AI Chat Character Apps

AI Chat Character Apps — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Association for Computational Linguistics

    Association for Computational Linguistics

    The Association for Computational Linguistics (ACL) is a scientific and professional organization for people working on natural language processing. Its namesake conference is one of the primary high impact conferences for natural language processing research, along with EMNLP. The conference is held each summer in locations where significant computational linguistics research is carried out. It was founded in 1962, originally named the Association for Machine Translation and Computational Linguistics (AMTCL). It became the ACL in 1968. The ACL has a European (EACL), a North American (NAACL), and an Asian (AACL) chapter. == History == The ACL was founded in 1962 as the Association for Machine Translation and Computational Linguistics (AMTCL). The initial membership was about 100. In 1965, the AMTCL took over the journal Mechanical Translation and Computational Linguistics. This journal was succeeded by many other journals: the American Journal of Computational Linguistics (1974–1978, 1980–1983), and then Computational Linguistics (1984–present). Since 1988, the journal has been published for the ACL by MIT Press. The annual meeting was first held in 1963 in conjunction with the Association for Computing Machinery National Conference. The annual meeting was, for a long time, relatively informal and did not publish anything longer than abstracts. By 1968, the society took on its current name, the Association for Computational Linguistics (ACL). The publication of the annual meeting's Proceedings of the ACL began in 1979 and gradually matured into its modern form. Many of the meetings were held in conjunction with the Linguistic Society of America, and a few with the American Society for Information Science and the Cognitive Science Society. The United States government sponsored much research from 1989 to 1994, characterized by an increase in author retention rates and an increase in research in some key topics, such as speech recognition, in ACL. By the 21st century, it was able to maintain authors at a high rate who coalesced in a more stable arrangement around individual research topics. In 1991, the group published a prototype for a text generator based on the universal grammar theory of Noam Chomsky. The system, nicknamed Parrot, relied on a finite set of syntactic transformations and a hand-curated lexicon. Despite some initial success, including experimentation with morpheme syntactics, funding halted after the research team encountered intractable difficulties with inflection and abstract locutions. == Annual Meeting of the ACL == Every year, the ACL holds the Annual Meeting of the ACL. The location lies in Europe in years zero modulo three, North America in years one modulo three, and Asia–Australia in years two modulo three. In 2020, the Annual Meeting received for the first time more submissions from China than the United States. == Activities == The ACL organizes several of the top conferences and workshops in the field of computational linguistics and natural language processing. These include: Annual Meeting of the Association for Computational Linguistics (ACL), the flagship conference of the organization Empirical Methods in Natural Language Processing (EMNLP) International Joint Conference on Natural Language Processing (IJCNLP), held jointly one of the other conferences on a rotating basis Conference on Computational Natural Language Learning (CoNLL) Lexical and Computational Semantics and Semantic Evaluation (SemEval) Joint Conference on Lexical and Computational Semantics (SEM) Workshop on Statistical Machine Translation (WMT) Besides conferences, the ACL also sponsors the journals Computational Linguistics and Transactions of the Association for Computational Linguistics (TACL). Papers and other presentations at ACL and ACL-affiliated venues are archived online in the open-access ACL Anthology. == Special Interest Groups == ACL has a large number of Special Interest Groups (SIGs), focusing on specific areas of natural language processing. Some current SIGs within ACL are: == Presidents == Each year, the ACL elects a distinguished computational linguist who becomes vice-president of the organization in the next calendar year and president one year later. Recent ACL presidents are:

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  • Content Credentials

    Content Credentials

    Content Credentials (also known as C2PA signatures) are a digital media metadata specification. They aim to provide provenance information about a piece of media (such as an image or a video) and help prove its authenticity. They are described as the equivalent of nutrition labels for digital media. One of the stated goal of this specification is to fight online disinformation. The specification is written and maintained by the Coalition for Content Provenance and Authenticity (C2PA), a group of many media and tech organizations including Adobe, Amazon, the BBC, Google, Meta, Microsoft, OpenAI and Sony. Another organization, the Content Authenticity Initiative (CAI), is responsible for promoting the standard and accelerate its adoption. The standard relies on cryptographic digital signatures. == Adoption == There are two main stakeholders who can implement Content Credentials: Producers (softwares and hardwares that produce or modify digital media) and publishers (softwares that show digital media to users). === Producers === ==== Adobe ==== Adobe is one of the first companies to implement the specification, announcing support in Photoshop in 2021. Content Credentials can be enabled and the complete history of edits is kept. ==== Google ==== Google announced support for Content Credentials on its Pixel 10 phones in August 2025. The Content Credentials are embedded on each picture taken from the Pixel Camera, and modifications done using Google Photos. Information include picture timestamp and a non-identifiable signature that proves it was taken from a Pixel 10. As for Google Photos, a list of AI and non-AI edits are kept. Google is the first company to introduce support for Content Credentials on either phones or consumer-grade devices, and also the first company to make it available for free to all users. ==== Nikon ==== Nikon announced in 2024 that their Z6 III camera would support embedding Content Credentials in its photos. However, in 2025, a vulnerability was discovered in the software of the camera that allowed to combine unauthentic images with authentic photos and still have the resulting image with a valid digital signature. Nikon revoked the certificates. ==== Media organizations ==== CBC/Radio-Canada and the BBC both have started attaching Content Credentials to media they produce or verify. ==== OpenAI ==== OpenAI embeds Content Credentials on the images and videos it generates that includes that the media was created by AI using their platforms. ==== Sony ==== In June 2025, Sony announced the release of its Camera Verify system for press photographers and news editors using C2PA digital signatures. Initially, the system will be limited to still images, high‑end cameras, and selected news agencies. Registration with Sony Creators' Cloud is also required. === Publishers === ==== LinkedIn ==== In 2024, LinkedIn started showing a "CR" icon on images that contain Content Credentials of AI-generated images. In 2025, they announced a partnership with Adobe to allow photographers to prove ownership of images using Content Credentials. ==== TikTok ==== TikTok announced in 2024 that an "AI-generated" label would be applied to videos containing Content Credentials if they were AI-generated. In 2025, they announced that users could control the amount of AI-generated content they see, using self-reported labels, Content Credentials and an invisible, proprietary AI watermark embedded in videos by their AI editor tool. ==== YouTube ==== In 2024, YouTube started showing to users a label that reads "captured with a camera" on videos that show authentic, unedited videos taken by Content Credentials-compatible cameras.

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  • Computer aided transceiver

    Computer aided transceiver

    Computer aided transceiver (CAT) is a non-generic serial protocol used by radio amateurs for (remotely) controlling a transceiver radio receiver equipment using a computer. Conventional transmitters are manually controlled and used to transmit voice using buttons, dials, etc. However, advances in electronics have come to market devices that can be controlled by a computer and allow digital modes such as packet radio and also the use of satellite tracking, because it can continuously change the device's frequency according to the Doppler effect. This is done by connecting a Radio receiver and a PC using a CAT interface and a CAT Program Additionally, CAT interfaces can also be used to position tracking antennas, in controllers. As a satellite moves overhead. A CAT interface is a piece of hardware that connects the PC and radio that provides a connection to allows the radio and the PC to communicate with each other. The CAT interface provides the signals to and fro via correct voltage levels and in the case of a Universal Serial Bus (USB) CAT interface it requires a "protocol" for communication but communication itself is down to the radio and the software on the PC. Software that may be called a CAT program allows a radio to be controlled through the PC. Changes made on the radio through user interactions on the CAT Program are (generally) shown on the PC's screen. The functionality of CAT equipment (software & interface) depends on the radio and what features the software writers included in the CAT software. Modern radio systems do have more CAT functionality If you run a logging program that supports CAT, then that software may take advantage of the CAT system by retrieving information from the radio to help fill in log details, such as the frequency that the contact was made. CAT is also useful on many radios where there are many sub-menus in the radios menu system, and many of the sub-menu items can be easily changed via the PC. On many HF radios, the CAT system is also used to program the memories on the radio, but you would need to use appropriate programming software. A CAT interface does not receive or transmit any DATA mode, that is the purpose of a DATA interface. Although, both may be used at the same time with the correct CAT Equipment. DATA modes, and getting audio to and from the PC is the function of a DATA interface. A completely different thing but it is easier and more useful when CAT and DATA are used at the same time. Wouldn't it be nice to have an interface that could operate Frequency-shift keying (FSK), Audio FSK (AFSK), (real) Morse Code (CW), with a CAT interface and its own sound card..... (eg. The DigiMaster Pro3).

