AI App Q

AI App Q — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  PenTile matrix family

  PenTile matrix is a family of patented subpixel matrix schemes used in electronic device displays. PenTile is a trademark of Samsung. PenTile matrices are used in AMOLED and LCD displays. These subpixel layouts are specifically designed to operate with proprietary algorithms for subpixel rendering embedded in the display driver, allowing plug and play compatibility with conventional RGB (Red-Green-Blue) stripe panels. == Overview == "PenTile Matrix" (a neologism from penta-, meaning "five" in Greek and tile) describes the geometric layout of the prototypical subpixel arrangement developed in the early 1990s. The layout consists of a quincunx comprising two red subpixels, two green subpixels, and one central blue subpixel in each unit cell. It was inspired by biomimicry of the human retina, which has nearly equal numbers of L and M type cone cells, but significantly fewer S cones. As the S cones are primarily responsible for perceiving blue colors, which do not appreciably affect the perception of luminance, reducing the number of blue subpixels with respect to the red and green subpixels in a display does not reduce the image quality. However, the layout may cause color leakage image distortion, which can be reduced by filters. In some cases the layout causes reduced moiré and blockiness compared to conventional RGB layouts. The PenTile layout is specifically designed to work with and be dependent upon subpixel rendering that uses only one and a quarter subpixel per pixel, on average, to render an image. That is, that any given input pixel is mapped to either a red-centered logical pixel, or a green-centered logical pixel. === History === PenTile was invented by Candice H. Brown Elliott, for which she was awarded the Society for Information Display's Otto Schade Prize in 2014. The technology was licensed by the company Clairvoyante from 2000 until 2008, during which time several prototype PenTile displays were developed by a number of Asian liquid crystal display (LCD) manufacturers. In March 2008, Samsung Electronics acquired Clairvoyante's PenTile IP assets. Samsung then funded a new company, Nouvoyance, Inc. to continue development of the PenTile technology. == PenTile RGBG == PenTile RGBG layout used in AMOLED and plasma displays uses green pixels interleaved with alternating red and blue pixels. The human eye is most sensitive to green, especially for high resolution luminance information. The green subpixels are mapped to input pixels on a one-to-one basis. The red and blue subpixels are subsampled, reconstructing the chroma signal at a lower resolution. The luminance signal is processed using adaptive subpixel rendering filters to optimize reconstruction of high spatial frequencies from the input image, wherein the green subpixels provide the majority of the reconstruction. The red and blue subpixels are capable of reconstructing the horizontal and vertical spatial frequencies, but not the highest of the diagonal. Diagonal high spatial frequency information in the red and blue channels of the input image are transferred to the green subpixels for image reconstruction. Thus the RG-BG scheme creates a color display with one third fewer subpixels than a traditional RGB-RGB scheme but with the same measured luminance display resolution. This is similar to the Bayer filter commonly used in digital cameras. === Devices === As of 2021, "almost all" OLED screens in portable consumer devices use some form of Pentile subpixel layout. == PenTile RGBW == PenTile RGBW technology, used in LCD, adds an extra subpixel to the traditional red, green and blue subpixels that is a clear area without color filtering material and with the only purpose of letting backlight come through, hence W for white. This makes it possible to produce a brighter image compared to an RGB-matrix while using the same amount of power, or produce an equally bright image while using less power. The PenTile RGBW layout uses each red, green, blue and white subpixel to present high-resolution luminance information to the human eyes' red-sensing and green-sensing cone cells, while using the combined effect of all the color subpixels to present lower-resolution chroma (color) information to all three cone cell types. Combined, this optimizes the match of display technology to the biological mechanisms of human vision. The layout uses one third fewer subpixels for the same resolution as the RGB stripe (RGB-RGB) layout, in spite of having four color primaries instead of the conventional three, using subpixel rendering combined with metamer rendering. Metamer rendering optimizes the energy distribution between the white subpixel and the combined red, green, and blue subpixels: W <> RGB, to improve image sharpness. The display driver chip has an RGB to RGBW color vector space converter and gamut mapping algorithm, followed by metamer and subpixel rendering algorithms. In order to maintain saturated color quality, to avoid simultaneous contrast error between saturated colors and peak white brightness, while simultaneously reducing backlight power requirements, the display backlight brightness is under control of the PenTile driver engine. When the image is mostly desaturated colors, those near white or grey, the backlight brightness is significantly reduced, often to less than 50% peak, while the LCD levels are increased to compensate. When the image has very bright saturated colors, the backlight brightness is maintained at higher levels. The PenTile RGBW also has an optional high-brightness mode that doubles the brightness of the desaturated color image areas, such as black-and-white text, for improved outdoor viewability. === Devices === Motorola MC65 Motorola ES55 Motorola ES400 Motorola Atrix 4G Samsung Galaxy Note 10.1 2014 version Lenovo Yoga 2 Pro Lenovo Yoga 3 Pro HP ENVY TouchSmart 14-k022tx Sleekbook MSI GS60 Ghost Pro 4K Lenovo IdeaPad Y50 4K Asus ZenBook UX303LN 4K Asus ZenBook Pro UX501JW LG UH7500/6500/6100 LG ThinQ G7/G7+ Oculus Quest 1 == Controversy == An ongoing controversy regarding the definition or measurement of resolution of color subpixelated flat panel displays led many people to question the resolution claims of PenTile display products. Journalists have noted that in "just about every flat-panel TV in existence, each pixel is composed of one red, one green, and one blue subpixel (RGB), all of uniform size". In traditional flat-panel screens, the resolution is defined by the number of red, green, and blue subpixels, in groups of three, in an array in each axis. As a result, each pixel or group of subpixels can render any colour on the screen, regardless of neighbouring pixels. This is not the case with PenTile screens. The Video Electronics Standards Association (VESA) method of measuring and defining resolution in color displays is to measure the contrast of line pairs, requiring a minimum of 50% Michelson contrast for displays intended for rendering text. The developers of PenTile displays use this VESA criterion for contrast of line pairs to calculate the resolutions specified. In the RGBG layout the alternate red and blue subpixels are 'shared' or sub-sampled with neighboring pixels. Due to the one third lower subpixel density on PenTile displays the pixel structure may be more visible when compared to RGB stripe displays with the same pixel density. The loss of subpixels for a given resolution specification has led some journalists to describe the use of PenTile as "shady practice" and "sort of cheating". For a given size and resolution specification, the PenTile screen can appear grainy, pixelated, speckled, with blurred text on some saturated colors and backgrounds when compared to RGB stripe color. This effect is understood to be caused by the restriction of the number of subpixels that may participate in the image reconstruction when colors are highly saturated to primaries. In the RGBW case, this is caused as the W subpixel will not be available in order to maintain the saturated color. In the RGBG case, this effect will occur when the color boundary is primarily red or blue, as the fully populated (one green per pixel) sub-pixel cannot contribute. For all other cases, text and especially full color images are effectively reconstructed. == Advantages and disadvantages == The PenTile layout reduces the number of subpixels needed to create a specified resolution. Consequently it is possible to achieve an HD resolution on a PenTile AMOLED screen at lower cost than other technologies, and most reviewers note that "300 ppi" (as per VESA - not full pixels) resolution displays (such as Samsung Galaxy S III) make the PenTile effect less obvious than lower resolution PenTile displays (Droid Razr). The second advantage is lower power consumption: the HTC One S's use of a PenTile display makes it more energy efficient and thinner than equivalent LCD screens, giving it better battery life than the HTC One X's IPS LCD. A PenTile AMOLED screen is also

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  Business continuity and disaster recovery auditing

