Robust Principal Component Analysis (RPCA) is a modification of the widely used statistical procedure of principal component analysis (PCA) which works well with respect to grossly corrupted observations. A number of different approaches exist for Robust PCA, including an idealized version of Robust PCA, which aims to recover a low-rank matrix L0 from highly corrupted measurements M = L0 +S0. This decomposition in low-rank and sparse matrices can be achieved by techniques such as Principal Component Pursuit method (PCP), Stable PCP, Quantized PCP, Block based PCP, and Local PCP. Then, optimization methods are used such as the Augmented Lagrange Multiplier Method (ALM), Alternating Direction Method (ADM), Fast Alternating Minimization (FAM), Iteratively Reweighted Least Squares (IRLS ) or alternating projections (AP). == Algorithms == === Non-convex method === The 2014 guaranteed algorithm for the robust PCA problem (with the input matrix being M = L + S {\displaystyle M=L+S} ) is an alternating minimization type algorithm. The computational complexity is O ( m n r 2 log 1 ϵ ) {\displaystyle O\left(mnr^{2}\log {\frac {1}{\epsilon }}\right)} where the input is the superposition of a low-rank (of rank r {\displaystyle r} ) and a sparse matrix of dimension m × n {\displaystyle m\times n} and ϵ {\displaystyle \epsilon } is the desired accuracy of the recovered solution, i.e., ‖ L ^ − L ‖ F ≤ ϵ {\displaystyle \|{\widehat {L}}-L\|_{F}\leq \epsilon } where L {\displaystyle L} is the true low-rank component and L ^ {\displaystyle {\widehat {L}}} is the estimated or recovered low-rank component. Intuitively, this algorithm performs projections of the residual onto the set of low-rank matrices (via the SVD operation) and sparse matrices (via entry-wise hard thresholding) in an alternating manner - that is, low-rank projection of the difference the input matrix and the sparse matrix obtained at a given iteration followed by sparse projection of the difference of the input matrix and the low-rank matrix obtained in the previous step, and iterating the two steps until convergence. This alternating projections algorithm is later improved by an accelerated version, coined AccAltProj. The acceleration is achieved by applying a tangent space projection before projecting the residue onto the set of low-rank matrices. This trick improves the computational complexity to O ( m n r log 1 ϵ ) {\displaystyle O\left(mnr\log {\frac {1}{\epsilon }}\right)} with a much smaller constant in front while it maintains the theoretically guaranteed linear convergence. Another fast version of accelerated alternating projections algorithm is IRCUR. It uses the structure of CUR decomposition in alternating projections framework to dramatically reduces the computational complexity of RPCA to O ( max { m , n } r 2 log ( m ) log ( n ) log 1 ϵ ) {\displaystyle O\left(\max\{m,n\}r^{2}\log(m)\log(n)\log {\frac {1}{\epsilon }}\right)} === Convex relaxation === This method consists of relaxing the rank constraint r a n k ( L ) {\displaystyle rank(L)} in the optimization problem to the nuclear norm ‖ L ‖ ∗ {\displaystyle \|L\|_{}} and the sparsity constraint ‖ S ‖ 0 {\displaystyle \|S\|_{0}} to ℓ 1 {\displaystyle \ell _{1}} -norm ‖ S ‖ 1 {\displaystyle \|S\|_{1}} . The resulting program can be solved using methods such as the method of Augmented Lagrange Multipliers. === Deep-learning augmented method === Some recent works propose RPCA algorithms with learnable/training parameters. Such a learnable/trainable algorithm can be unfolded as a deep neural network whose parameters can be learned via machine learning techniques from a given dataset or problem distribution. The learned algorithm will have superior performance on the corresponding problem distribution. == Applications == RPCA has many real life important applications particularly when the data under study can naturally be modeled as a low-rank plus a sparse contribution. Following examples are inspired by contemporary challenges in computer science, and depending on the applications, either the low-rank component or the sparse component could be the object of interest: === Video surveillance === Given a sequence of surveillance video frames, it is often required to identify the activities that stand out from the background. If we stack the video frames as columns of a matrix M, then the low-rank component L0 naturally corresponds to the stationary background and the sparse component S0 captures the moving objects in the foreground. === Face recognition === Images of a convex, Lambertian surface under varying illuminations span a low-dimensional subspace. This is one of the reasons for effectiveness of low-dimensional models for imagery data. In particular, it is easy to approximate images of a human's face by a low-dimensional subspace. To be able to correctly retrieve this subspace is crucial in many applications such as face recognition and alignment. It turns out that RPCA can be applied successfully to this problem to exactly recover the face.
