association, indicated intent to challenge the ban in court. Twitter itself called the ban "deeply concerning". Former U.S. President Donald Trump, who was permanently suspended from Twitter following the United States Capitol attack in January, praised the ban, stating "Congratulations to the country of Nigeria, who just banned Twitter because they banned their President", and also called on other countries to ban Twitter and Facebook due to "not allowing free and open speech." == Lifting of the ban == On 12 January 2022, the Nigerian Government lifted the ban after Twitter agreed to pay an "applicable tax" and establish "a legal entity in Nigeria during the first quarter of 2022".
Kernel-phase
Kernel-phases are observable quantities used in high resolution astronomical imaging used for superresolution image creation. It can be seen as a generalization of closure phases for redundant arrays. For this reason, when the wavefront quality requirement are met, it is an alternative to aperture masking interferometry that can be executed without a mask while retaining phase error rejection properties. The observables are computed through linear algebra from the Fourier transform of direct images. They can then be used for statistical testing, model fitting, or image reconstruction. == Prerequisites == In order to extract kernel-phases from an image, some requirements must be met: Images are nyquist-sampled (at least 2 pixels per resolution element ( λ D {\displaystyle {\frac {\lambda }{D}}} )) Images are taken in near monochromatic light Exposure time is shorter than the timescale of aberrations Strehl ratio is high (good adaptive optics) Linearity of the pixel response (i.e. no saturation) Deviations from these requirements are known to be acceptable, but lead to observational bias that should be corrected by the observation of calibrators. == Definition == The method relies on a discrete model of the instrument's pupil plane and the corresponding list of baselines to provide corresponding vectors φ {\displaystyle \varphi } of pupil plane errors and Φ {\displaystyle \Phi } of image plane Fourier Phases. When the wavefront error in the pupil plane is small enough (i.e. when the Strehl ratio of the imaging system is sufficiently high), the complex amplitude associated to the instrumental phase in one point of the pupil φ k {\displaystyle \varphi _{k}} , can be approximated by e i φ k ≈ 1 + i φ k {\displaystyle e^{i\varphi _{k}}\approx 1+{\mathit {i}}\varphi _{k}} . This permits the expression of the pupil-plane phase aberrations φ {\displaystyle \varphi } to the image plane Fourier phase as a linear transformation described by the matrix A {\displaystyle A} : Φ = Φ 0 + A ⋅ φ {\displaystyle \Phi =\Phi _{0}+A\cdot \varphi } Where Φ 0 {\displaystyle \Phi _{0}} is the theoretical Fourier phase vector of the object. In this formalism, singular value decomposition can be used to find a matrix K {\displaystyle K} satisfying K ⋅ A = 0 {\displaystyle K\cdot A=0} . The rows of K {\displaystyle K} constitute a basis of the kernel of A T {\displaystyle A^{T}} . K ⋅ Φ = K ⋅ Φ 0 + K ⋅ A ⋅ φ {\displaystyle K\cdot \Phi =K\cdot \Phi _{0}+{\cancel {K\cdot A\cdot \varphi }}} The vector K . Φ {\displaystyle K.\Phi } is called the kernel-phase vector of observables. This equation can be used for model-fitting as it represents the interpretation of a sub-space of the Fourier phase that is immune to the instrumental phase errors to the first order. == Applications == The technique was first used in the re-analysis of archival images from the Hubble Space Telescope where it enabled the discovery of a number of brown dwarf in close binary systems. The technique is used as an alternative to aperture masking interferometry, especially for fainter stars because it does not require the use of masks that typically block 90% of the light, and therefore allows higher throughput. It is also considered to be an alternative to coronagraphy for direct detection of exoplanets at very small separations (below 2 λ D {\displaystyle 2{\frac {\lambda }{D}}} ) where coronagraphs are limited by the wavefront errors of adaptive optics. The same framework can be used for wavefront sensing. In the case of an asymmetric aperture, a pseudo-inverse of A {\displaystyle A} can be used to reconstruct the wavefront errors directly from the image. A Python library called xara is available on GitHub and maintained by Frantz Martinache to facilitate the extraction and interpretation of kernel-phases. The KERNEL project, has received funding from the European Research Council to explore the potential of these observables for a number of use-cases, including direct detection of exoplanets, image reconstruction, and image plane wavefront sensing for adaptive optics.