  Given organizations' increasing dependency on information technology (IT) to run their operations, business continuity planning (and its subset IT service continuity planning) covers the entire organization, while disaster recovery focuses on IT. Auditing documents covering an organization's business continuity and disaster recovery (BCDR) plans provides a third-party validation to stakeholders that the documentation is complete and does not contain material misrepresentations. == Overview == Often used together, the terms business continuity (BC) and disaster recovery (DR) are very different. BC refers to the ability of a business to continue critical functions and business processes after the occurrence of a disaster, whereas DR refers specifically to the IT functions of the business, albeit a subset of BC. == Metrics == The primary objective is to protect the organization in the event that all or part of its operations and/or computer services are rendered partially or completely unusable. === DR metrics === Minimizing downtime and data loss during disaster recovery is typically measured in terms of two key concepts: Recovery time objective (RTO), time until a system is completely up and running Recovery point objective (RPO), a measure of the ability to recover files by specifying a point in time the backup copy will restore to. == The auditor's role == Role of the Internal Auditor in Auditing a Disaster Recovery Plan (DRP): 1. Governance & Oversight - Confirm roles, responsibilities, and oversight are defined, and DRP aligns with risk appetite and continuity strategy. 2. Risk Assessment & BIA - Verify risk and impact assessments identify critical systems and define RTO/RPO. 3. Plan Design & Documentation - Ensure the DRP is current, complete, and includes key recovery procedures. 4. Testing & Validation - Confirm regular DRP testing occurs and results are used to improve the plan. 5. Backup & Recovery - Assess backup frequency and recovery capabilities against RTO/RPO targets. 6. Communication & Training - Verify staff are trained and communication protocols are in place for crises. 7. Maintenance & Improvement - Ensure the DRP is regularly updated and lessons learned are integrated. == Documentation == === Disaster recovery plan === A disaster recovery plan (DRP) is a documented process or set of procedures to execute an organization's disaster recovery processes and recover and protect a business IT infrastructure in the event of a disaster. It is "a comprehensive statement of consistent actions to be taken before, during and after a disaster". The disaster could be natural, environmental or man-made. Man-made disasters could be intentional (for example, an act of a terrorist) or unintentional (that is, accidental, such as the breakage of a man-made dam or even "fat fingers" - or errant commands entered - on a computer system). ==== Types of plans ==== Although there is no one-size-fits-all plan, there are three basic strategies: prevention, including proper backups, having surge protectors and generators detection, a byproduct of routine inspections, which may discover new (potential) threats correction The latter may include securing proper insurance policies, and holding a "lessons learned" brainstorming session. ==== Best practices ==== To maximize their effectiveness, DRPs are most effective when updated frequently, and should: be an integral part of all business analysis processes, be revisited at every major corporate acquisition, at every new product launch and at every new system development milestone. be thoroughly tested, not just unpracticed bureaucratic documentation Adequate records need to be retained by the organization. The auditor examines records, billings, and contracts to verify that records are being kept. One such record is a current list of the organization's hardware and software vendors. Such list is made and periodically updated to reflect changing business practices and as part of an IT asset management system. Copies of it are stored on and off site and are made available or accessible to those who require them. An auditor tests the procedures used to meet this objective and determine their effectiveness. === Relationship to BCPs === Disaster recovery is a subset of business continuity. Where DRP encompasses the policies, tools and procedures to enable recovery of data following a catastrophic event, BCP involves keeping all aspects of a business functioning regardless of potential disruptive events. As such, a business continuity plan is a comprehensive organizational strategy that includes the DRP as well as threat prevention, detection, recovery, and resumption of operations should a data breach or other disaster event occur. Therefore, BCP consists of five component plans: Business resumption plan Occupant emergency plan Continuity of operations plan Incident management plan Disaster recovery plan The first three components (business resumption, occupant emergency, and continuity of operations plans) do not deal with the IT infrastructure. The incident management plan (IMP) does deal with the IT infrastructure, but since it establishes structure and procedures to address cyber attacks against an organization's IT systems, it generally does not represent an agent for activating the DRP; thus DRP is the only BCP component of active interest to IT. == Testing == The overall categorization of tests are functional- and discussion-based. Types of tests include: tabletop exercises, checklists, simulations, parallel processing (testing recovery site while primary site is in operation), and full interruption (fail over) tests. These apply to both BC and DR. == Benefits == Like every insurance plan, there are benefits that can be obtained from proper business continuity planning, including: Studies have shown a correlation between higher spending on auditing fees and lower rates of Incidents. Minimizing risk of delays Guaranteeing the reliability of standby systems (even automating the failure detection and recovery in certain scenarios) Providing a standard for testing the plan Minimizing decision-making during a disaster Reducing potential legal liabilities Lowering unnecessarily stressful work environment === Planning and testing methodology === According to Geoffrey H. Wold of the Disaster Recovery Journal, the entire process involved in developing a Disaster Recovery Plan consists of 10 steps: Performing a risk assessment: The planning committee prepares a risk analysis and a business impact analysis (BIA) that includes a range of possible disasters. Each functional area of the organization is analyzed to determine potential consequences. Traditionally, fire has posed the greatest threat. A thorough plan provides for "worst case" situations, such as destruction of the main building. Establishing priorities for processing and operations: Critical needs of each department are evaluated and prioritized. Written agreements for alternatives selected are prepared, with details specifying duration, termination conditions, system testing, cost, any special security procedures, procedure for the notification of system changes, hours of operation, the specific hardware and other equipment required for processing, personnel requirements, definition of the circumstances constituting an emergency, process to negotiate service extensions, guarantee of compatibility, availability, non-mainframe resource requirements, priorities, and other contractual issues. Collecting data: This includes various lists (employee backup position listing, critical telephone numbers list, master call list, master vendor list, notification checklist), inventories (communications equipment, documentation, office equipment, forms, insurance policies, workgroup and data center computer hardware, microcomputer hardware and software, office supply, off-site storage location equipment, telephones, etc.), distribution register, software and data files backup/retention schedules, temporary location specifications, any other such lists, materials, inventories, and documentation. Pre-formatted forms are often used to facilitate the data gathering process. Organizing and documenting a written plan Developing testing criteria and procedures: reasons for testing include Determining the feasibility and compatibility of backup facilities and procedures. Identifying areas in the plan that need modification. Providing training to the team managers and team members. Demonstrating the ability of the organization to recover. Providing motivation for maintaining and updating the disaster recovery plan. Testing the plan: An initial "dry run" of the plan is performed by conducting a structured walk-through test. An actual test-run must be performed. Problems are corrected. Initial testing can be plan is done in sections and after normal business hours to minimize disruptions. Subsequent tests occur during normal business hours. === Caveats/controversie

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  Trace zero cryptography

  First proposed by Gerhard Frey in 1998, trace zero cryptography refers to the use of trace zero varieties (TZV) for cryptographic purpose. Trace zero varieties are subgroups of the divisor class group on a low genus hyperelliptic curve defined over a finite field. These groups can be used to establish asymmetric cryptography using the discrete logarithm problem as cryptographic primitive. Trace zero varieties feature a better scalar multiplication performance than elliptic curves. This allows fast arithmetic in these groups, which can speed up the calculations with a factor 3 compared with elliptic curves and hence speed up the cryptosystem. Another advantage is that for groups of cryptographically relevant size, the order of the group can simply be calculated using the characteristic polynomial of the Frobenius endomorphism. This is not the case, for example, in elliptic curve cryptography when the group of points of an elliptic curve over a prime field is used for cryptographic purpose. However, to represent an element of the trace zero variety more bits are needed compared with elements of elliptic or hyperelliptic curves. Another disadvantage is the fact that it is possible to reduce the security of the TZV of 1/6th of the bit length using cover attack. == Mathematical background == A hyperelliptic curve C of genus g over a prime field F q {\displaystyle \mathbb {F} _{q}} where q = pn (p prime) of odd characteristic is defined as C : y 2 + h ( x ) y = f ( x ) , {\displaystyle C:~y^{2}+h(x)y=f(x),} where f monic, deg(f) = 2g + 1 and deg(h) ≤ g. The curve has at least one F q {\displaystyle \mathbb {F} _{q}} -rational Weierstraßpoint. The Jacobian variety J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} of C is for all finite extension F q n {\displaystyle \mathbb {F} _{q^{n}}} isomorphic to the ideal class group Cl ⁡ ( C / F q n ) {\displaystyle \operatorname {Cl} (C/\mathbb {F} _{q^{n}})} . With the Mumford's representation it is possible to represent the elements of J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} with a pair of polynomials [u, v], where u, v ∈ F q n [ x ] {\displaystyle \mathbb {F} _{q^{n}}[x]} . The Frobenius endomorphism σ is used on an element [u, v] of J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} to raise the power of each coefficient of that element to q: σ([u, v]) = [uq(x), vq(x)]. The characteristic polynomial of this endomorphism has the following form: χ ( T ) = T 2 g + a 1 T 2 g − 1 + ⋯ + a g T g + ⋯ + a 1 q g − 1 T + q g , {\displaystyle \chi (T)=T^{2g}+a_{1}T^{2g-1}+\cdots +a_{g}T^{g}+\cdots +a_{1}q^{g-1}T+q^{g},} where ai in Z {\displaystyle \mathbb {Z} } With the Hasse–Weil theorem it is possible to receive the group order of any extension field F q n {\displaystyle \mathbb {F} _{q^{n}}} by using the complex roots τi of χ(T): | J C ( F q n ) | = ∏ i = 1 2 g ( 1 − τ i n ) {\displaystyle |J_{C}(\mathbb {F} _{q^{n}})|=\prod _{i=1}^{2g}(1-\tau _{i}^{n})} Let D be an element of the J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} of C, then it is possible to define an endomorphism of J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} , the so-called trace of D: Tr ⁡ ( D ) = ∑ i = 0 n − 1 σ i ( D ) = D + σ ( D ) + ⋯ + σ n − 1 ( D ) {\displaystyle \operatorname {Tr} (D)=\sum _{i=0}^{n-1}\sigma ^{i}(D)=D+\sigma (D)+\cdots +\sigma ^{n-1}(D)} Based on this endomorphism one can reduce the Jacobian variety to a subgroup G with the property, that every element is of trace zero: G = { D ∈ J C ( F q n ) | Tr ( D ) = 0 } , ( 0 neutral element in J C ( F q n ) {\displaystyle G=\{D\in J_{C}(\mathbb {F} _{q^{n}})~|~{\text{Tr}}(D)={\textbf {0}}\},~~~({\textbf {0}}{\text{ neutral element in }}J_{C}(\mathbb {F} _{q^{n}})} G is the kernel of the trace endomorphism and thus G is a group, the so-called trace zero (sub)variety (TZV) of J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} . The intersection of G and J C ( F q ) {\displaystyle J_{C}(\mathbb {F} _{q})} is produced by the n-torsion elements of J C ( F q ) {\displaystyle J_{C}(\mathbb {F} _{q})} . If the greatest common divisor gcd ( n , | J C ( F q ) | ) = 1 {\displaystyle \gcd(n,|J_{C}(\mathbb {F} _{q})|)=1} the intersection is empty and one can compute the group order of G: | G | = | J C ( F q n ) | | J C ( F q ) | = ∏ i = 1 2 g ( 1 − τ i n ) ∏ i = 1 2 g ( 1 − τ i ) {\displaystyle |G|={\dfrac {|J_{C}(\mathbb {F} _{q^{n}})|}{|J_{C}(\mathbb {F} _{q})|}}={\dfrac {\prod _{i=1}^{2g}(1-\tau _{i}^{n})}{\prod _{i=1}^{2g}(1-\tau _{i})}}} The actual group used in cryptographic applications is a subgroup G0 of G of a large prime order l. This group may be G itself. There exist three different cases of cryptographical relevance for TZV: g = 1, n = 3 g = 1, n = 5 g = 2, n = 3 == Arithmetic == The arithmetic used in the TZV group G0 based on the arithmetic for the whole group J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} , But it is possible to use the Frobenius endomorphism σ to speed up the scalar multiplication. This can be archived if G0 is generated by D of order l then σ(D) = sD, for some integers s. For the given cases of TZV s can be computed as follows, where ai come from the characteristic polynomial of the Frobenius endomorphism : For g = 1, n = 3: s = q − 1 1 − a 1 mod ℓ {\displaystyle s={\dfrac {q-1}{1-a_{1}}}{\bmod {\ell }}} For g = 1, n = 5: s = q 2 − q − a 1 2 q + a 1 q + 1 q − 2 a 1 q + a 1 3 − a 1 2 + a 1 − 1 mod ℓ {\displaystyle s={\dfrac {q^{2}-q-a_{1}^{2}q+a_{1}q+1}{q-2a_{1}q+a_{1}^{3}-a_{1}^{2}+a_{1}-1}}{\bmod {\ell }}} For g = 2, n = 3: s = − q 2 − a 2 + a 1 a 1 q − a 2 + 1 mod ℓ {\displaystyle s=-{\dfrac {q^{2}-a_{2}+a_{1}}{a_{1}q-a_{2}+1}}{\bmod {\ell }}} Knowing this, it is possible to replace any scalar multiplication mD (|m| ≤ l/2) with: m 0 D + m 1 σ ( D ) + ⋯ + m n − 1 σ n − 1 ( D ) , where m i = O ( ℓ 1 / ( n − 1 ) ) = O ( q g ) {\displaystyle m_{0}D+m_{1}\sigma (D)+\cdots +m_{n-1}\sigma ^{n-1}(D),~~~~{\text{where }}m_{i}=O(\ell ^{1/(n-1)})=O(q^{g})} With this trick the multiple scalar product can be reduced to about 1/(n − 1)th of doublings necessary for calculating mD, if the implied constants are small enough. == Security == The security of cryptographic systems based on trace zero subvarieties according to the results of the papers comparable to the security of hyper-elliptic curves of low genus g' over F p ′ {\displaystyle \mathbb {F} _{p'}} , where p' ~ (n − 1)(g/g' ) for |G| ~128 bits. For the cases where n = 3, g = 2 and n = 5, g = 1 it is possible to reduce the security for at most 6 bits, where |G| ~ 2256, because one can not be sure that G is contained in a Jacobian of a curve of genus 6. The security of curves of genus 4 for similar fields are far less secure. == Cover attack on a trace zero crypto-system == The attack published in shows, that the DLP in trace zero groups of genus 2 over finite fields of characteristic diverse than 2 or 3 and a field extension of degree 3 can be transformed into a DLP in a class group of degree 0 with genus of at most 6 over the base field. In this new class group the DLP can be attacked with the index calculus methods. This leads to a reduction of the bit length 1/6th.