WaveMaker
WaveMaker is a Java-based low-code development platform designed for building software applications and platforms. The company, WaveMaker Inc., is based in Mountain View, California. The platform is intended to assist enterprises in speeding up their application development and IT modernization initiatives through low-code capabilities. Additionally, for independent software vendors (ISVs), WaveMaker serves as a customizable low-code component that integrates into their products. The WaveMaker Platform is a licensed software platform allowing organizations to establish their own end-to-application platform-as-a-service (PaaS) for the creation and operation of custom apps. It allows developers and business users to create apps that are customizable. These applications can seamlessly consume APIs, visualize data, and automatically adapt to multi-device responsive interfaces. WaveMaker's low-code platform allows organizations to deploy applications on either public or private cloud infrastructure. Containers can be deployed on top of virtual machines or directly on bare metal. The software features a graphical user interface (GUI) console for managing IT app infrastructure, leveraging the capabilities of Docker containerization. The solution offers functionalities for automating application deployment, managing the application lifecycle, overseeing release management, and controlling deployment workflows and access permissions: Apps for web, tablet, and smartphone interfaces Enterprise technologies like Java, Hibernate, Spring, AngularJS, JQuery Docker-provided APIs and CLI Software stack packaging, container provisioning, stack and app upgrading, replication, and fault tolerance == WaveMaker Studio == WaveMaker RAD Platform is built around WaveMaker Studio, a WYSIWYG rapid development tool that allows business users to compose an application using a drag-and-drop method. WaveMaker Studio supports rapid application development (RAD) for the web, similar to what products like PowerBuilder and Lotus Notes provided for client-server computing. WaveMaker Studio allows developers to produce an application once, then automatically adjust it for a particular target platform, whether a PC, mobile phone, or tablet. Applications created using the WaveMaker Studio follow a model–view–controller architecture. WaveMaker Studio has been downloaded more than two million times. The Studio community consists of 30,000 registered users. Applications generated by WaveMaker Studio are licensed under the Apache license. Studio 8 was released on September 25, 2015. The prior version, Studio 7, has some notable development milestones. It was based on AngularJS framework, previous Studio versions (6.7, 6.6, 6.5) use the Dojo Toolkit. Some of the features WaveMaker Studio 7 include: Automatic generation of Hibernate mapping, and Hibernate queries from database schema import. Automatic creation of Enterprise Data Widgets based on schema import. Each widget can display data from a database table as a grid or edit form. Edit form implements create, update, and delete functions automatically. WYSIWYG Ajax development studio runs in a browser. Deployment to Tomcat, IBM WebSphere, Weblogic, JBoss. Mashup tool to assemble web applications based on SOAP, REST and RSS web services, Java Services and databases. Supports existing CSS, HTML and Java code. The ability to deploy a standard Java .war file. == Technologies and frameworks == WaveMaker allows users to build applications that run on "Open Systems Stack" based on the following technologies and frameworks: AngularJS, Bootstrap, NVD3, HTML, CSS, Apache Cordova, Hibernate, Spring, Spring Security, Java. The various supported integrations include: Databases: Oracle, MySQL, Microsoft SQL Server, PostgreSQL, IBM DB2, HSQLDB Authentication: LDAP, Active Directory, CAS, Custom Java Service, Database Version Control: Bitbucket (or Stash), GitHub, Apache Subversion Deployment: Amazon AWS, Microsoft Azure, WaveMaker Private Cloud (Docker containerization), IBM Web Sphere, Apache Tomcat, SpringSource tcServer, Oracle WebLogic Server, JBoss(WildFly), GlassFish App Stores: Google Play, Apple App Store, Windows Store == History == In 2003, WaveMaker was founded as ActiveGrid. Then, in 2007, it was rebranded as Wavemaker. It was acquired by VMware in 2011. In March 2013, support for the WaveMaker project was discontinued. In May 2013, Pramati Technologies acquired the assets of WaveMaker. In February 2014, Wavemaker Studio 6.7 was released, which was the last open source version of Studio. In September 2014 WaveMaker Inc. launched the WaveMaker RAD Platform, which allowed organizations to run their own application platform for building and running apps. In March 2023, WaveMaker released version 11.5, which includes enhanced low-code development capabilities and new AI-driven tools to streamline the application development process.