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  • Information Age

    Information Age

    The Information Age is a historical period that began in the mid-20th century. It is characterized by a rapid shift from traditional industries, as established during the Industrial Revolution, to an economy centered on information technology. The onset of the Information Age has been linked to the development of the transistor in 1947. Advances in computer miniaturization, internet communication, and semiconductor technology enabled the rapid expansion of digital systems and global information networks. The Information Age transformed industries such as education, healthcare, finance, entertainment, and communication through digital infrastructure and connected technologies. The rise of smartphones and cloud-based services further accelerated global internet accessibility and digital interaction. == Digital applications and mobile technology == The expansion of Android and iOS ecosystems during the 21st century contributed to the widespread use of utility applications and mobile productivity tools. Applications related to calculations, scheduling, digital organization, and educational support became increasingly common on smartphones and tablets. Mobile utility software demonstrates how modern digital platforms support accessibility and everyday online services. Independent developers have contributed to this technological ecosystem through lightweight applications focused on mobile usability and internet-based functionality. == Influence on modern society == The Information Age has reshaped the way individuals communicate, consume information, and interact with digital services. Social media platforms, artificial intelligence systems, cloud storage, and mobile computing continue to influence modern economies and online communities worldwide. Emerging technologies such as the Internet of things, machine learning, and advanced automation are often associated with the transition toward the Fourth Industrial Revolution. == History == The digital revolution converted technology from analog format to digital format. By doing this, it became possible to make copies that were identical to the original. In digital communications, for example, repeating hardware was able to amplify the digital signal and pass it on with no loss of information in the signal. Of equal importance to the revolution was the ability to easily move the digital information between media and to access or distribute it remotely. One turning point of the revolution was the change from analog to digitally recorded music. During the 1980s, the digital format of optical compact discs gradually replaced analog formats, such as vinyl records and cassette tapes, as the popular medium of choice. === Previous inventions === Humans have manufactured tools for counting and calculating since ancient times, such as the abacus, astrolabe, equatorium, and mechanical timekeeping devices. More complicated devices started appearing in the 1600s, including the slide rule and mechanical calculators. By the early 1800s, the Industrial Revolution had produced mass-market calculators like the arithmometer and the enabling technology of the punch card. Charles Babbage proposed a mechanical general-purpose computer called the Analytical Engine, but it was never successfully built, and was largely forgotten by the 20th century, and unknown to most of the inventors of modern computers. The Second Industrial Revolution, in the last quarter of the 19th century, developed useful electrical circuits and the telegraph. In the 1880s, Herman Hollerith developed electromechanical tabulating and calculating devices using punch cards and unit record equipment, which became widespread in business and government. Meanwhile, various analog computer systems used electrical, mechanical, or hydraulic systems to model problems and calculate answers. These included an 1872 tide-predicting machine, differential analysers, perpetual calendar machines, the Deltar for water management in the Netherlands, network analyzers for electrical systems, and various machines for aiming military guns and bombs. The construction of problem-specific analog computers continued in the late 1940s and beyond, with FERMIAC for neutron transport, Project Cyclone for various military applications, and the Phillips Machine for economic modeling. Building on the complexity of the Z1 and Z2, German inventor Konrad Zuse used electromechanical systems to complete in 1941 the Z3, the world's first working programmable, fully automatic digital computer. Also, during World War II, Allied engineers constructed electromechanical bombes to break the German Enigma machine encoding. The base-10 electromechanical Harvard Mark I was completed in 1944, and was to some degree improved with inspiration from Charles Babbage's designs. === 1947–1969: Origins === In 1947, the first working transistor, the germanium-based point-contact transistor, was invented by John Bardeen and Walter Houser Brattain while working under William Shockley at Bell Labs. This led the way to more advanced digital computers. From the late 1940s, universities, the military, and businesses developed computer systems to digitally replicate and automate previously manually performed mathematical calculations, with the LEO being the first commercially available general-purpose computer. Digital communication became economical for widespread adoption after the invention of the personal computer in the 1970s. Claude Shannon, a Bell Labs mathematician, is generally credited with laying the foundations of digitalization in his pioneering 1948 article, A Mathematical Theory of Communication. In 1948, Bardeen and Brattain patented an insulated-gate transistor (IGFET) with an inversion layer. Their concept forms the basis of CMOS and DRAM technology today. In 1957, at Bell Labs, Frosch and Derick were able to manufacture planar silicon dioxide transistors, later a team at Bell Labs demonstrated a working MOSFET. The first integrated circuit milestone was achieved by Jack Kilby in 1958. Other important technological developments included the invention of the monolithic integrated circuit chip by Robert Noyce at Fairchild Semiconductor in 1959, made possible by the planar process developed by Jean Hoerni. In 1963, complementary MOS (CMOS) was developed by Chih-Tang Sah and Frank Wanlass at Fairchild Semiconductor. The self-aligned gate transistor, which further facilitated mass production, was invented in 1966 by Robert Bower at Hughes Aircraft and independently by Robert Kerwin, Donald Klein, and John Sarace at Bell Labs. In 1962, AT&T deployed the T-carrier for long-haul pulse-code modulation (PCM) digital voice transmission. The T1 format carried 24 pulse-code modulated, time-division multiplexed speech signals, each encoded in 64 kbit/s streams, leaving 8 kbit/s of framing information, which facilitated the synchronization and demultiplexing at the receiver. Over the subsequent decades, the digitisation of voice became the norm for all but the last mile (where analogue continued to be the norm right into the late 1990s). Following the development of MOS integrated circuit chips in the early 1960s, MOS chips reached higher transistor density and lower manufacturing costs than bipolar integrated circuits by 1964. MOS chips further increased in complexity at a rate predicted by Moore's law, leading to large-scale integration (LSI) with hundreds of transistors on a single MOS chip by the late 1960s. The application of MOS LSI chips to computing was the basis for the first microprocessors, as engineers began recognizing that a complete computer processor could be contained on a single MOS LSI chip. In 1968, Fairchild engineer Federico Faggin improved MOS technology with his development of the silicon-gate MOS chip, which he later used to develop the Intel 4004, the first single-chip microprocessor. It was released by Intel in 1971 and laid the foundations for the microcomputer revolution that began in the 1970s. MOS technology also led to the development of semiconductor image sensors suitable for digital cameras. The first such image sensor was the charge-coupled device, developed by Willard S. Boyle and George E. Smith at Bell Labs in 1969, based on MOS capacitor technology. === 1969–1989: Invention of the internet, rise of home computers === The public was first introduced to the concepts that led to the Internet when a message was sent over the ARPANET in 1969. Packet switched networks such as ARPANET, Mark I, CYCLADES, Merit Network, Tymnet, and Telenet, were developed in the late 1960s and early 1970s using a variety of protocols. The ARPANET in particular led to the development of protocols for internetworking, in which multiple separate networks could be joined into a network of networks. The Whole Earth movement of the 1960s advocated the use of new technology. In the 1970s, the home computer was introduced, time-sharing computers, the video game console, the first coin-op vide