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  BREACH

  BREACH (a backronym: Browser Reconnaissance and Exfiltration via Adaptive Compression of Hypertext) is a security vulnerability against HTTPS when using HTTP compression. BREACH is built based on the CRIME security exploit. BREACH was announced at the August 2013 Black Hat USA conference by security researchers Angelo Prado, Neal Harris and Yoel Gluck. == Details == While the CRIME attack was presented as a general attack that could work effectively against a large number of protocols, only exploits against SPDY request compression and TLS compression were demonstrated and largely mitigated in browsers and servers. The CRIME exploits 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. BREACH is an instance of the CRIME attack against HTTP compression—the use of gzip or DEFLATE data compression algorithms via the content-encoding option within HTTP by many web browsers and servers. Given this compression oracle, the rest of the BREACH attack follows the same general lines as the CRIME exploit, by performing an initial blind brute-force search to guess a few bytes, followed by divide-and-conquer search to expand a correct guess to an arbitrarily large amount of content. == Mitigation == BREACH exploits the compression in the underlying HTTP protocol. Therefore, turning off TLS compression makes no difference to BREACH, which can still perform a chosen-plaintext attack against the HTTP payload. As a result, clients and servers are either forced to disable HTTP compression completely (thus reducing performance), or to adopt workarounds to try to foil BREACH in individual attack scenarios, such as using cross-site request forgery (CSRF) protection. Another suggested approach is to disable HTTP compression whenever the referrer header indicates a cross-site request, or when the header is not present. This approach allows effective mitigation of the attack without losing functionality, only incurring a performance penalty on affected requests. Another approach is to add padding at the TLS, HTTP header, or payload level. Around 2013–2014, there was an IETF draft proposal for a TLS extension for length-hiding padding that, in theory, could be used as a mitigation against this attack. It allows the actual length of the TLS payload to be disguised by the insertion of padding to round it up to a fixed set of lengths, or to randomize the external length, thereby decreasing the likelihood of detecting small changes in compression ratio that is the basis for the BREACH attack. However, this draft has since expired without further action. A very effective mitigation is HTB (Heal-the-BREACH) that adds random-sized padding to compressed data, providing some variance in the size of the output contents. This randomness delays BREACH from guessing the correct characters in the secret token by a factor of 500 (10-byte max) to 500,000 (100-byte max). HTB protects all websites and pages in the server with minimal CPU usage and minimal bandwidth increase.

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  Single-page application

  A single-page application (SPA) is a web application or website that interacts with the user by dynamically rewriting the current web page with new data from the web server, instead of the default method of loading entire new pages. The goal is faster transitions that make the website feel more like a native app. In a SPA, a page refresh never occurs; instead, all necessary HTML, JavaScript, and CSS code is either retrieved by the browser with a single page load, or the appropriate resources are dynamically loaded and added to the page as necessary, usually in response to user actions. == History == The origins of the term single-page application are unclear, though the concept was discussed at least as early as 2003 by technology evangelists from Netscape. Stuart Morris, a programming student at Cardiff University, Wales, wrote the self-contained website at slashdotslash.com with the same goals and functions in April 2002, and later the same year Lucas Birdeau, Kevin Hakman, Michael Peachey and Clifford Yeh described a single-page application implementation in US patent 8,136,109. Earlier forms were called rich web applications. JavaScript can be used in a web browser to display the user interface (UI), run application logic, and communicate with a web server. Mature free libraries are available that support the building of a SPA, reducing the amount of JavaScript code developers have to write. == Technical approaches == There are various techniques available that enable the browser to retain a single page even when the application requires server communication. === Document hashes === HTML authors can leverage element IDs to show or hide different sections of the HTML document. Then, using CSS, authors can use the :target pseudo-class selector to only show the section of the page which the browser navigated to. === JavaScript frameworks === Web browser JavaScript frameworks and libraries, such as Angular, Ember.js, ExtJS, Knockout.js, Meteor.js, React, Vue.js, and Svelte have adopted SPA principles. Aside from ExtJS, all of these are free. AngularJS is a discontinued fully client-side framework. AngularJS's templating is based on bidirectional UI data binding. Data-binding is an automatic way of updating the view whenever the model changes, as well as updating the model whenever the view changes. The HTML template is compiled in the browser. The compilation step creates pure HTML, which the browser re-renders into the live view. The step is repeated for subsequent page views. In traditional server-side HTML programming, concepts such as controller and model interact within a server process to produce new HTML views. In the AngularJS framework, the controller and model states are maintained within the client browser. Therefore, new pages are capable of being generated without any interaction with a server. Angular 2+ is a SPA Framework developed by Google after AngularJS. There is a strong community of developers using this framework. The framework is updated twice every year. New features and fixes are frequently added in this framework. Ember.js is a client-side JavaScript web application framework based on the model–view–controller (MVC) software architectural pattern. It allows developers to create scalable single-page applications by incorporating common idioms and best practices into a framework that provides a rich object model, declarative two-way data binding, computed properties, automatically updating templates powered by Handlebars.js, and a router for managing application state. ExtJS is also a client side framework that allows creating MVC applications. It has its own event system, window and layout management, state management (stores) and various UI components (grids, dialog windows, form elements etc.). It has its own class system with either dynamic or static loader. The application built with ExtJS can either exist on its own (with state in the browser) or with the server (e.g. with REST API that is used to fill its internal stores). ExtJS has only built in capabilities to use localStorage so larger applications need a server to store state. Knockout.js is a client side framework which uses templates based on the Model-View-ViewModel pattern. Meteor.js is a full-stack (client-server) JavaScript framework designed exclusively for SPAs. It features simpler data binding than Angular, Ember or ReactJS, and uses the Distributed Data Protocol and a publish–subscribe pattern to automatically propagate data changes to clients in real-time without requiring the developer to write any synchronization code. Full stack reactivity ensures that all layers, from the database to the templates, update themselves automatically when necessary. Ecosystem packages such as Server Side Rendering address the problem of search engine optimization. React is a JavaScript library for building user interfaces. It is maintained by Facebook, Instagram and a community of individual developers and corporations. React uses a syntax extension for JavaScript, named JSX, which is a mix of JS and HTML (a subset of HTML). Several companies use React with Redux (JavaScript library) which adds state management capabilities, which (with several other libraries) lets developers create complex applications. Vue.js is a JavaScript framework for building user interfaces. Vue developers also provide Pinia for state management. Svelte is a framework for building user interfaces that compiles Svelte code to JavaScript DOM (Document Object Model) manipulations, avoiding the need to bundle a framework to the client, and allowing for simpler application development syntax. ==== Capabilities and trade-offs in modern frameworks ==== JavaScript-based web application frameworks, such as React and Vue, provide extensive capabilities but come with associated trade-offs. These frameworks often extend or enhance features available through native web technologies, such as routing, component-based development, and state management. While native web standards, including Web Components, modern JavaScript APIs like Fetch and ES Modules, and browser capabilities like Shadow DOM, have advanced significantly, frameworks remain widely used for their ability to enhance developer productivity, offer structured patterns for large-scale applications, simplify handling edge cases, and provide tools for performance optimization. Frameworks can introduce abstraction layers that may contribute to performance overhead, larger bundle sizes, and increased complexity. Modern frameworks, such as React 18 and Vue 3, address these challenges with features like concurrent rendering, tree-shaking, and selective hydration. While these advancements improve rendering efficiency and resource management, their benefits depend on the specific application and implementation context. Lightweight frameworks, such as Svelte and Preact, take different architectural approaches, with Svelte eliminating the virtual DOM entirely in favor of compiling components to efficient JavaScript code, and Preact offering a minimal, compatible alternative to React. Framework choice depends on an application’s requirements, including the team’s expertise, performance goals, and development priorities. A newer category of web frameworks, including enhance.dev, Astro, and Fresh, leverages native web standards while minimizing abstractions and development tooling. These solutions emphasize progressive enhancement, server-side rendering, and optimizing performance. Astro renders static HTML by default while hydrating only interactive parts. Fresh focuses on server-side rendering with zero runtime overhead. Enhance.dev prioritizes progressive enhancement patterns using Web Components. While these tools reduce reliance on client-side JavaScript by shifting logic to build-time or server-side execution, they still use JavaScript where necessary for interactivity. This approach makes them particularly suitable for performance-critical and content-focused applications. === WebAssembly-based frameworks === The following frameworks utilize WebAssembly or can build single-page applications (SPAs) with WebAssembly as a core technology or support mechanism. These frameworks enable high-performance and interactive client-side development, extending the SPA paradigm across languages and ecosystems. Avalonia is primarily a cross-platform desktop UI framework, but experimental support for WebAssembly allows it to be used for SPA development. It has an XAML-based UI design and native-style application features. Blazor WebAssembly is a .NET-based framework that allows developers to build SPAs using C# and Razor syntax. It runs .NET code in the browser via WebAssembly, enabling a full-stack .NET development experience without relying on JavaScript. Flutter on the Web extends Flutter’s cross-platform development capabilities to web-based SPAs. Using Dart and its Skia graphics engine, Flutter allows developers to create visually rich SPAs that