Universal Plug and Play
UPnP (originally Universal Plug and Play) is a set of Internet Protocol-based networking protocols that permits networked devices, such as personal computers, printers, Internet gateways, Wi-Fi access points and mobile devices, to seamlessly discover each other's presence on the network and establish functional network services. UPnP is intended primarily for residential networks without enterprise-class devices. Officially, only the abbreviations UPnP and UPnP+ are trademarked. UPnP assumes the network runs IP, and then uses HTTP on top of IP to provide device/service description, actions, data transfer and event notification. Device search requests and advertisements are supported by running HTTP on top of UDP (port 1900) using multicast (known as HTTPMU). Responses to search requests are also sent over UDP, but are instead sent using unicast (known as HTTPU). Conceptually, UPnP extends plug and play—a technology for dynamically attaching devices directly to a computer—to zero-configuration networking for residential and SOHO wireless networks. UPnP devices are plug-and-play in that, when connected to a network, they automatically establish working configurations with other devices, removing the need for users to manually configure and add devices through IP addresses. UPnP is generally regarded as unsuitable for deployment in business settings for reasons of economy, complexity, and consistency: the multicast foundation makes it chatty, consuming too many network resources on networks with a large population of devices; the simplified access controls do not map well to complex environments. == Overview == The UPnP architecture allows device-to-device networking of consumer electronics, mobile devices, personal computers, and networked home appliances. It is a distributed, open architecture protocol based on established standards such as the Internet Protocol Suite (TCP/IP), HTTP, XML, and SOAP. UPnP control points (CPs) are devices which use UPnP protocols to control UPnP controlled devices (CDs). The UPnP architecture supports zero-configuration networking. A UPnP-compatible device from any vendor can dynamically join a network, obtain an IP address, announce its name, advertise or convey its capabilities upon request, and learn about the presence and capabilities of other devices. Dynamic Host Configuration Protocol (DHCP) and Domain Name System (DNS) servers are optional and are only used if they are available on the network. Devices can disconnect from the network automatically without leaving state information. UPnP was published as a 73-part international standard ISO/IEC 29341 in December 2008. Other UPnP features include: Media and device independence UPnP technology can run on many media that support IP, including Ethernet, FireWire, Infrared (IrDA), home wiring (G.hn) and Radiofrequency (Bluetooth, Wi-Fi). No special device driver support is necessary; common network protocols are used instead. User interface (UI) control Optionally, the UPnP architecture enables devices to present a user interface through a web browser (see Presentation below). Operating system and programming language independence Any operating system and any programming language can be used to build UPnP products. UPnP stacks are available for most platforms and operating systems in both closed- and open-source forms. Programmatic control UPnP architecture also enables conventional application programmatic control. Extensibility Each UPnP product can have device-specific services layered on top of the basic architecture. In addition to combining services defined by the UPnP Forum in various ways, vendors can define their own device and service types. They can extend standard devices and services with vendor-defined actions, state variables, data structure elements, and variable values. == Protocol == UPnP uses common Internet technologies. It assumes the network must run Internet Protocol (IP) and then uses HTTP, SOAP and XML on top of IP, to provide device/service description, actions, data transfer and eventing. Device search requests and advertisements are supported by running HTTP on top of UDP using multicast (known as HTTPMU). Responses to search requests are also sent over UDP, but are instead sent using unicast (known as HTTPU). UPnP uses UDP due to its lower overhead, as it does not require confirmation of received data and retransmission of corrupt packets. HTTPU and HTTPMU specifications were initially submitted as an Internet Draft, but it expired in 2001; These specifications have since been integrated into the actual UPnP specifications. UPnP uses UDP port 1900, and all used TCP ports are derived from the SSDP alive and response messages. === Addressing === The foundation for UPnP networking is IP addressing. Each device must implement a DHCP client and search for a DHCP server when the device is first connected to the network. If no DHCP server is available, the device must assign itself an address. The process by which a UPnP device assigns itself an address is known within the UPnP Device Architecture as AutoIP. In UPnP Device Architecture Version 1.0, AutoIP is defined within the specification itself; in UPnP Device Architecture Version 1.1, AutoIP references IETF RFC 3927. If during the DHCP transaction, the device obtains a domain name, for example, through a DNS server or via DNS forwarding, the device should use that name in subsequent network operations; otherwise, the device should use its IP address. === Discovery === Once a device has established an IP address, the next step in UPnP networking is discovery. The UPnP discovery protocol is known as the Simple Service Discovery Protocol (SSDP). When a device is added to the network, SSDP allows that device to advertise its services to control points on the network. This is achieved by sending SSDP alive messages. When a control point is added to the network, SSDP enables that control point to actively search for devices of interest on the network or listen passively to SSDP alive messages from devices. The fundamental exchange is a discovery message containing a few essential details about the device or one of its services, such as its type, identifier, and a pointer (network location) to more detailed information. === Description === After a control point has discovered