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  • Eigenmoments

    Eigenmoments

    EigenMoments is a set of orthogonal, noise robust, invariant to rotation, scaling and translation and distribution sensitive moments. Their application can be found in signal processing and computer vision as descriptors of the signal or image. The descriptors can later be used for classification purposes. It is obtained by performing orthogonalization, via eigen analysis on geometric moments. == Framework summary == EigenMoments are computed by performing eigen analysis on the moment space of an image by maximizing signal-to-noise ratio in the feature space in form of Rayleigh quotient. This approach has several benefits in Image processing applications: Dependency of moments in the moment space on the distribution of the images being transformed, ensures decorrelation of the final feature space after eigen analysis on the moment space. The ability of EigenMoments to take into account distribution of the image makes it more versatile and adaptable for different genres. Generated moment kernels are orthogonal and therefore analysis on the moment space becomes easier. Transformation with orthogonal moment kernels into moment space is analogous to projection of the image onto a number of orthogonal axes. Nosiy components can be removed. This makes EigenMoments robust for classification applications. Optimal information compaction can be obtained and therefore a few number of moments are needed to characterize the images. == Problem formulation == Assume that a signal vector s ∈ R n {\displaystyle s\in {\mathcal {R}}^{n}} is taken from a certain distribution having correlation C ∈ R n × n {\displaystyle C\in {\mathcal {R}}^{n\times n}} , i.e. C = E [ s s T ] {\displaystyle C=E[ss^{T}]} where E[.] denotes expected value. Dimension of signal space, n, is often too large to be useful for practical application such as pattern classification, we need to transform the signal space into a space with lower dimensionality. This is performed by a two-step linear transformation: q = W T X T s , {\displaystyle q=W^{T}X^{T}s,} where q = [ q 1 , . . . , q n ] T ∈ R k {\displaystyle q=[q_{1},...,q_{n}]^{T}\in {\mathcal {R}}^{k}} is the transformed signal, X = [ x 1 , . . . , x n ] T ∈ R n × m {\displaystyle X=[x_{1},...,x_{n}]^{T}\in {\mathcal {R}}^{n\times m}} a fixed transformation matrix which transforms the signal into the moment space, and W = [ w 1 , . . . , w n ] T ∈ R m × k {\displaystyle W=[w_{1},...,w_{n}]^{T}\in {\mathcal {R}}^{m\times k}} the transformation matrix which we are going to determine by maximizing the SNR of the feature space resided by q {\displaystyle q} . For the case of Geometric Moments, X would be the monomials. If m = k = n {\displaystyle m=k=n} , a full rank transformation would result, however usually we have m ≤ n {\displaystyle m\leq n} and k ≤ m {\displaystyle k\leq m} . This is specially the case when n {\displaystyle n} is of high dimensions. Finding W {\displaystyle W} that maximizes the SNR of the feature space: S N R t r a n s f o r m = w T X T C X w w T X T N X w , {\displaystyle SNR_{transform}={\frac {w^{T}X^{T}CXw}{w^{T}X^{T}NXw}},} where N is the correlation matrix of the noise signal. The problem can thus be formulated as w 1 , . . . , w k = a r g m a x w w T X T C X w w T X T N X w {\displaystyle {w_{1},...,w_{k}}=argmax_{w}{\frac {w^{T}X^{T}CXw}{w^{T}X^{T}NXw}}} subject to constraints: w i T X T N X w j = δ i j , {\displaystyle w_{i}^{T}X^{T}NXw_{j}=\delta _{ij},} where δ i j {\displaystyle \delta _{ij}} is the Kronecker delta. It can be observed that this maximization is Rayleigh quotient by letting A = X T C X {\displaystyle A=X^{T}CX} and B = X T N X {\displaystyle B=X^{T}NX} and therefore can be written as: w 1 , . . . , w k = a r g m a x x w T A w w T B w {\displaystyle {w_{1},...,w_{k}}={\underset {x}{\operatorname {arg\,max} }}{\frac {w^{T}Aw}{w^{T}Bw}}} , w i T B w j = δ i j {\displaystyle w_{i}^{T}Bw_{j}=\delta _{ij}} === Rayleigh quotient === Optimization of Rayleigh quotient has the form: max w R ( w ) = max w w T A w w T B w {\displaystyle \max _{w}R(w)=\max _{w}{\frac {w^{T}Aw}{w^{T}Bw}}} and A {\displaystyle A} and B {\displaystyle B} , both are symmetric and B {\displaystyle B} is positive definite and therefore invertible. Scaling w {\displaystyle w} does not change the value of the object function and hence and additional scalar constraint w T B w = 1 {\displaystyle w^{T}Bw=1} can be imposed on w {\displaystyle w} and no solution would be lost when the objective function is optimized. This constraint optimization problem can be solved using Lagrangian multiplier: max w w T A w {\displaystyle \max _{w}{w^{T}Aw}} subject to w T B w = 1 {\displaystyle {w^{T}Bw}=1} max w L ( w ) = max w ( w T A w − λ w T B w ) {\displaystyle \max _{w}{\mathcal {L}}(w)=\max _{w}(w{T}Aw-\lambda w^{T}Bw)} equating first derivative to zero and we will have: A w = λ B w {\displaystyle Aw=\lambda Bw} which is an instance of Generalized Eigenvalue Problem (GEP). The GEP has the form: A w = λ B w {\displaystyle Aw=\lambda Bw} for any pair ( w , λ ) {\displaystyle (w,\lambda )} that is a solution to above equation, w {\displaystyle w} is called a generalized eigenvector and λ {\displaystyle \lambda } is called a generalized eigenvalue. Finding w {\displaystyle w} and λ {\displaystyle \lambda } that satisfies this equations would produce the result which optimizes Rayleigh quotient. One way of maximizing Rayleigh quotient is through solving the Generalized Eigen Problem. Dimension reduction can be performed by simply choosing the first components w i {\displaystyle w_{i}} , i = 1 , . . . , k {\displaystyle i=1,...,k} , with the highest values for R ( w ) {\displaystyle R(w)} out of the m {\displaystyle m} components, and discard the rest. Interpretation of this transformation is rotating and scaling the moment space, transforming it into a feature space with maximized SNR and therefore, the first k {\displaystyle k} components are the components with highest k {\displaystyle k} SNR values. The other method to look at this solution is to use the concept of simultaneous diagonalization instead of Generalized Eigen Problem. === Simultaneous diagonalization === Let A = X T C X {\displaystyle A=X^{T}CX} and B = X T N X {\displaystyle B=X^{T}NX} as mentioned earlier. We can write W {\displaystyle W} as two separate transformation matrices: W = W 1 W 2 . {\displaystyle W=W_{1}W_{2}.} W 1 {\displaystyle W_{1}} can be found by first diagonalize B: P T B P = D B {\displaystyle P^{T}BP=D_{B}} . Where D B {\displaystyle D_{B}} is a diagonal matrix sorted in increasing order. Since B {\displaystyle B} is positive definite, thus D B > 0 {\displaystyle D_{B}>0} . We can discard those eigenvalues that large and retain those close to 0, since this means the energy of the noise is close to 0 in this space, at this stage it is also possible to discard those eigenvectors that have large eigenvalues. Let P ^ {\displaystyle {\hat {P}}} be the first k {\displaystyle k} columns of P {\displaystyle P} , now P T ^ B P ^ = D B ^ {\displaystyle {\hat {P^{T}}}B{\hat {P}}={\hat {D_{B}}}} where D B ^ {\displaystyle {\hat {D_{B}}}} is the k × k {\displaystyle k\times k} principal submatrix of D B {\displaystyle D_{B}} . Let W 1 = P ^ D B ^ − 1 / 2 {\displaystyle W_{1}={\hat {P}}{\hat {D_{B}}}^{-1/2}} and hence: W 1 T B W 1 = ( P ^ D B ^ − 1 / 2 ) T B ( P ^ D B ^ − 1 / 2 ) = I {\displaystyle W_{1}^{T}BW_{1}=({\hat {P}}{\hat {D_{B}}}^{-1/2})^{T}B({\hat {P}}{\hat {D_{B}}}^{-1/2})=I} . W 1 {\displaystyle W_{1}} whiten B {\displaystyle B} and reduces the dimensionality from m {\displaystyle m} to k {\displaystyle k} . The transformed space resided by q ′ = W 1 T X T s {\displaystyle q'=W_{1}^{T}X^{T}s} is called the noise space. Then, we diagonalize W 1 T A W 1 {\displaystyle W_{1}^{T}AW_{1}} : W 2 T W 1 T A W 1 W 2 = D A {\displaystyle W_{2}^{T}W_{1}^{T}AW_{1}W_{2}=D_{A}} , where W 2 T W 2 = I {\displaystyle W_{2}^{T}W_{2}=I} . D A {\displaystyle D_{A}} is the matrix with eigenvalues of W 1 T A W 1 {\displaystyle W_{1}^{T}AW_{1}} on its diagonal. We may retain all the eigenvalues and their corresponding eigenvectors since most of the noise are already discarded in previous step. Finally the transformation is given by: W = W 1 W 2 {\displaystyle W=W_{1}W_{2}} where W {\displaystyle W} diagonalizes both the numerator and denominator of the SNR, W T A W = D A {\displaystyle W^{T}AW=D_{A}} , W T B W = I {\displaystyle W^{T}BW=I} and the transformation of signal s {\displaystyle s} is defined as q = W T X T s = W 2 T W 1 T X T s {\displaystyle q=W^{T}X^{T}s=W_{2}^{T}W_{1}^{T}X^{T}s} . === Information loss === To find the information loss when we discard some of the eigenvalues and eigenvectors we can perform following analysis: η = 1 − t r a c e ( W 1 T A W 1 ) t r a c e ( D B − 1 / 2 P T A P D B − 1 / 2 ) = 1 − t r a c e ( D B ^ − 1 / 2 P ^ T A P ^ D B ^ − 1 / 2 ) t r a c e ( D B − 1 / 2 P T A P D B − 1 / 2 ) {\displaystyle {\begin{array}{lll}\eta &=&