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  Social media mining

  Social media mining is the process of obtaining data from user-generated content on social media in order to extract actionable patterns, form conclusions about users, and act upon the information. Mining supports targeting advertising to users or academic research. The term is an analogy to the process of mining for minerals. Mining companies sift through raw ore to find the valuable minerals; likewise, social media mining sifts through social media data in order to discern patterns and trends about matters such as social media usage, online behaviour, content sharing, connections between individuals, buying behaviour. These patterns and trends are of interest to companies, governments and not-for-profit organizations, as such organizations can use the analyses for tasks such as design strategies, introduce programs, products, processes or services. Social media mining uses concepts from computer science, data mining, machine learning, and statistics. Mining is based on social network analysis, network science, sociology, ethnography, optimization and mathematics. It attempts to formally represent, measure and model patterns from social media data. In the 2010s, major corporations, governments and not-for-profit organizations began mining to learn about customers, clients and others. Platforms such as Google, Facebook (partnered with Datalogix and BlueKai) conduct mining to target users with advertising. Scientists and machine learning researchers extract insights and design product features. Users may not understand how platforms use their data. Users tend to click through Terms of Use agreements without reading them, leading to ethical questions about whether platforms adequately protect users' privacy. During the 2016 United States presidential election, Facebook allowed Cambridge Analytica, a political consulting firm linked to the Trump campaign, to analyze the data of an estimated 87 million Facebook users to profile voters, creating controversy when this was revealed. == Background == As defined by Kaplan and Haenlein, social media is the "group of internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of user-generated content." There are many categories of social media including, but not limited to, social networking (Facebook or LinkedIn), microblogging (Twitter), photo sharing (Flickr, Instagram, Photobucket, or Picasa), news aggregation (Google Reader, StumbleUpon, or Feedburner), video sharing (YouTube, MetaCafe), livecasting (Ustream or Twitch), virtual worlds (Kaneva), social gaming (World of Warcraft), social search (Google, Bing, or Ask.com), and instant messaging (Google Talk, Skype, or Yahoo! messenger). The first social media website was introduced by GeoCities in 1994. It enabled users to create their own homepages without having a sophisticated knowledge of HTML coding. The first social networking site, SixDegrees.com, was introduced in 1997. Since then, many other social media sites have been introduced, each providing service to millions of people. These individuals form a virtual world in which individuals (social atoms), entities (content, sites, etc.) and interactions (between individuals, between entities, between individuals and entities) coexist. Social norms and human behavior govern this virtual world. By understanding these social norms and models of human behavior and combining them with the observations and measurements of this virtual world, one can systematically analyze and mine social media. Social media mining is the process of representing, analyzing, and extracting meaningful patterns from data in social media, resulting from social interactions. It is an interdisciplinary field encompassing techniques from computer science, data mining, machine learning, social network analysis, network science, sociology, ethnography, statistics, optimization, and mathematics. Social media mining faces grand challenges such as the big data paradox, obtaining sufficient samples, the noise removal fallacy, and evaluation dilemma. Social media mining represents the virtual world of social media in a computable way, measures it, and designs models that can help us understand its interactions. In addition, social media mining provides necessary tools to mine this world for interesting patterns, analyze information diffusion, study influence and homophily, provide effective recommendations, and analyze novel social behavior in social media. == Uses == Social media mining is used across several industries including business development, social science research, health services, and educational purposes. Once the data received goes through social media analytics, it can then be applied to these various fields. Often, companies use the patterns of connectivity that pervade social networks, such as assortativity—the social similarity between users that are induced by influence, homophily, and reciprocity and transitivity. These forces are then measured via statistical analysis of the nodes and connections between these nodes. Social analytics also uses sentiment analysis, because social media users often relay positive or negative sentiment in their posts. This provides important social information about users' emotions on specific topics. These three patterns have several uses beyond pure analysis. For example, influence can be used to determine the most influential user in a particular network. Companies would be interested in this information in order to decide who they may hire for influencer marketing. These influencers are determined by recognition, activity generation, and novelty—three requirements that can be measured through the data mined from these sites. Analysts also value measures of homophily: the tendency of two similar individuals to become friends. Users have begun to rely on information of other users' opinions in order to understand diverse subject matter. These analyses can also help create recommendations for individuals in a tailored capacity. By measuring influence and homophily, online and offline companies are able to suggest specific products for individuals consumers, and groups of consumers. Social media networks can use this information themselves to suggest to their users possible friends to add, pages to follow, and accounts to interact with. == Perception == Modern social media mining is a controversial practice that has led to exponential gains in user growth for tech giants such as Facebook, Inc., Twitter, and Google. Companies such as these, considered "Big Tech" are companies that build algorithms that take advantage of user input to understand their preferences, and keep them on the platform as much as possible. These inputs, that can be as simple as time spent on a given screen, provide the data being mined, and lead to companies profiting heavily from using that data to capitalize on extremely accurate predictions about user behavior. The growth of platforms accelerated rapidly once these strategies were put in place; Most of the largest platforms now average over 1 billion active users per month as of 2021. It has been claimed by a multitude of anti-algorithm personalities, like Tristan Harris or Chamath Palihapitiya, that certain companies (specifically Facebook) valued growth above all else, and ignored potential negative impacts from these growth engineering tactics. At the same time, users have now created their own data arbitrages with the help of their own data, through content monetization and becoming influencers. Users typically have access to a varied set of analytics specific to people that interact with them on social media, and can use these as building blocks for their own targeting and growth strategies through ads and posts that cater to their audiences. Influencers also commonly promote products and services for established brands, creating one of the largest digital industries: Influencer marketing. Instagram, Facebook, Twitter, YouTube, Google, and others have long given access to platform analytics, and allowed third parties to access that information as well, at times unbeknownst to even the user whose data is being viewed/bought. == Research == === Research areas === Social media event detection – Social networks enable users to freely communicate with each other and share their recent news, ongoing activities or views about different topics. As a result, they can be seen as a potentially viable source of information to understand the current emerging topics/events. Public health monitoring and surveillance - Using large-scale analysis of social media to study large cohorts of patients and the general public, e.g. to obtain early warning signals of drug-drug interactions and adverse drug reactions, or understand human reproduction and sexual interest. Community structure (Community Detection/Evolution/Evaluation) – Identifying communities on social networks, how t