HTTP compression
HTTP compression is a capability that can be built into web servers and web clients to improve transfer speed and bandwidth utilization. HTTP data is compressed before it is sent from the server: compliant browsers will announce what methods are supported to the server before downloading the correct format; browsers that do not support compliant compression method will download uncompressed data. The most common compression schemes include gzip and Brotli; a full list of available schemes is maintained by the IANA. There are two different ways compression can be done in HTTP. At a lower level, a Transfer-Encoding header field may indicate the payload of an HTTP message is compressed. At a higher level, a Content-Encoding header field may indicate that a resource being transferred, cached, or otherwise referenced is compressed. Compression using Content-Encoding is more widely supported than Transfer-Encoding, and some browsers do not advertise support for Transfer-Encoding compression to avoid triggering bugs in servers. == Compression scheme negotiation == The negotiation is done in two steps, described in RFC 2616 and RFC 9110: 1. The web client advertises which compression schemes it supports by including a list of tokens in the HTTP request. For Content-Encoding, the list is in a field called Accept-Encoding; for Transfer-Encoding, the field is called TE. 2. If the server supports one or more compression schemes, the outgoing data may be compressed by one or more methods supported by both parties. If this is the case, the server will add a Content-Encoding or Transfer-Encoding field in the HTTP response with the used schemes, separated by commas. The web server is by no means obligated to use any compression method – this depends on the internal settings of the web server and also may depend on the internal architecture of the website in question. == Content-Encoding tokens == The official list of tokens available to servers and client is maintained by IANA, and it includes: br – Brotli, a compression algorithm specifically designed for HTTP content encoding, defined in RFC 7932 and implemented in all modern major browsers. compress – UNIX "compress" program method (historic; deprecated in most applications and replaced by gzip or deflate) deflate – compression based on the deflate algorithm (described in RFC 1951), a combination of the LZ77 algorithm and Huffman coding, wrapped inside the zlib data format (RFC 1950); exi – W3C Efficient XML Interchange gzip – GNU zip format (described in RFC 1952). Uses the deflate algorithm for compression, but the data format and the checksum algorithm differ from the "deflate" content-encoding. This method is the most broadly supported as of March 2011. identity – No transformation is used. This is the default value for content coding. pack200-gzip – Network Transfer Format for Java Archives zstd – Zstandard compression, defined in RFC 8478 In addition to these, a number of unofficial or non-standardized tokens are used in the wild by either servers or clients: bzip2 – compression based on the free bzip2 format, supported by lighttpd lzip – compression based on the free lzip format, supported by wget and Links lzma – compression based on (raw) LZMA is available in Opera 20, and in elinks via a compile-time option peerdist – Microsoft Peer Content Caching and Retrieval rsync – delta encoding in HTTP, implemented by a pair of rproxy proxies. xpress – Microsoft compression protocol used by Windows 8 and later for Windows Store application updates. LZ77-based compression optionally using a Huffman encoding. xz – LZMA2-based content compression, supported by a non-official Firefox patch; and fully implemented in mget since 2013-12-31. == Servers that support HTTP compression == SAP NetWeaver Microsoft IIS: built-in or using third-party module Apache HTTP Server, via mod_deflate (despite its name, only supporting gzip), and mod_brotli Hiawatha HTTP server: serves pre-compressed files Cherokee HTTP server, On the fly gzip and deflate compressions Oracle iPlanet Web Server Zeus Web Server lighttpd nginx – built-in Applications based on Tornado, if "compress_response" is set to True in the application settings (for versions prior to 4.0, set "gzip" to True) Jetty Server – built-into default static content serving and available via servlet filter configurations GeoServer Apache Tomcat IBM Websphere AOLserver Ruby Rack, via the Rack::Deflater middleware HAProxy Varnish – built-in. Works also with ESI Armeria – Serving pre-compressed files NaviServer – built-in, dynamic and static compression Caddy – built-in via encode Many content delivery networks also implement HTTP compression to improve speedy delivery of resources to end users. The compression in HTTP can also be achieved by using the functionality of server-side scripting languages like PHP, or programming languages like Java. Various online tools exist to verify a working implementation of HTTP compression. These online tools usually request multiple variants of a URL, each with different request headers (with varying Accept-Encoding content). HTTP compression is considered to be implemented correctly when the server returns a document in a compressed format. By comparing the sizes of the returned documents, the effective compression ratio can be calculated (even between different compression algorithms). == Problems preventing the use of HTTP compression == A 2009 article by Google engineers Arvind Jain and Jason Glasgow states that more than 99 person-years are wasted daily due to increase in page load time when users do not receive compressed content. This occurs when anti-virus software interferes with connections to force them to be uncompressed, where proxies are used (with overcautious web browsers), where servers are misconfigured, and where browser bugs stop compression being used. Internet Explorer 6, which drops to HTTP 1.0 (without features like compression or pipelining) when behind a proxy – a common configuration in corporate environments – was the mainstream browser most prone to failing back to uncompressed HTTP. Another problem found while deploying HTTP compression on large scale is due to the deflate encoding definition: while HTTP 1.1 defines the deflate encoding as data compressed with deflate (RFC 1951) inside a zlib formatted stream (RFC 1950), Microsoft server and client products historically implemented it as a "raw" deflated stream, making its deployment unreliable. For this reason, some software, including the Apache HTTP Server, only implements gzip encoding. == Security implications == Compression allows a form of chosen plaintext attack to be performed: if an attacker can inject any chosen content into the page, they can know whether the page contains their given content by observing the size increase of the encrypted stream. If the increase is smaller than expected for random injections, it means that the compressor has found a repeat in the text, i.e. the injected content overlaps the secret information. This is the idea behind CRIME. In 2012, a general attack against the use of data compression, called CRIME, was announced. While the CRIME attack could work effectively against a large number of protocols, including but not limited to TLS, and application-layer protocols such as SPDY or HTTP, only exploits against TLS and SPDY were demonstrated and largely mitigated in browsers and servers. The CRIME exploit against HTTP compression has not been mitigated at all, even though the authors of CRIME have warned that this vulnerability might be even more widespread than SPDY and TLS compression combined. In 2013, a new instance of the CRIME attack against HTTP compression, dubbed BREACH, was published. A BREACH attack can extract login tokens, email addresses or other sensitive information from TLS encrypted web traffic in as little as 30 seconds (depending on the number of bytes to be extracted), provided the attacker tricks the victim into visiting a malicious web link. All versions of TLS and SSL are at risk from BREACH regardless of the encryption algorithm or cipher used. Unlike previous instances of CRIME, which can be successfully defended against by turning off TLS compression or SPDY header compression, BREACH exploits HTTP compression which cannot realistically be turned off, as virtually all web servers rely upon it to improve data transmission speeds for users. As of 2016, the TIME attack and the HEIST attack are now public knowledge.