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  • T.38

    T.38

    T.38 is an ITU recommendation for allowing transmission of fax over IP networks (FoIP) in real time. == History == The T.38 fax relay standard was devised in 1998 as a way to transport faxes across IP networks between existing Group 3 (G3) fax terminals. T.4 and related fax standards were published by the ITU in 1980, before the rise of the Internet. In the late 1990s, VoIP, or voice over IP, began to gain ground as an alternative to the conventional public switched telephone network (PSTN). However, because most VoIP systems are optimized (through their use of aggressive lossy bandwidth-saving compression) for voice rather than data calls, conventional fax machines worked poorly or not at all on them due to the network impairments such as delay, jitter, packet loss, and so on. Thus, some way of transmitting fax over IP was needed. == Overview == In practical scenarios, a T.38 fax call has at least part of the call being carried over PSTN, although this is not required by the T.38 definition, and two T.38 devices can send faxes to each other. This particular type of device is called Internet-Aware Fax device, or IAF, and it is capable of initiating or completing a fax call towards the IP network. The typical scenario where T.38 is used is – T.38 fax relay – where a T.30 fax device sends a fax over PSTN to a T.38 fax gateway which converts or encapsulates the T.30 protocol into a T.38 data stream. This is then sent either to a T.38-enabled end point such as fax machine or fax server or another T.38 gateway that converts it back to a PSTN PCM or analog signal and terminates the fax on a T.30 device. The T.38 recommendation defines the use of both TCP and UDP to transport T.38 packets. Implementations tend to use UDP, due to TCP's requirement for acknowledgement packets and resulting retransmission during packet loss, which introduces delays. When using UDP, T.38 copes with packet loss by using redundant data packets. T.38 is not a call setup protocol, thus the T.38 devices need to use standard call setup protocols to negotiate the T.38 call, e.g. H.323, SIP & MGCP. == Operation == There are two primary ways that fax transactions are conveyed across packet networks. The T.37 standard specifies how a fax image is encapsulated in e-mail and transported, ultimately, to the recipient using a store-and-forward process through intermediary entities. T.38, however, defines a protocol that supports the use of the T.30 protocol in both the sender and recipient terminals. (See diagram above.) T.38 lets one transmit a fax across an IP network in real time, just as the original G3 fax standards did for the traditional (time-division multiplexed (TDM)) network, also called the public switched telephone network or PSTN. A special protocol is needed for real-time fax over IP (Internet Protocol) since existing fax terminals only supported PSTN connections, where the information flow was generally smooth and uninterrupted, as opposed to the jittery arrival of IP packets. The trick was to come up with a protocol that makes the IP network “invisible” to the endpoint fax terminals, which would mean the user of a legacy fax terminal need not know that the fax call was traversing an IP network. The network interconnections supported by T.38 are shown above. The two fax terminals on either side of the figure communicate using the T.30 fax protocol published by the ITU in 1980. Interconnection of the PSTN with the IP packet network requires a “gateway” between the PSTN and IP networks. PSTN-IP Gateways support TDM voice on the PSTN side and VoIP and FoIP on the packet side. For voice sessions, the gateway will take in voice packets on the IP side, accumulate a few packets to ensure a smooth flow of TDM data upon their release, and then meter them out over TDM where they eventually are heard by a human or stored on a computer for later playback. The gateway employs packet-management techniques to enhance the quality of the speech in the presence of network errors by taking advantage of the natural ability of a listener to not really hear the occasional missing or repeated packet. But facsimile data are transmitted by modems, which aren't as forgiving as the human ear is for speech. Missing packets will often cause a fax session to fail at worst or create one or more image lines in error at best. So the job of T.38 is to “fool” the terminal into “thinking” that it's communicating directly with another T.30 terminal. It will also correct for network delays with so-called spoofing techniques, and missing or delayed packets with fax-aware buffer-management techniques. Spoofing refers to the logic implemented in the protocol engine of a T.38 relay that modifies the protocol commands and responses on the TDM side to keep network delays on the IP side from causing the transaction to fail. This is done, for example, by padding image lines or deliberately causing a message to be re-transmitted to render network delays transparent to the sending/receiving fax terminals. Networks that do not have packet loss or excessive delay can exhibit acceptable fax performance without T.38, provided the PCM clocks in all gateways are of very high accuracy (explained below). T.38 not only removes the effect of PCM clocks not being synchronized, but also reduces the required network bandwidth by a factor of 10, while it corrects for packet loss and delay. === Bandwidth reduction === As shown in the diagram below, a T.38 gateway is composed of two primary elements: the fax modems and the T.38 subsystem. The fax modems modulate and demodulate the PCM samples of the analog data, turning the sampled-data representation of the fax terminal's analog signal to its binary translation, and vice versa. The PSTN network samples the analog signal of a voice or modem signal (it doesn't know the difference) 8,000 times per second (SPS), and encodes them as 8-bit data bytes. This means 8000 samples-per-second times 8-bits per sample, or 64,000 bits per second (bit/s) to represent the modem (or voice) data in one direction. For both directions the modem transaction consumes 128,000 bits of network bandwidth. However, the typical modem in a fax terminal transmits the image data at 33,600 bit/s, so if the analog data are first converted to the digital content they represent, only 33,600 bits (plus network overhead of a few bytes) are needed. And since T.30 fax is a half-duplex protocol, the network is only needed for one direction at a time. Refer to RFC 3261 === PCM clock synchronization === In the diagram above, there is a sample-rate clock in the fax terminal and one in the gateway's modems that is used to trigger the sampling of the analog line 8,000 times per second. These clocks are usually quite accurate, but in some low-cost terminal adapters (a one or two-line gateway) the PCM clock can be surprisingly inaccurate. If the terminal is sending data to the gateway, and the gateway's clock is too slow, the buffers (jitter buffers) in the gateway will eventually overflow, causing the transaction to fail. Since the difference is often quite small, this problem occurs on long, detailed fax images giving the clocks more time to cause the jitter buffer in gateway to either underflow or overflow, which is just the same as missing or duplicated packets. === Packet loss === T.38 provides facilities to eliminate the effects of packet loss through data redundancy. When a packet is sent, either zero, one, two, three, or even more of the previously sent packets are repeated. (The specification does not impose a limit.) This increases the network bandwidth required (it's still much less than not using T.38) but it allows the receiving gateway to reconstruct the complete packet sequence, even with a fairly high level of packet loss. == Related standards == T.4 is the umbrella specification for fax. It specifies the standard image sizes, two forms of image-data compression (encoding), the image-data format, and references, T.30 and the various modem standards. T.6 specifies a compression scheme that reduces the time required to transmit an image by roughly 50-percent. T.30 specifies the procedures that a sending and receiving terminal use to set up a fax call, determine the image size, encoding, and transfer speed, the demarcation between pages, and the termination of the call. T.30 also references the various modem standards. V.21, V.27ter, V.29, V.17, V.34: ITU modem standards used in facsimile. The first three were ratified prior to 1980, and were specified in the original T.4 and T.30 standards. V.34 was published for fax in 1994. T.37 The ITU standard for sending a fax-image file via e-mail to the intended recipient of a fax. G.711 pass through - this is where the T.30 fax call is carried in a VoIP call encoded as audio. This is sensitive to network packet loss, jitter and clock synchronization. When using voice high-compression encoding techniques such as, but not limited to, G.729, some fax tonal signa