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  Cut, copy, and paste

  Cut, copy, and paste are essential commands of modern human–computer interaction and user interface design. They offer an interprocess communication technique for transferring data through a computer's user interface. The cut command removes the selected data from its original position, and the copy command creates a duplicate; in both cases the selected data is kept in temporary storage called the clipboard. Clipboard data is later inserted wherever a paste command is issued. The data remains available to any application supporting the feature, thus allowing easy data transfer between applications. The command names are a (skeuomorphic) interface metaphor based on the physical procedure used in manuscript print editing to create a page layout, like with paper. The commands were pioneered into computing by Xerox PARC in 1974, popularized by Apple Computer in the 1983 Lisa workstation and the 1984 Macintosh computer, and in a few home computer applications such as the 1984 word processor Cut & Paste. This interaction technique has close associations with related techniques in graphical user interfaces (GUIs) that use pointing devices such as a computer mouse (by drag and drop, for example). Typically, clipboard support is provided by an operating system as part of its GUI and widget toolkit. The capability to replicate information with ease, changing it between contexts and applications, involves privacy concerns because of the risks of disclosure when handling sensitive information. Terms like cloning, copy forward, carry forward, or re-use refer to the dissemination of such information through documents, and may be subject to regulation by administrative bodies. == History == === Origins === The term "cut and paste" comes from the traditional practice in manuscript editing, whereby people cut paragraphs from a page with scissors and paste them onto another page. This practice remained standard into the 1980s. Stationery stores sold "editing scissors" with blades long enough to cut an 8½"-wide page. The advent of photocopiers made the practice easier and more flexible. The act of copying or transferring text from one part of a computer-based document ("buffer") to a different location within the same or different computer-based document was a part of the earliest on-line computer editors. As soon as computer data entry moved from punch-cards to online files (in the mid/late 1960s) there were "commands" for accomplishing this operation. This mechanism was often used to transfer frequently-used commands or text snippets from additional buffers into the document, as was the case with the QED text editor. === Early methods === The earliest editors (designed for teleprinter terminals) provided keyboard commands to delineate a contiguous region of text, then delete or move it. Since moving a region of text requires first removing it from its initial location and then inserting it into its new location, various schemes had to be invented to allow for this multi-step process to be specified by the user. Often this was done with a "move" command, but some text editors required that the text be first put into some temporary location for later retrieval/placement. In 1983, the Apple Lisa became the first text editing system to call that temporary location "the clipboard". Earlier control schemes such as NLS used a verb—object command structure, where the command name was provided first and the object to be copied or moved was second. The inversion from verb—object to object—verb on which copy and paste are based, where the user selects the object to be operated before initiating the operation, was an innovation crucial for the success of the desktop metaphor as it allowed copy and move operations based on direct manipulation. === Popularization === Inspired by early line and character editors, such as Pentti Kanerva's TV-Edit, that broke a move or copy operation into two steps—between which the user could invoke a preparatory action such as navigation—Lawrence G. "Larry" Tesler proposed the names "cut" and "copy" for the first step and "paste" for the second step. Beginning in 1974, he and colleagues at Xerox PARC implemented several text editors that used cut/copy-and-paste commands to move and copy text. Apple Computer popularized this paradigm with its Lisa (1983) and Macintosh (1984) operating systems and applications. The functions were mapped to key combinations using the ⌘ Command key as a special modifier, which is held down while also pressing X for cut, C for copy, or V for paste. These few keyboard shortcuts allow the user to perform all the basic editing operations, and the keys are clustered at the left end of the bottom row of the standard QWERTY keyboard. These are the standard shortcuts: Control-Z (or ⌘ Command+Z) to undo Control-X (or ⌘ Command+X) to cut Control-C (or ⌘ Command+C) to copy Control-V (or ⌘ Command+V) to paste The IBM Common User Access (CUA) standard also uses combinations of the Insert, Del, Shift and Control keys. Early versions of Windows used the IBM standard. Microsoft later also adopted the Apple key combinations with the introduction of Windows, using the control key as modifier key. Similar patterns of key combinations, later borrowed by others, are widely available in most GUI applications. The original cut, copy, and paste workflow, as implemented at PARC, utilizes a unique workflow: With two windows on the same screen, the user could use the mouse to pick a point at which to make an insertion in one window (or a segment of text to replace). Then, by holding shift and selecting the copy source elsewhere on the same screen, the copy would be made as soon as the shift was released. Similarly, holding shift and control would copy and cut (delete) the source. This workflow requires many fewer keystrokes/mouse clicks than the current multi-step workflows, and did not require an explicit copy buffer. It was dropped, one presumes, because the original Apple and IBM GUIs were not high enough density to permit multiple windows, as were the PARC machines, and so multiple simultaneous windows were rarely used. == Cut and paste == Computer-based editing can involve very frequent use of cut-and-paste operations. Most software-suppliers provide several methods for performing such tasks, and this can involve (for example) key combinations, pulldown menus, pop-up menus, or toolbar buttons. The user selects or "highlights" the text or file for moving by some method, typically by dragging over the text or file name with the pointing-device or holding down the Shift key while using the arrow keys to move the text cursor. The user performs a "cut" operation via key combination Ctrl+x (⌘+x for Macintosh users), menu, or other means. Visibly, "cut" text immediately disappears from its location. "Cut" files typically change color to indicate that they will be moved. Conceptually, the text has now moved to a location often called the clipboard. The clipboard typically remains invisible. On most systems only one clipboard location exists, hence another cut or copy operation overwrites the previously stored information. Many UNIX text-editors provide multiple clipboard entries, as do some Macintosh programs such as Clipboard Master, and Windows clipboard-manager programs such as the one in Microsoft Office. The user selects a location for insertion by some method, typically by clicking at the desired insertion point. A paste operation takes place which visibly inserts the clipboard text at the insertion point. (The paste operation does not typically destroy the clipboard text: it remains available in the clipboard and the user can insert additional copies at other points). Whereas cut-and-paste often takes place with a mouse-equivalent in Windows-like GUI environments, it may also occur entirely from the keyboard, especially in UNIX text editors, such as Pico or vi. Cutting and pasting without a mouse can involve a selection (for which Ctrl+x is pressed in most graphical systems) or the entire current line, but it may also involve text after the cursor until the end of the line and other more sophisticated operations. The clipboard usually stays invisible, because the operations of cutting and pasting, while actually independent, usually take place in quick succession, and the user (usually) needs no assistance in understanding the operation or maintaining mental context. Some application programs provide a means of viewing, or sometimes even editing, the data on the clipboard. == Copy and paste == The term "copy-and-paste" refers to the popular, simple method of reproducing text or other data from a source to a destination. It differs from cut and paste in that the original source text or data does not get deleted or removed. The popularity of this method stems from its simplicity and the ease with which users can move data between various applications visually – without resorting to permanent storage. Use in healthcare do