a device, it still knows very little about the device. For the control point to learn more about the device and its capabilities, or to interact with the device, it must retrieve the device's description from the location (URL) provided by the device in the discovery message. The UPnP Device Description is expressed in XML. It includes vendor-specific manufacturer information like the model name and number, serial number, manufacturer name, (presentation) URLs to vendor-specific websites, etc. The description also includes a list of any embedded services. For each service, the Device Description document lists the URLs for control, eventing and service description. Each service description includes a list of the commands, or actions, to which the service responds, and parameters, or arguments, for each action; the description for a service also includes a list of variables; these variables model the state of the service at run time and are described in terms of their data type, range, and event characteristics. === Control === Having retrieved a description of the device, the control point can send actions to a device's service. To do this, a control point sends a suitable control message to the control URL for the service (provided in the device description). Control messages are also expressed in XML using the Simple Object Access Protocol (SOAP). Much like function calls, the service returns any action-specific values in response to the control message. The effects of the action, if any, are modeled by changes in the variables that describe the run-time state of the service. === Event notification === Another capability of UPnP networking is event notification, or eventing. The event notification protocol defined in the UPnP Device Architecture is known as General Event Notification Architecture (GENA). A UPnP description for a service includes a list of actions the service responds to and a list of variables that model the state of the service at runtime. The service publishes updates when these variables change, and a control point may subscribe to receive this information. The service publishes updates by sending event messages. Event messages contain the names of one or more state variables and their current values. These messages are also expressed in XML. A special initial event message is sent when a control point first subscribes; this event message contains the names and values for all evented variables and allows the subscriber to initialize its model of the state of the service. To support scenarios with multiple control points, eventing is designed to keep all control points equally informed
Fifth Estate
The Fifth Estate is a socio-cultural reference to groupings of outlier viewpoints in contemporary society, and is most associated with bloggers, journalists publishing in non-mainstream media outlets, and online social networks. The "Fifth" Estate extends the sequence of the three classical estates (clergy (first), nobility (second), commoners (third)) and the preceding Fourth Estate, essentially the common press. The use of "fifth estate" dates to the 1960s counterculture, and in particular the influential Fifth Estate, an underground newspaper first published in Detroit in 1965. Web-based technologies have enhanced the scope and power of the Fifth Estate far beyond the modest and boutique conditions of its beginnings. Nimmo and Combs asserted in 1992 that political pundits constitute a Fifth Estate. Media researcher Stephen D. Cooper argued in 2006 that bloggers are the Fifth Estate. In 2009, William Dutton argued that the Fifth Estate is not just the blogging community, nor an extension of the media, but "networked individuals" enabled by the Internet, e.g. social media, in ways that can hold the other estates accountable.
List of video games using NFC
This is a list of video games that use near field communication (NFC) technology. Currently, games have leveraged NFC in unlocking additional features through payment. This takes the form of a direct transaction over NFC or by purchasing a physical item, which signals to the platform that a certain set of features has been purchased (e.g. Skylanders). This list catalogues gaming NFC platforms by device. == Mobile == === Android === Gun Bros. Near Field Ninja NFC Cards Skylanders, with an NFC base. The Haunted House: Soul Fighters, with an NFC base. === iOS === ==== As item-triggered game enhancement ==== Skylanders, with an NFC base. ==== As payment ==== In-App Purchases Here, games that leverage Apple's In-App Purchase framework use information stored in the NFC Secure Element to process the purchase through Apple Pay. While an NFC radio is not used here, the NFC protocol is used nonetheless. == Console == === Nintendo Wii, Wii U, Switch, Switch 2, 3DS and 2DS === ==== As item-triggered game enhancement ==== Pokémon Rumble U NFC Figure Amiibo, built into Nintendo consoles since 2014. Works with Wii U, New Nintendo 3DS/3DS XL, New Nintendo 2DS XL, Nintendo Switch, Nintendo Switch 2 and older Nintendo 3DS/Nintendo 2DS systems via a peripheral device. Disney Infinity, with an NFC base. Works with Wii, Nintendo 3DS, Nintendo 2DS and Wii U. Lego Dimensions, with an NFC base. Works with Wii U. Skylanders, with an NFC base. Works with Wii, Nintendo 3DS, Nintendo 2DS and Wii U. The Nintendo Switch version of Skylanders: Imaginators uses the NFC built into the game controller, it is also has full backward compatibility with Nintendo Switch 2. Some functionalities are missing compared to the other versions. ==== As payment ==== The Wii U GamePad controller, Joy-Con R, Joy-Con 2 R, Nintendo Switch Pro Controller and Nintendo Switch 2 Pro Controller can read information from an NFC data source. === PlayStation === Disney Infinity, with an NFC base. Works with PlayStation 3, PlayStation Vita, PlayStation 4 and PlayStation 5. Lego Dimensions, with an NFC base. Works with PlayStation 3, PlayStation 4 and PlayStation 5. Skylanders, with an NFC base. Works with PlayStation 3, PlayStation 4 and PlayStation 5. === Xbox === While NFC bases are normally interoperable between all platforms, the Xbox 360, Xbox One and Xbox Series X require specific bases that are compatible only with the respective platform. Disney Infinity, with an NFC base. Lego Dimensions, with an NFC base. Skylanders, with an NFC base.