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  • Digital signage

    Digital signage

    Digital signage is a segment of electronic signage that uses digital display technologies to present multimedia content in both public and private environments. Content may include video, images, text, or interactive media and is typically displayed for purposes such as advertising, information dissemination, branding, or entertainment. Digital signage systems can be either networked or standalone. Networked systems are managed through centralized content management systems (CMS), often cloud-based, enabling remote updates, scheduling, real-time data integration, and dynamic content delivery. These systems may also incorporate audience analytics, IoT sensors, or AI-driven personalization. Standalone systems, by contrast, operate without a network connection. They rely on local media playback via USB drives, SD cards, or internal storage. These solutions are simpler and suitable for locations where connectivity is limited or content changes infrequently. == Applications of digital signage == Digital signage is widely used in transportation hubs, retail stores, restaurants, corporate buildings, hotels, educational institutions, healthcare facilities, and public spaces. One prominent application of digital signage is Digital Out-of-Home (DOOH) advertising, which leverages digital signage displays in public spaces to deliver targeted advertisements to people outside of their homes. DOOH has become a significant segment of digital signage, providing advertisers with a dynamic and contextually relevant way to engage with audiences. == Components == === Hardware components === Digital signage hardware includes the physical equipment used to show multimedia content in public and private spaces. ==== Display devices ==== Display devices are the most prominent components of a digital signage system, serving as the primary medium for presenting content. Display devices come in various technologies, such as LCD, LED, and OLED formats, each offering different advantages in terms of clarity, color reproduction, and energy efficiency. In addition to flat-panel displays, projectors are also commonly used in digital signage, particularly in large-scale settings. Projectors can cast large-format visuals onto walls, screens, or other surfaces, providing flexibility in display size and positioning. Screen sizes vary widely to suit different applications. Smaller panels are often used in kiosks and point-of-sale systems, while larger displays, such as video walls and projection surfaces, are deployed in venues like stadiums, auditoriums, and other public spaces. Many digital signage displays are also equipped with touchscreen capabilities, allowing for interactive applications. These interactive displays are commonly used in information kiosks, wayfinding systems, and self-service applications. ==== Playback devices ==== Playback devices are specialized hardware components that manage the storage, processing, and transmission of multimedia content to digital signage displays and projectors. They serve as the crucial link between the content management system (CMS) and the visual output, ensuring seamless playback of static images, video files, animated graphics, and real-time content, such as news feeds. Playback devices can be standalone units or integrated into display hardware using System-on-Chip (SoC) technology. The latter reduces hardware complexity and installation time, making the system more efficient. These devices support remote or local content updates, allowing digital signage operators to manage networks effectively. Content can be updated via cloud-based platforms for centralized control or through direct interfaces on-site, depending on the system's configuration and deployment requirements. ==== Mounting systems ==== Mounting systems provide structural support for digital signage displays, enabling deployment across diverse environments. Typical configurations include wall mounts, ceiling mounts, and floor stands each engineered to meet specific spatial and functional requirements. === Software components === Digital signage software is responsible for content creation, scheduling, and management. It enables users to manage and distribute content to one or more playback devices. ==== Software compatibility ==== Digital signage software supports various operating systems, including Android, Windows, Linux, iOS, tvOS, webOS, Tizen, ChromeOS, macOS, and others. This allows customers to choose the hardware and software solution that best suits their digital signage needs. == Interactivity == Interactivity in digital signage allows users to interact directly with displays using input methods like touch, gestures, voice, or proximity sensors. This feature enables real-time responses and personalized content, improving the user experience. Interactive digital signage is commonly used in places like retail, transportation, education, and public spaces to create engaging and informative interactions. Additionally, self-service kiosks are often integrated into interactive signage solutions, allowing users to perform tasks such as ordering products, checking in for flights, accessing information, or making payments. These kiosks empower users to complete transactions or obtain services independently, improving efficiency and convenience in high-traffic locations. == Audience measurement and context-aware content adaptation == === Audience measurement === Cameras can be integrated into digital signage systems to enable audience measurement. They are used to detect and count viewers, estimate demographics such as age and gender, measure dwell time and attention, and sometimes analyze emotional reactions using computer vision techniques. This process is valuable for understanding audience behavior and refining business strategies. Privacy concerns are addressed by anonymizing collected data and avoiding the storage of personally identifiable information. === Context-aware digital signage === Context-aware digital signage refers to systems that adjust content based on environmental or audience data. The infrastructure supporting context awareness, including sensors and analytics systems, also facilitates the collection of audience insights. While these insights may be primarily used for reporting, optimization, or planning future campaigns rather than immediate content adjustments, they play a crucial role in the overall context-aware ecosystem. ==== Contextual information ==== Contextual information in the realm of context-aware digital signage refers to data about the environment, audience, and other factors that influence how digital signage content is displayed. This information helps the system to deliver more relevant, timely, and personalized content to its audience. Contextual information can include, but is not limited to: Audience demographics — this can involve detecting the age, gender, or even emotional state of viewers through cameras or sensors. It helps tailor content to specific audience segments, improving engagement. Time and weather — the system may adjust content based on the time of day or current weather conditions. For example, weather-appropriate content (like a raincoat ad on a rainy day) or time-specific content (like dinner menu promotions in the evening) can be shown. Emergency information — in situations of emergency, systems can prioritize displaying urgent notifications such as fire alerts, disaster warnings, or evacuation instructions. This can be crucial for public safety in crowded environments or densely populated areas. The system may adapt content in real-time to inform and guide individuals to safety, offering location-specific instructions or emergency service contacts. == Challenges == === Display blindness === Digital signage in public spaces has been found to lose visibility, significantly diminishing its ability to capture attention. This issue, known as "Display Blindness", was identified by Müller et al. and refers to the phenomenon where digital advertisements are largely overlooked by passersby. Observations indicate that many of these advertisements fail to resonate with their audience, often being irrelevant or unengaging, which leads to passive reception and reduced interaction. == Comparison with print signage == Digital signage and traditional print signage serve similar purposes by delivering visual information to a target audience, but they differ significantly in terms of flexibility, cost, maintenance, and environmental impact. Digital signage is advantageous in low-light or nighttime environments, where its internal illumination ensures visibility without the need for external lighting, unlike printed signs, which may require additional fixtures to be seen after dark. === Content and flexibility === Digital signage allows for dynamic and real-time content updates, often controlled remotely through content management systems. This makes it well-suited for environments where information chan