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  Data grid

  A data grid is an architecture or set of services that allows users to access, modify and transfer extremely large amounts of geographically distributed data for research purposes. Data grids make this possible through a host of middleware applications and services that pull together data and resources from multiple administrative domains and then present it to users upon request. The data in a data grid can be located at a single site or multiple sites where each site can be its own administrative domain governed by a set of security restrictions as to who may access the data. Likewise, multiple replicas of the data may be distributed throughout the grid outside their original administrative domain and the security restrictions placed on the original data for who may access it must be equally applied to the replicas. Specifically developed data grid middleware is what handles the integration between users and the data they request by controlling access while making it available as efficiently as possible. == Middleware == Middleware provides all the services and applications necessary for efficient management of datasets and files within the data grid while providing users quick access to the datasets and files. There is a number of concepts and tools that must be available to make a data grid operationally viable. However, at the same time not all data grids require the same capabilities and services because of differences in access requirements, security and location of resources in comparison to users. In any case, most data grids will have similar middleware services that provide for a universal name space, data transport service, data access service, data replication and resource management service. When taken together, they are key to the data grids functional capabilities. === Universal namespace === Since sources of data within the data grid will consist of data from multiple separate systems and networks using different file naming conventions, it would be difficult for a user to locate data within the data grid and know they retrieved what they needed based solely on existing physical file names (PFNs). A universal or unified name space makes it possible to create logical file names (LFNs) that can be referenced within the data grid that map to PFNs. When an LFN is requested or queried, all matching PFNs are returned to include possible replicas of the requested data. The end user can then choose from the returned results the most appropriate replica to use. This service is usually provided as part of a management system known as a Storage Resource Broker (SRB). Information about the locations of files and mappings between the LFNs and PFNs may be stored in a metadata or replica catalogue. The replica catalogue would contain information about LFNs that map to multiple replica PFNs. === Data transport service === Another middleware service is that of providing for data transport or data transfer. Data transport will encompass multiple functions that are not just limited to the transfer of bits, to include such items as fault tolerance and data access. Fault tolerance can be achieved in a data grid by providing mechanisms that ensures data transfer will resume after each interruption until all requested data is received. There are multiple possible methods that might be used to include starting the entire transmission over from the beginning of the data to resuming from where the transfer was interrupted. As an example, GridFTP provides for fault tolerance by sending data from the last acknowledged byte without starting the entire transfer from the beginning. The data transport service also provides for the low-level access and connections between hosts for file transfer. The data transport service may use any number of modes to implement the transfer to include parallel data transfer where two or more data streams are used over the same channel or striped data transfer where two or more steams access different blocks of the file for simultaneous transfer to also using the underlying built-in capabilities of the network hardware or specifically developed protocols to support faster transfer speeds. The data transport service might optionally include a network overlay function to facilitate the routing and transfer of data as well as file I/O functions that allow users to see remote files as if they were local to their system. The data transport service hides the complexity of access and transfer between the different systems to the user so it appears as one unified data source. === Data access service === Data access services work hand in hand with the data transfer service to provide security, access controls and management of any data transfers within the data grid. Security services provide mechanisms for authentication of users to ensure they are properly identified. Common forms of security for authentication can include the use of passwords or Kerberos (protocol). Authorization services are the mechanisms that control what the user is able to access after being identified through authentication. Common forms of authorization mechanisms can be as simple as file permissions. However, need for more stringent controlled access to data is done using Access Control Lists (ACLs), Role-Based Access Control (RBAC) and Tasked-Based Authorization Controls (TBAC). These types of controls can be used to provide granular access to files to include limits on access times, duration of access to granular controls that determine which files can be read or written to. The final data access service that might be present to protect the confidentiality of the data transport is encryption. The most common form of encryption for this task has been the use of SSL while in transport. While all of these access services operate within the data grid, access services within the various administrative domains that host the datasets will still stay in place to enforce access rules. The data grid access services must be in step with the administrative domains access services for this to work. === Data replication service === To meet the needs for scalability, fast access and user collaboration, most data grids support replication of datasets to points within the distributed storage architecture. The use of replicas allows multiple users faster access to datasets and the preservation of bandwidth since replicas can often be placed strategically close to or within sites where users need them. However, replication of datasets and creation of replicas is bound by the availability of storage within sites and bandwidth between sites. The replication and creation of replica datasets is controlled by a replica management system. The replica management system determines user needs for replicas based on input requests and creates them based on availability of storage and bandwidth. All replicas are then cataloged or added to a directory based on the data grid as to their location for query by users. In order to perform the tasks undertaken by the replica management system, it needs to be able to manage the underlying storage infrastructure. The data management system will also ensure the timely updates of changes to replicas are propagated to all nodes. ==== Replication update strategy ==== There are a number of ways the replication management system can handle the updates of replicas. The updates may be designed around a centralized model where a single master replica updates all others, or a decentralized model, where all peers update each other. The topology of node placement may also influence the updates of replicas. If a hierarchy topology is used then updates would flow in a tree like structure through specific paths. In a flat topology it is entirely a matter of the peer relationships between nodes as to how updates take place. In a hybrid topology consisting of both flat and hierarchy topologies updates may take place through specific paths and between peers. ==== Replication placement strategy ==== There are a number of ways the replication management system can handle the creation and placement of replicas to best serve the user community. If the storage architecture supports replica placement with sufficient site storage, then it becomes a matter of the needs of the users who access the datasets and a strategy for placement of replicas. There have been numerous strategies proposed and tested on how to best manage replica placement of datasets within the data grid to meet user requirements. There is not one universal strategy that fits every requirement the best. It is a matter of the type of data grid and user community requirements for access that will determine the best strategy to use. Replicas can even be created where the files are encrypted for confidentiality that would be useful in a research project dealing with medical files. The following section contains several strategies for replica placement. ===== Dynamic replication ===== Dynam

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  Web development tools

  Web development tools (often abbreviated to dev tools) allow web developers to test, modify and debug their websites. They are different from website builders and integrated development environments (IDEs) in that they do not assist in the direct creation of a webpage, rather they are tools used for testing the user interface of a website or web application. Web development tools come as browser add-ons or built-in features in modern web browsers. Browsers such as Google Chrome, Firefox, Safari, Microsoft Edge, and Opera have built-in tools to help web developers, and many additional add-ons can be found in their respective plugin download centers. Web development tools allow developers to work with a variety of web technologies, including HTML, CSS, the DOM, JavaScript, and other components that are handled by the web browser. == History and support == Early web developers manually debugged their websites by commenting out code and using JavaScript functions. One of the first browser debugging tools to exist was Mozilla's Firebug extension, which possessed many of the current core features of today's developer tools, leading to Firefox becoming popular with developers at the time. Safari's WebKit engine also introduced its integrated developer tools around that period, which eventually became the basis for both Safari and Chrome's current tooling. Microsoft released a developer toolbar for Internet Explorer 6 and 7; and then integrated them into the browser from version 8 onwards. In 2017, Mozilla discontinued Firebug in favour of integrated developer tools. Nowadays, all modern web browsers have support for web developer tools that allow web designers and developers to look at the make-up of their pages. These are all tools that are built into the browser and do not require additional modules or configuration. Firefox – F12 opens the Firefox DevTools. Google Chrome and Opera – Developer Tools (DevTools) Microsoft Edge – F12 opens Web Developer Tools. Microsoft incorporates additional features that are not included in mainline Chromium. Safari – The Safari Web Inspector has to be enabled from its settings pane. == Features == The built-in web developer tools in the browser are commonly accessed by hovering over an item on a webpage and selecting the "Inspect Element" or similar option from the context menu. Alternatively the F12 key tends to be another common shortcut. === HTML and the DOM === HTML and DOM viewer and editor is commonly included in the built-in web development tools. The difference between the HTML and DOM viewer, and the view source feature in web browsers is that the HTML and DOM viewer allows you to see the DOM as it was rendered in addition to allowing you to make changes to the HTML and DOM and see the change reflected in the page after the change is made. In addition to selecting and editing, the HTML elements panels will usually also display properties of the DOM object, such as display dimension, and CSS properties. Firefox, Safari, Chrome, and Edge all allow users to simulate the document on a mobile device by modifying the viewport dimensions and pixel density. Additionally, Firefox and Chrome both have the option to simulate colour blindness for the page. === Web page assets, resources and network information === Web pages typically load and require additional content in the form of images, scripts, font and other external files. Web development tools also allow developers to inspect resources that are loaded and available on the web page in a tree-structure listing, and the appearance of style sheets can be tested in real time. Web development tools also allow developers to view information about the network usage, such as viewing what the loading time and bandwidth usage are and which HTTP headers are being sent and received. Developers can manipulate and resend network requests. === Profiling and auditing === Profiling allows developers to capture information about the performance of a web page or web application. With this information developers can improve the performance of their scripts. Auditing features may provide developers suggestions, after analyzing a page, for optimizations to decrease page load time and increase responsiveness. Web development tools typically also provide a record of the time it takes to render the page, memory usage, and the types of events which are taking place. These features allow developers to optimize their web page or web application. ==== JavaScript debugging ==== JavaScript is commonly used in web browsers. Web development tools commonly include a debugger panel for scripts by allowing developers to add watch expressions, breakpoints, view the call stack, and pause, continue, and step while debugging JavaScript. A console is also often included, which allow developers to type in JavaScript commands and call functions, or view errors that may have been encountered during the execution of a script. === Extensions === The devtools API allows browser extensions to add their own features to developer tools.

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  Cleo Communications

  Cleo Communications LLC, simply referred to as Cleo, is a privately held software company founded in 1976. The company is best known for its ecosystem integration platform, Cleo Integration Cloud with RADAR. == History == Cleo originally began as a division of Phone 1 Inc., a voice data gathering systems manufacturer, and built data concentrators and terminal emulators — multi-bus computers, modems, and terminals to interface with IBM mainframes via bisynchronous communications. The company then began developing mainframe middleware in the 1980s, and with the rise of the PC, moved into B2B data communications and secure file transfer software. Cleo Communications was acquired in 2012 by Global Equity Partners along with other investment companies. Since being acquired in 2012, the company’s offerings have evolved into Cleo Integration Cloud, a platform for enterprise business integration. == Business == Based in Rockford, Illinois (USA), with offices in Chicago, Pennsylvania, London, and Bangalore, Cleo has about 400 employees and more than 4,100 direct customers. The company's flagship offering, Cleo Integration Cloud, provides both on-premise and cloud-based integration technologies and comprises solutions for B2B/EDI, application integration, data movement and data transformation. Previous products now incorporated into the Cleo Integration Cloud platform include Cleo Harmony, Cleo Clarify, and Cleo Jetsonic. Cleo solutions span a variety of industries, including manufacturing, logistics and supply chain, retail, third-party logistics, warehouse management and transportation management, healthcare, financial services and government. The U.S. Department of Veterans Affairs adopted Cleo's fax technology, Cleo Streem, in 2013 when in need of FIPS 140-2-compliant technology to protect information, and the City of Atlanta has used Cleo Streem for network and desktop faxing since 2006. Cleo also serves U.S. transportation logistics company MercuryGate International and SaaS-based food logistics organization ArrowStream. It powers the architecture for several major supply chain companies, such as Blue Yonder and SAP. Cleo integrates the pharmaceutical supply chain for such companies as Octapharma. Key partners include FourKites and ClientsFirst, among many others. In May 2023, Cleo announced it entered a global partnership with consulting and multinational information technology services company, Cognizant (NASDAQ: CTSH). Together, the companies announced CCIB, powered by Cleo, which is a B2B iPaaS solution that provides B2B managed services with built-in, scalable infrastructure on the cloud. The solution comprises elements from Cleo’s flagship offering, Cleo Integration Cloud. == Expansion == In June 2014, Cleo opened an office in Chicago for members of its support and Ashok and teams. In 2014, the company hired Jorge Rodriguez as Senior Vice President of Product Development and John Thielens as Vice President of Technology. Cleo hired Dave Brunswick as Vice President of Solutions for North America in 2015, and Cleo hired Ken Lyons to lead global sales in 2016. Lyons now serves as the company's Chief Revenue Officer. More recent additions to the company's leadership team include Vipin Mittal, Vice President, Customer Experience, and Tushar Patel, CMO. Cleo opened its product development facility in Bengaluru, India, in 2015 and expanded its hybrid cloud integration teams into a new office there in 2017. The company also opened a London office in 2016 and expanded its network of channel partners in EMEA. In 2016, Cleo acquired EXTOL International, a Pottsville, Pa.-based business and EDI integration and data transformation company for an undisclosed amount. In 2017, the company moved its headquarters from Loves Park, Illinois, to Rockford. In 2021 the company received a significant growth investment from H.I.G. Capital. In July 2022, Cleo opened a new, 5,000-square-foot office located in Chicago's Loop. In November 2022, Cleo launched an accelerator for Microsoft Dynamics 365 SCM-to-X12 and a connector for Microsoft Dynamics 365 Business Central. These pre-built solutions allow businesses and users to quickly build integration flows that integrate their digital ecosystems. In March 2023, Cleo released CIC PAVE (Procurement Automation and Vendor Enablement). PAVE provides customers with enhanced supply chain visibility via a supplier portal that allows the customer to keep vendor interaction in a single location, even if they cannot use EDI or have API-ready applications. In December 2023, Cleo acquired ECS International, an integration technology company based in the Netherlands. == Certification == Cleo regularly submits its products to Drummond Group's interoperability software testing for AS2, AS3 and ebMS 2.0. In January 2020, Cleo announced that its new application connector for Acumatica ERP has been recognized as an Acumatica-Certified Application (ACA). The company also holds SOC 2, Type 2 certification. == Awards == Cleo was a Xerox partner of the year award for five years, from 2009 to 2014. The Cleo Streem solution integrates with Xerox multi-function products, providing customers with solutions for network fax and interactive messaging needs. Cleo was named to Food Logistics’ FL100+ Top Software and Technology Providers Lists in 2016, 2017, 2019 and 2020. Cleo CEO, Mahesh Rajasekharan was named an Ernst & Young Entrepreneur Of The Year 2022 Midwest Award winner. Rajasekharan is serving as a judge for the 2023 Ernst & Young Entrepreneur Of the Year Awards. As of April 2022, Cleo has been named a Leader in EDI on the G2 Grid, a peer-to-peer review site, for 20 straight quarters. In Spring 2023, Cleo won 23 G2 awards—including EDI Leader Enterprise, MFT Leader Enterprise, On-Premise Data Integration Best Support Enterprise, and iPaaS High Performer Asia.