Smart speaker industry in South Korea
Smart speakers, or AI speakers, have been developed by multiple domestic electronics and telecommunications firms in South Korea. Since their introduction to the local market in 2016, they have been used by millions of people in the country. == Brands == === Google === In September 2018, Google Home (including the Google Home Mini) launched in South Korea. Running Google Assistant, it featured simultaneous recognition of two languages among a total of seven, including Korean. At launch, it could play music from Bugs!, in addition to YouTube. === Kakao === In November 2017, Kakao launched the Kakao Mini, featuring integrated KakaoTalk functionality. === KT === KT launched the GiGA Genie smart speaker in January 2017, using a Harman Kardon speaker. In November 2017, KT announced GiGA Genie LTE, a portable AI speaker with LTE support. They also released a mini speaker called GiGA Genie Buddy. In 2018, KT created a special version of GiGa Genie with a screen for use in hotels. On 29 April 2019, KT announced the GiGA Genie Table TV, a consumer-oriented smart speaker with a display. It featured paid TV access through Wi-Fi. Based on usage data from the hotel model, KT decided not to add a touchscreen. The Table TV also featured a limited-access "personalized-text-to-speech technology" which could use parents' voice recording inputs to read children books. In February 2022, KT began rolling out Amazon Alexa integration into its speakers for English support. === Naver === In August 2017, Naver announced the Wave smart speaker, operating on Clova. In October 2017, Naver launched the Friends smart speaker, which were designed based on Line characters. ==== LG Uplus ==== In December 2017, LG Uplus launched the Friends+ speaker with Naver, operating on U+ Home AI. === Samsung === In August 2018, Samsung announced the Samsung Galaxy Home in partnership with Spotify. The original size was delayed, while the Galaxy Home Mini appeared briefly as a bonus for Samsung Galaxy S20 preorders in South Korea in February 2020. === SK Telecom === SK Telecom launched the Nugu smart speaker in September 2016, using an Astell & Kern audio system. In August 2017, SKT released a portable speaker named Nugu mini. In July 2018, SKT launched the Nugu Candle, featuring expanded mood lighting. The first-generation Nugu was subsequently discontinued. On 18 April 2019, SKT released the NUGU Nemo AI, which featured a display and JBL stereo speaker. In August 2019, SKT collaborated with SM Entertainment, incorporating functions related to the agency's artists into Nugu. In January 2022, SKT showcased the NUGU Candle SE, introducing Alexa support. == Usage == In 2018, approximately 3 million people in South Korea used smart speakers. According to data from KT in 2018, the most common commands to its speakers were for controlling televisions. Based on a broader survey in 2017, music was selected as the most frequent use case. By 2018, smart speaker companies were partnering with reading and other education services, adding potential use-cases for children. By 2022, smart speakers were being utilized by the South Korean government. SKT, in partnership with 70 regional governments, distributed smart speakers to 12,000 senior citizens living alone. The government paid for monthly subscriptions to help seniors stay mentally engaged. Naver made an agreement with the Seoul Metropolitan Government to provide Clova CareCall, an automated health checkup program to hundreds of senior citizens living alone. KT's AI care service included an emergency dispatch call function and medication notifications. == Criticism == === Communication === In a survey of 300 users in 2017, approximately half reported having some type of communication issue with their smart speakers. === Privacy === South Korean smart speakers sparked privacy concerns when they were found to be collecting and documenting user audio data in 2019. The speaker companies responded that only a minority of data was collected and that it was anonymized. They stated that such recordings were collected for performance improvements.
Comparison of JavaScript-based web frameworks
This is a comparison of web frameworks for front-end web development that are reliant on JavaScript code for their behavior. == General information == == High-level framework comparison == 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. == Features == == Browser support ==