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  • Scandiweb

    Scandiweb

    scandiweb is a web development, digital strategy, AI consultation & implementation agency specializing in the Magento (Adobe Commerce) platform. The company was established in 2003 in Latvia by Antons Sapriko. It has offices in the United States, Sweden, Latvia, and Georgia. scandiweb provides solutions for primarily eCommerce businesses and acts as a strategic partner for IT development focusing on web, mobile, and big data analysis. T == Partnerships == scandiweb is an official Adobe Gold Partner, with the largest team of Adobe Commerce-certified employees. The company holds the Google Premier Partner status for 2025, placing it among top 3% agencies globally. scandiweb is a BigCommerce Certified Partner and a Pimcore Platinum Partner. Since 2016, scandiweb has been collaborating with Oro, Inc., an open-source business application development firm. scandiweb is a Platinum Partner of Hyvä, working with the Magento 2 frontend theme to optimize performance metrics. The company is also a Sanity Agency Partner, assisting with content management through Sanity’s headless CMS.

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  • Fuse Mediation Router

    Fuse Mediation Router

    Fuse Mediation Router is an open source tool for integrating services using Enterprise Integration Patterns based on Apache Camel for use in enterprise IT organizations. It is certified, productized and fully supported by the people who wrote the code. Fuse Mediation Router uses a standard method of notation to go from diagram to implementation without coding. Fuse Mediation Router is a rule-based routing and process mediation engine that combines the ease of basic POJO development with the clarity of the standard Enterprise Integration Patterns. It can be deployed inside any container or be used stand-alone, and works directly with any kind of transport or messaging model to rapidly integrate existing services and applications. Fuse Mediation Router is now a part of Red Hat JBoss Fuse. == Tooling == FuseSource offers graphical, Eclipse-based tooling for Apache Camel for download.

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  • CodePen

    CodePen

    CodePen is an online community for testing and showcasing user-created HTML, CSS and JavaScript code snippets. It functions as an online code editor and open-source learning environment, where developers can create code snippets, called "pens," and test them. It was founded in 2012 by full-stack developers Alex Vazquez and Tim Sabat and front-end designer Chris Coyier. Its employees work remotely, rarely all meeting together in person. CodePen is a large community for web designers and developers to showcase their coding skills, with an estimated 330,000 registered users and 14.16 million monthly visitors.

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  • The Big Book of Social Media

    The Big Book of Social Media

    The Big Book of Social Media: Case Studies, Stories, Perspectives, released in November 2010 by Yorkshire Publishing, is a compilation of non-fiction articles and chapters written by social media experts in their respective fields and edited by Robert Fine, organizer of the Cool Social Conferences World Tour and founder of Cool Blue Press, with a foreword by Sam Feist, political director for CNN. == Synopsis == The publisher, on its site, summed up the book as, "Not business. Not marketing. This is an idea book." And an article in Business Insider described the book as bringing "the social back into social media." == Contributors == Contributing authors include: Alan Rosenblatt, Alane Anderson, Alecia Dantico, Alex Priest, Alfred Naranjo, Becky Carroll, Carri Bugbee, Cathy Scott, Colleen Crinklaw, Constantine Markides, Cordelia Mendoza, Craig Kanalley, Dave Ingland, Eric Andersen, Eric Brown, Gary Zukowski, Haja Rasambainarivo, Jennifer Kaplan, Kari Quaas, Lauri Stevens, Lev Ekster, Mark Stelzner, Matthew Felling, Matt Stewart, Melani Gordon, Michael Bourne, Michele Mattia, Mirna Bard, Neal Schaffer, Nic Evans, Noaf Ereiqat, Pek Pongpaet, Perri Gorman, Phil Baumann, Regina Holliday, Rory Cooper, Sam Feist, Shashi Bellamkonda, Shrinath Navghane, Steve Pratt, Ted Nguyen, Todd Schnick, Tonia Ries, Wayne Burke, as well as Robert Fine. In December 2011, some of the contributing authors organized "Tweet It Forward," a holiday charity fundraiser, with net proceeds benefitting the Food Bank for New York City. == Reception == Reviewer Mike Brown wrote on the Brainzooming blog that the book goes "beyond the valueless chatter out there; it provides solid discussions of real-life social media strategy implementations that have truly integrated organizational objectives and delivered real metrics." And Tech Cocktail wrote it in its review, "Through a collection of entertaining anecdotes and insightful marketing agendas, one sees what social media is truly all about and how it is revolutionizing the communications industry." In 2011, at the SXSW social media festival in Austin, Texas, Fine launched Cool Blue Press and reintroduced The Big Book of Social Media, with plans, he told a reporter from the Washington Examiner, for other new media books and publishing projects, including The Social Media Monthly magazine. The book was reviewed in 2012 by SAGE Publications for its Journalism and Mass Communication Educator magazine. It is also cited in several books and journals. === Awards === The book was a winner in the 4th Annual Reader's Choice "Small Business Book Awards" for 2011. Windmill Networking named it the Top 15 recommended social media books of 2010.

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  • Media Block

    Media Block

    A Media Block or Integrated Media Block (IMB) is a component in a digital cinema projection system. Its purpose is to convert the Digital Cinema Package (DCP) content into data that ultimately produces picture and sound in a theater in compliance with DCI anti-piracy encryption requirements. == Terminology == DCI specification allows for two different security system architectures. In the first the Media Block is outside of the projector. This design is simply referred to as a "Media Block" and is typically a device attached directly to the motherboard of a Digital Cinema server. The media block is usually connected to the projector by dual-link SDI cables. Such media block is limited to processing 2K output, downscaling 4K DCPs if necessary. The second architecture describes an "Integrated Media Block". This refers to a device attached and integrated directly into the projector, which receives image data from the server, usually via a cat6 Ethernet connection. They can process 2K and 4K output. Some hardware implementations integrate the entire server on a single board and are able to work both as a MB as well as an IMB. == Security features == All security functions are contained within a Secure Processing Block (SPB), a tamper-proof physical device. Upon ingestion into a DCP server, Key Delivery Messages (KDM) are stored on flash memory in the media block or IMB. A KDM is written to enable the playback of a specific DCP during a specific time window and on a specific media block or IMB, identified by its serial number during the authoring process. Media blocks and IMBs also contain a secure clock that is set in the factory cannot be altered by the end user, which the DCP servers to which they are attached use to determine showtimes. The secure clock prevents theaters from showing encrypted movies outside the times authorized by the KDM (e.g. after it has expired) by simply changing the date and time in the server's BIOS. Media blocks and IMBs also typically include anti-tamper devices, designed to self-destruct the unit if unauthorized modification of its hardware, software or secure clock is attempted.