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  Harvest now, decrypt later

  Harvest now, decrypt later (HNDL) is a surveillance strategy that relies on the acquisition and long-term storage of currently unreadable encrypted data awaiting possible breakthroughs in decryption technology that would render it readable in the future—a hypothetical date referred to as Y2Q (a reference to Y2K), or Q-Day. The most common concern is the prospect of developments in quantum computing which would allow current strong encryption algorithms to be broken at some time in the future, making it possible to decrypt any stored material that had been encrypted using those algorithms. However, the improvement in decryption technology need not be due to a quantum-cryptographic advance; any other form of attack capable of enabling decryption would be sufficient. The existence of this strategy has led to concerns about the need to urgently deploy post-quantum cryptography; even though no practical quantum attacks yet exist, some data stored now may still remain sensitive even decades into the future. As of 2022, the U.S. federal government has proposed a roadmap for organizations to start migrating toward quantum-cryptography-resistant algorithms to mitigate these threats. This new version of Commercial National Security Algorithm Suite uses publicly-available algorithms and is allowed for government use up to the TOP SECRET level. == Terminology and scope == The term “harvest now, decrypt later” encompasses various surveillance or espionage operations in which ciphertext or encrypted communications are collected today with the view that they may one day be decrypted, given sufficient advances in computing power or cryptanalysis. The abbreviation HNDL is sometimes used in technical and policy documents. The “Y2Q” (or “Q-Day”) label draws an analogy to the Y2K date-change issue, emphasising a potential future point at which current cryptography may collapse. The strategy is particularly relevant for data with long confidentiality lifetimes, such as diplomatic communications, personal health records, critical infrastructure logs, or intellectual property. == Mitigation strategies == The primary defense against HNDL attacks is the transition to post-quantum cryptography (PQC), which utilizes algorithms believed to be secure against quantum computer attacks. However, because PQC protects the data payload digitally, rather than the transmission itself, the encrypted data can still be harvested and stored. A complementary approach involves physical layer security (also known as optical layer encryption or photonic shielding). Unlike algorithmic encryption, this method modifies the optical waveform itself—often by burying the signal within optical noise or using spectral phase encoding—to render the transmission unrecordable by standard receivers. By preventing the attacker from capturing a valid signal in the first place, this approach aims to eliminate the "harvest" phase of the threat. Commercial implementations of harvest-proof optical encryption have been developed by firms such as CyberRidge to secure long-haul fiber networks. Field trials have demonstrated 100 Gbps throughput over legacy DWDM networks using this method.

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  European Grid Infrastructure

  EGI (originally an initialism for European Grid Infrastructure) is a federation of computing and storage resource providers that deliver advanced computing and data analytics services for research and innovation. The Federation is governed by its participants represented in the EGI Council and coordinated by the EGI Foundation. As of 2024, the EGI Federation supports 160 scientific communities worldwide and over 95,000 users in their intensive data analysis. The most significant scientific communities supported by EGI in 2022 were Medical and Health Sciences, High Energy Physics, and Engineering and Technology. The EGI Federation provideds services through over 150 data centres, of which 25 are cloud sites, in 43 countries and 64 Research Infrastructures (4 of which are members of the Federation). == Name == Originally, EGI stood for European Grid Infrastructure. This reflected its focus on providing access to high-throughput computing resources across Europe using Grid computing techniques. However, as EGI's service offerings expanded beyond traditional grid computing, particularly with the incorporation of federated cloud services, the original meaning of the acronym became less accurate. To emphasise the broader scope of EGI's services and avoid any confusion associated with the outdated term "grid," it is recommended to refer to EGI simply as EGI. == Structure == === EGI Federation === The EGI Federation delivers a scalable digital research infrastructure (e-infrastructure), empowering tens of thousands of researchers across diverse scientific disciplines. Through the EGI Federation, researchers gain access to advanced computing and data analytics capabilities, including large-scale data analysis, while benefiting from the collaborative efforts of hundreds of service providers from both public and private sectors, consolidating resources from Europe and beyond. Overall, the EGI Federation offers a range of services, encompassing distributed high-throughput computing and cloud computing, storage and data management capabilities, co-development of new solutions, expert support, and comprehensive training opportunities. This ecosystem propels collaboration, scientific progress and innovation. === EGI Foundation === The EGI Foundation is the coordinating body of the EGI Federation. It was established in 2010 with headquarters in Amsterdam, Netherlands. The Foundation coordinates the research and innovation efforts of its members, spanning technical areas critical to data-intensive science, including large-scale data processing and analysis, distributed Artificial Intelligence/Machine Learning, federated Identity and access management and the application of digital twins for research. The day-to-day running of the EGI Foundation is supervised by the Executive Board. The board’s members work closely with the EGI Director on operational, technical and financial issues. The Executive Board’s members are appointed by the EGI Council for a two-year term. === EGI Council === The EGI Council is responsible for defining the strategic direction of the EGI Federation. The Council acts as the senior decision-making and supervisory authority of the EGI Foundation, with a mandate to define the strategic direction of the entire EGI ecosystem. === EGI Services === EGI offers a suite of services to support data-intensive research. These services include compute resources, orchestration tools, storage and data management solutions, training programmes, security and identity services, and applications. Compute resources encompass cloud compute, cloud container compute, high-throughput compute, and software distribution. Orchestration tools include the Workload Manager and infrastructure manager. Storage and data management solutions include online storage, data transfer, and DataHub. Training programmes cover FitSM, ISO 27001, and general training infrastructure. EGI Check-in and Secrets Store are key security and identity services, while applications such as Notebooks and Replay enhance research productivity. In addition to services for Research, EGI also provides services for Federation and Business. Services for Federation are designed to help resource providers and user communities collaborate and share resources. EGI also offers a range of services to support businesses in their digital transformation. Through the EGI Digital Innovation Hub (EGI DIH), companies can access advanced computing resources, networking, funding and training opportunities, collaborate with research institutions, and test solutions before investing. == History == In 2002, the first large-scale experimental facility was successfully demonstrated by the DataGrid project under the lead of CERN with tens of technical architects from the major High Energy Physics institutes in the world. For the first time, distributed computing was applied to data-intensive processing. It aimed at developing a large-scale computational grid to facilitate distributed data-intensive scientific computing across High Energy Physics, Earth Observation, and Biology science applications. On 28 February 2003, the first software release of LCG-MW was published. gLite, the Lightweight Middleware for Grid Computing and LCG, Large Hadron Collider Computing Grid, are the cornerstone of the Worldwide LHC Computing Grid, which expanded over time towards the EGI Federation. 2004 marks the year of the first pilot infrastructure, seeing the participation of CERN and data centres in the United Kingdom, Spain, Germany, the Netherlands, France, Canada, Russia, Bulgaria, the Asia-Pacific region and Switzerland. Over the years, the infrastructure has grown into a federation of 128 data centres and 25 cloud providers serving more than 95,000 users worldwide. In 2004, the first data processing tasks started being formally recorded in a central accounting system. The EGI Accounting Portal provides the accounting data for Compute, Storage and Data services gathered from the data centres of the EGI Federation. A few years later, in 2010, EGI was established as the coordinating body of the EGI Federation to build an integrated pan-European infrastructure to support European research communities primarily. In the same year, EGI launched the flagship project EGI Inspire. That project brought together European organisations to establish a sustainable European Grid Infrastructure for large-scale data analysis. The success of the project was due to the adoption of a distributed computing model to solve big data problems. Moreover, EGI-Inspire harmonised operational policies across its federation of affiliated data centres and cloud service providers worldwide, integrating e-infrastructures from 57 countries. The EGI Federation was the first to apply federation to cloud provisioning, opening a new avenue in large-scale interactive data analysis. In 2015, within EGI Engage, opening a new avenue in large-scale interactive data analysis. The EGI Federated Cloud is an IaaS-type cloud, incorporating academic and private clouds and virtualised resources built using open standards. Its development is driven by the needs of the scientific community, resulting in a novel research e-infrastructure that relies on well-established federated operational services, making EGI a dependable resource for scientific endeavours. In 2015, EGI, EUDAT, GÉANT, LIBER and OpenAIRE published a position paper on a 'European Open Science Cloud for Research'. With the EOSC-hub project in 2016, EGI started contributing in practice to shaping the services for the EOSC. The work continued with a series of projects, like EOSC Enhance, EOSC Life and EOSC Synergy. With EGI-ACE and its contribution to EOSC Future, EGI has continued developing the EOSC Core. In early 2024, EGI started providing services to the EOSC EU Node, and with EOSC Beyond it will provide new EOSC Core capabilities and pilot additional national and thematic nodes. In October 2024, EUDAT, GÉANT, OpenAIRE, PRACE and EGI signed a Memorandum of Understanding establishing the European e-Infrastructures Assembly. This collaboration will bolster the position and promote the services of e-Infrastructures, empowering researchers across Europe to drive innovation and advance scientific discovery.

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  SurveyLab

  SurveyLab is an online system designed for creating and deploying surveys, questionnaires, web forms, tests, and quizzes. The platform functions as a web application, without the need for additional software installation. Founded in 2006, by the Polish company 7 Points, SurveyLab is used by businesses and professional users for market research, human resources assessments, customer feedback, and academic research. == History == SurveyLab was launched in 2006 under the name MySurveyLab, developed by the Warsaw-based company 7 Points. Early media coverage described the system as supporting online survey creation, real-time reporting, group collaboration and question logic, and noted that the platform was opened to custom feature development. MySurveyLab featured multi-user accounts, SSL-secured surveys, and support for right-to-left languages. Further 2010s updates improved reporting capabilities, expanded question types, and integration options. In 2020, the platform was rebranded to SurveyLab. By the early 2020s, the software supported integrations with external tools including Zapier, and offered additional analytics features. In 2025, 7 Points reported that SurveyLab had over 85,000 registered users and had processed over 7 million surveys. == Functionalities == SurveyLab is a web-based platform used for creating online surveys, questionnaires, and forms. Independent reviewers and software directories describe it as a tool used for market research, customer feedback management, and human resources-related assessments, including employee feedback surveys. According to the creators at 7 Points, SurveyLab supports customer satisfaction measurement, survey analysis, and 360-degree feedback evaluations. The platform allows users to create surveys with no limits on the number of questions or responses. Independent reviews describe SurveyLab as offering multiple-choice, matrix, rating-scale, and open-ended questions. According to 7 Points, the platform manages market-research workflows, including Net Promoter Score, Customer Satisfaction, and Customer Effort Score questions. The tool can also re-use previous answers in later questions, and create A/B survey variants. SurveyLab can integrate with external services and applications through APIs and third-party connectors. According to its developers, the platform can connect with customer service tools, as well as CRM, marketing automation, e-commerce, and data-storage tools An industry review cited workflow integrations with CINT, Slack, Salesforce, and Zendesk Other integrations included Aquera (SSO), Sona Systems (internet research), and Synerise (customer data management). == Data collection and aggregation == Independent descriptions note that SurveyLab can combine results from emails, SMS, website widgets and pop-ups, QR codes, and social media. Its surveys are also accessible through mobile apps on iOS and Android, used for online and offline data collection in the field. Developers state that the tool supports exporting data as CSV, Excel, and SPSS, with independent reviews also mentioning PDF and PowerPoint. SurveyLab can automate response collection through a multi-channel survey distribution and reporting. It includes data trends, offline responses, and reminders to non-respondents. According to its documentation, newer versions include AI-based tools that detect and analyze sentiment, and a survey builder generating questionnaires based on user prompts. === Data security and compliance === According to 7 Points, SurveyLab provides password-protected surveys, token-based access, IP-address filtering, and two-factor authentication for user accounts, and it complies with the General Data Protection Regulation. == Awards and accolades == In 2017, SurveyLab was listed in Capterra’s Top 20 Survey Software ranking, among 20 highest-scoring survey tools based on market presence and user base. In 2018, a software review platform FinancesOnline awarded SurveyLab the Rising Star Award and the Great User Experience Award, distinctions given to products that demonstrate positive user satisfaction and strong usability characteristics.

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  WYSIWYS

  In cryptography, What You See Is What You Sign (WYSIWYS) is a property of digital signature systems that ensures the semantic content of signed messages can not be changed, either by accident or intent. == Mechanism of WYSIWYS == When digitally signing a document, the integrity of the signature relies not just on the soundness of the digital signature algorithms that are used, but also on the security of the computing platform used to sign the document. The WYSIWYS property of digital signature systems aims to tackle this problem by defining a desirable property that the visual representation of a digital document should be consistent across computing systems, particularly at the points of digital signature and digital signature verification. It is relatively easy to change the interpretation of a digital document by implementing changes on the computer system where the document is being processed, and the greater the semantic distance, the easier it gets. From a semantic perspective this creates uncertainty about what exactly has been signed. WYSIWYS is a property of a digital signature system that ensures that the semantic interpretation of a digitally signed message cannot be changed, either by accident or by intent. This property also ensures that a digital document to be signed can not contain hidden semantic content that can be revealed after the signature has been applied. Though a WYSIWYS implementation is only as secure as the computing platform it is running on, various methods have been proposed to make WYSIWYS more robust. The term WYSIWYS was coined by Peter Landrock and Torben Pedersen to describe some of the principles in delivering secure and legally binding digital signatures for Pan-European projects.

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  Serge Belamant

  Serge Belamant (born 1953) is a French-born South African entrepreneur best known for designing the Universal Electronic Payment System (UEPS) and the Chip Offline Pre-authorised Card (COPAC). He founded the cash-payments company Net1 UEPS Technologies in 1989, led it through dual listings on the NASDAQ and the Johannesburg Stock Exchange, and oversaw the contentious welfare-payments contract with the South African Social Security Agency (SASSA) until his retirement in 2017. Since 2018 he has been non-executive chair of London-based buy-now-pay-later fintech Zilch. == Early life and education == Belamant moved from France to South Africa with his family in 1967 and matriculated from Highlands North Boys' High School, Johannesburg. In 1972 he entered the University of the Witwatersrand to study civil engineering but switched to computer science and applied mathematics in his second year. He left the university without a degree and later took short courses in information systems at the University of South Africa (UNISA). == Early career and SASWITCH (1981–1989) == Belamant worked for Control Data Corporation as a systems analyst for a decade before joining SASWITCH Ltd in 1985. Economic sanctions had left the consortium's national ATM network dependent on unsupported Christian Rovsing computers. Belamant led a rebuild on fault-tolerant Stratus hardware and wrote protocol-translation software that allowed fourteen banks to connect without altering their host systems. By 1988 SASWITCH was handling about three million ATM transactions a month, according to the Competition Commission. The switch—now run by BankservAfrica—remains the backbone of South Africa's shared ATM network. == Net1 UEPS Technologies (1989–2017) == === Founding and UEPS === In 1989, Serge Belamant developed the Universal Electronic Payment System (UEPS), enabling secure, real-time transactions even in areas with limited connectivity. In the same year, he founded NET1 UEPS Technologies Inc., serving as its CEO and Director. === COPAC for VISA === In 1995, VISA tasked Belamant with designing the Chip Offline Pre-authorized Card (COPAC), a technology still widely used in chip-enabled credit and debit cards. A year later, he listed his company APLITEC (Applied Technology Holdings Limited) on the Johannesburg Stock Exchange. === Listings and acquisitions === In 1999, Belamant acquired Cash Payment Services (CPS) from First National Bank of South Africa, modernizing its welfare payment system to serve millions in rural areas. In 2005, he led NET1 Technologies to an IPO, listing it as NET1 UEPS Technologies Inc. on the Nasdaq. A secondary listing on the Johannesburg Stock Exchange (JSE) followed in 2008. === SASSA contract === Under Belamant's leadership, NET1 managed welfare payments for the South African Social Security Agency (SASSA), handling payments for over 10 million beneficiaries monthly. Despite criticism over handling the SASSA contract, investigations by the U.S. Department of Justice and the South African Constitutional Court found no wrongdoing. == Zilch (2018–present) == Belamant co-founded London-based "buy-now-pay-later" firm Zilch Technology in 2018 and serves as non-executive chair. Zilch reported £145 million in annual-recurring revenue and 4.5 million customers in January 2025. == Patents == Belamant is listed as inventor on more than a dozen payment-security patents, including: "Funds transfer system" (US RE36,788, 2000) – the basis for UEPS. "Financial transactions with a varying PIN" (WO 2014/037869, 2014).

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