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  • Quantum artificial life

    Quantum artificial life

    Quantum artificial life is the application of quantum algorithms with the ability to simulate biological behavior. Quantum computers offer many potential improvements to processes performed on classical computers, including machine learning and artificial intelligence. Artificial intelligence applications are often inspired by the idea of mimicking human brains through closely related biomimicry. This has been implemented to a certain extent on classical computers (using neural networks), but quantum computers offer many advantages in the simulation of artificial life. Artificial life and artificial intelligence are extremely similar, with minor differences; the goal of studying artificial life is to understand living beings better, while the goal of artificial intelligence is to create intelligent beings. In 2016, Alvarez-Rodriguez et al. developed a proposal for a quantum artificial life algorithm with the ability to simulate life and Darwinian evolution. In 2018, the same research team led by Alvarez-Rodriguez performed the proposed algorithm on the IBM ibmqx4 quantum computer, and received optimistic results. The results accurately simulated a system with the ability to undergo self-replication at the quantum scale. == Artificial life on quantum computers == The growing advancement of quantum computers has led researchers to develop quantum algorithms for simulating life processes. Researchers have designed a quantum algorithm that can accurately simulate Darwinian Evolution. Since the complete simulation of artificial life on quantum computers has only been actualized by one group, this section shall focus on the implementation by Alvarez-Rodriguez, Sanz, Lomata, and Solano on an IBM quantum computer. Individuals were realized as two qubits, one representing the genotype of the individual and the other representing the phenotype. The genotype is copied to transmit genetic information through generations, and the phenotype is dependent on the genetic information as well as the individual's interactions with their environment. In order to set up the system, the state of the genotype is instantiated by some rotation of an ancillary state ( | 0 ⟩ ⟨ 0 | {\displaystyle |0\rangle \langle 0|} ). The environment is a two-dimensional spatial grid occupied by individuals and ancillary states. The environment is divided into cells that are able to possess one or more individuals. Individuals move throughout the grid and occupy cells randomly; when two or more individuals occupy the same cell they interact with each other. === Self replication === The ability to self-replicate is critical for simulating life. Self-replication occurs when the genotype of an individual interacts with an ancillary state, creating a genotype for a new individual; this genotype interacts with a different ancillary state in order to create the phenotype. During this interaction, one would like to copy some information about the initial state into the ancillary state, but by the no cloning theorem, it is impossible to copy an arbitrary unknown quantum state. However, physicists have derived different methods for quantum cloning which does not require the exact copying of an unknown state. The method that has been implemented by Alvarez-Rodriguez et al. is one that involves the cloning of the expectation value of some observable. For a unitary U {\displaystyle U} which copies the expectation value of some set of observables X {\displaystyle {\mathsf {X}}} of state ρ {\displaystyle \rho } into a blank state ρ e {\displaystyle \rho _{e}} , the cloning machine is defined by any ( U , ρ e , X ) {\displaystyle (U,\rho _{e},{\mathsf {X}})} that fulfill the following: ∀ ρ ∀ X ∈ X {\displaystyle \forall \rho \forall X\in {\mathsf {X}}} X ¯ = X 1 ¯ = X 2 ¯ {\displaystyle {\bar {X}}={\bar {X_{1}}}={\bar {X_{2}}}} Where X ¯ {\displaystyle {\bar {X}}} is the mean value of the observable in ρ {\displaystyle \rho } before cloning, X 1 ¯ {\displaystyle {\bar {X_{1}}}} is the mean value of the observable in ρ {\displaystyle \rho } after cloning, and X 2 ¯ {\displaystyle {\bar {X_{2}}}} is the mean value of the observable in ρ e {\displaystyle \rho _{e}} after cloning. Note that the cloning machine has no dependence on ρ {\displaystyle \rho } because we want to be able to clone the expectation of the observables for any initial state. It is important to note that cloning the mean value of the observable transmits more information than is allowed classically. The calculation of the mean value is defined naturally as: X ¯ = T r [ ρ X ] {\displaystyle {\bar {X}}=Tr[\rho X]} , X 1 ¯ = T r [ R X ⊗ I ] {\displaystyle {\bar {X_{1}}}=Tr[RX\otimes I]} , X 2 ¯ = T r [ R I ⊗ X ] {\displaystyle {\bar {X_{2}}}=Tr[RI\otimes X]} where R = U ρ ⊗ ρ e U † {\displaystyle R=U\rho \otimes \rho _{e}U^{\dagger }} The simplest cloning machine clones the expectation value of σ z {\displaystyle \sigma _{z}} in arbitrary state ρ = | ψ ⟩ ⟨ ψ | {\displaystyle \rho =|\psi \rangle \langle \psi |} to ρ e = | 0 ⟩ ⟨ 0 | {\displaystyle \rho _{e}=|0\rangle \langle 0|} using U = C N O T {\displaystyle U=CNOT} . This is the cloning machine implemented for self-replication by Alvarez-Rodriguez et al. The self-replication process clearly only requires interactions between two qubits, and therefore this cloning machine is the only one necessary for self replication. === Interactions === Interactions occur between individuals when the two take up the same space on the environmental grid. The presence of interactions between individuals provides an advantage for shorter-lifespan individuals. When two individuals interact, exchanges of information between the two phenotypes may or may not occur based on their existing values. When both individual's control qubits (genotypes) are alike, no information will be exchanged. When the control qubits differ, the target qubits (phenotype) will be exchanged between the two individuals. This procedure produces a constantly changing predator-prey dynamic in the simulation. Therefore, long-living qubits, with a larger genetic makeup in the simulation, are at a disadvantage. Since information is only exchanged when interacting with an individual of different genetic makeup, the short-lived population has the advantage. === Mutation === Mutations exist in the artificial world with limited probability, equivalent to their occurrence in the real world. There are two ways in which the individual can mutate: through random single qubit rotations and by errors in the self-replication process. There are two different operators that act on the individual and cause mutations. The M operation causes a spontaneous mutation within the individual by rotating a single qubit by parameter θ. The parameter θ is random for each mutation, which creates biodiversity within the artificial environment. The M operation is a unitary matrix which can be described as: M = ( cos ⁡ ( θ ) s i n ( θ ) s i n ( θ ) − c o s ( θ ) ) {\displaystyle M={\begin{pmatrix}\cos(\theta )&sin(\theta )\\sin(\theta )&-cos(\theta )\end{pmatrix}}} The other possible way for mutations to occur is due to errors in the replication process. Due to the no-cloning theorem, it is impossible to produce perfect copies of systems that are originally in unknown quantum states. However, quantum cloning machines make it possible to create imperfect copies of quantum states, in other words, the process introduces some degree of error. The error that exists in current quantum cloning machines is the root cause for the second kind of mutations in the artificial life experiment. The imperfect cloning operation can be seen as: U M ( θ ) = I 4 + 1 2 ( 0 0 0 1 ) ⊗ ( − 1 1 1 − 1 ) ( c o s θ + i s i n θ + 1 ) {\displaystyle U_{M}(\theta )=\mathrm {I} _{4}+{\frac {1}{2}}{\begin{pmatrix}0&0\\0&1\end{pmatrix}}\otimes {\begin{pmatrix}-1&1\\1&-1\end{pmatrix}}(cos\theta +isin\theta +1)} The two kinds of mutations affect the individual differently. While the spontaneous M operation does not affect the phenotype of the individual, the self-replicating error mutation, UM, alters both the genotype of the individual, and its associated lifetime. The presence of mutations in the quantum artificial life experiment is critical for providing randomness and biodiversity. The inclusion of mutations helps to increase the accuracy of the quantum algorithm. === Death === At the instant the individual is created (when the genotype is copied into the phenotype), the phenotype interacts with the environment. As time evolves, the interaction of the individual with the environment simulates aging which eventually leads to the death of the individual. The death of an individual occurs when the expectation value of σ z {\displaystyle \sigma _{z}} is within some ϵ {\displaystyle \epsilon } of 1 in the phenotype, or, equivalently, when ρ p = | 0 ⟩ ⟨ 0 | {\displaystyle \rho _{p}=|0\rangle \langle 0|} The Lindbladian describes the interaction of the individual with the environment: ρ

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  • Digital goods

    Digital goods

    Digital goods or e-goods are intangible goods that exist in digital form. Examples are Wikipedia articles; digital media, such as e-books, downloadable music, internet radio, internet television and streaming media; fonts, logos, photos and graphics; digital subscriptions; online ads (as purchased by the advertiser); internet coupons; electronic tickets; electronically treated documentation in many different fields; downloadable software (Digital Distribution) and mobile apps; cloud-based applications and online games; virtual goods used within the virtual economies of online games and communities; community access; workbooks; worksheets; planners; e-learning (online courses); webinars, video tutorials, blog posts; cards; patterns; website themes and templates. == Legal concerns about digital goods == Special legal concerns regarding digital goods include copyright infringement and taxation. Also the question of the ownership (versus licensed use or service only) of purely digital goods is not finally resolved. For instance, the software installers of the digital software distributor gog.com are technically independent to the account but are still subject to the EULA, where a "licensed, not sold" formulation is used. Therefore, it is not clear if the software can be legally used after a hypothetical loss of the account; a question which was also raised before in practice for the similar service Steam. In July 2012, the European Court of Justice ruled in the case UsedSoft GMbH v. Oracle International Corp. that the sale of a software product, either through a physical support or download, constituted a transfer of ownership in EU law, thus the first sale doctrine applies; the ruling thereby breaks the "licensed, not sold" legal theory, but leaves open numerous questions. Therefore, it is also permissible to resell software licenses even if the digital good has been downloaded directly from the Internet, as the first-sale doctrine applied whenever software was originally sold to a customer for an unlimited amount of time, thus prohibiting any software maker from preventing the resale of their software by any of their legitimate owners. The court requires that the previous owner must no longer be able to use the licensed software after the resale, but finds that the practical difficulties in enforcing this clause should not be an obstacle to authorizing resale, as they are also present for software which can be installed from physical supports, where the first-sale doctrine is in force. In several cases, content providers have faced criticism for revoking access to digital goods due to expired licenses or the discontinuation of a product, such as ebooks (which resulted in a lawsuit against Amazon.com, Inc.), digital video (with Sony Interactive Entertainment revoking access to purchased StudioCanal content from its now-defunct PlayStation video store; a similar move involving Warner Bros. Discovery content was averted by an updated license agreement), and video games (such as Ubisoft discontinuing and revoking access to its game The Crew without providing refunds or the ability to redownload the game) In September 2024, the U.S. state of California implemented a consumer protection law that prohibits the use of terms such as "buy" or "purchase" during transactions involving digital goods if there is no way to obtain the purchases in a manner that cannot be revoked by the seller (such as allowing it to be downloaded for permanent, offline access), and requires a disclaimer to be displayed to the customer at the time of purchase.

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  • Digital scrapbooking

    Digital scrapbooking

    Digital scrapbooking is the term for the creation of a new 2D artwork by re-combining various graphic elements. It is a form of scrapbooking that is done using a personal computer, digital or scanned photos and computer graphics software. It is a relatively new form of the traditional print scrapbooking. Recent advances in technology now enable the craft to be pursued on tablets and smart devices utilising imaging apps as well as hobby specific apps, some of which have been created specifically by brands for use with their own image products. Digital scrapbooking kits are available to purchase and download at many websites that specialize in the craft. Kits contain graphics and word-art and are usually themed and color-coordinated. They usually consist of a mix of background images and "cut out" [extracted] images containing alpha channels. Once a kit has been downloaded to the computer or device, it can then be used over and over again to make new scrapbook pages (scrapbook layouts) within the software program that one chooses to use, often in combination with the users's own family photographs, scanned keepsakes and other unique personal elements scanned on a flatbed scanner. Scanning is usually done at 300dpi, to make the resulting images suitable for print. == Licensing and Copyright == Kits are sometimes licensed differently from other forms of traditional royalty-free stock images that may be purchased per-item or in sets at online stock photography sites. Some kit packs will be wholly royalty-free, but some kit makers may restrict usage to non-commercial work only. Some may specifically forbid the use of their work in projects for commercial gain, for example greetings cards and gift tags that may be made with their kits. Licensing often varies from kit to kit, even from the same maker. Some kits include derivative works of public domain material. In contrast to stock, creators of digital scrapbooking kits often require a credit or byline to indicate that their image elements have been used in a new creation. == Uses == Some artistic individuals combine digital scrapbooking with traditional scrapbooking to create what's known as hybrid scrapbooking projects. Hybrid scrapbooking involves creating layouts on the computer using digital supplies that will then be printed and combined with traditional supplies such as buttons, ribbons and other elements. Conversely, a hybrid scrapbook project may also be created using traditional paper supplies and augmented with digital elements that have been printed and cut out specifically for use on the project. Journaling may be done within the software programs to accompany images and to create digital storybooks, or scrapbooks, which are then published in photo books via various popular print-on-demand services, printed and added to traditional scrapbooks, burned to CDs or posted on the Web. Digital Scrapbooking may also be done online by uploading photos to a specialist scrapbooking website and utilising their custom built platforms and decorative image elements to complete the projects for print to finished products, for example photo books and holiday greeting cards. == Market Size == The traditional scrapbooking market appeared to decline somewhat in the USA since 2010, probably due to the 2008 financial crisis, and the digital scrapbooking market (being potentially a much cheaper form of scrapbooking) may have increased accordingly. Both markets currently appear to have recovered lost ground and expanded since the beginning of the COVID-19 pandemic as many people sought to productively fill their time during lockdowns, quarantines and self-isolation / stay at home directions. == Digital scrapbooking software == The main software programs that are typically used are Adobe Photoshop, Adobe Photoshop Elements, paint.net (freeware), Filter Forge, Corel Paintshop Pro, and GIMP. Additionally Adobe offer the Photoshop iOS product using the same code base as the desktop version to drive the app version. == Digital scrapbooking supplies == Digital scrapbooking supplies are downloaded from the Internet and then stored on a computer or external hardrive, DVD or CD media, SD cards, or in the cloud, to be used as needed. Both paid and free digital scrapbooking supplies available from numerous designers on their blogs or in e-commerce stores either as solo designers or as part of a wide cohort of designers working cooperatively in large full service e-commerce websites. Usually designed at 300ppi image resolution, digital scrapbooking product offerings and supplies often include: Full coordinated kits containing digital background “papers”, decorative alphabets, and diverse embellishments generally containing a mixture of .JPG and .PNG files; "Quick pages", flattened files containing a completed page layout with transparent photo windows in .PNG file format; Digital templates, fully layered layouts i.e. pages that have had the composition pre-designed ready for use in an imaging program or app, fully customizable for color schemes, kit choices, photographs and other embellishments, generally supplied in either .PSD or .TIF file format; Hybrid “quick pages”, i.e. layouts that are both fully designed and fully layered for customization, generally supplied in either .PSD or .TIF file format; Adobe Photoshop actions, brushes, custom shapes, paths and styles, saved in their respective native Photoshop file formats; and Corel PaintShop Pro equivalent tools.

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