Rake is a software task management and a build automation tool created by Jim Weirich. It allows the user to specify tasks and to describe dependencies as well as to group tasks into namespaces. It is similar to SCons and Make. Rake was written in Ruby and has been part of the standard library of Ruby since version 1.9. == Examples == The tasks that should be executed need to be defined in a configuration file called Rakefile. A Rakefile has no special syntax and contains executable Ruby code. === Tasks === The basic unit in Rake is the task. A task has a name and an action block, that defines its functionality. The following code defines a task called greet that will output the text "Hello, Rake!" to the console. When defining a task, you can optionally add dependencies, that is one task can depend on the successful completion of another task. Calling the "seed" task from the following example will first execute the "migrate" task and only then proceed with the execution of the "seed" task.Tasks can also be made more versatile by accepting arguments. For example, the "generate_report" task will take a date as argument. If no argument is supplied the current date is used.A special type of task is the file task, which can be used to specify file creation tasks. The following task, for example, is given two object files, i.e. "a.o" and "b.o", to create an executable program.Another useful tool is the directory convenience method, that can be used to create directories upon demand. === Rules === When a file is named as a prerequisite but it does not have a file task defined for it, Rake will attempt to synthesize a task by looking at a list of rules supplied in the Rakefile. For example, suppose we were trying to invoke task "mycode.o" with no tasks defined for it. If the Rakefile has a rule that looks like this: This rule will synthesize any task that ends in ".o". It has as a prerequisite that a source file with an extension of ".c" must exist. If Rake is able to find a file named "mycode.c", it will automatically create a task that builds "mycode.o" from "mycode.c". If the file "mycode.c" does not exist, Rake will attempt to recursively synthesize a rule for it. When a task is synthesized from a rule, the source attribute of the task is set to the matching source file. This allows users to write rules with actions that reference the source file. === Advanced rules === Any regular expression may be used as the rule pattern. Additionally, a proc may be used to calculate the name of the source file. This allows for complex patterns and sources. The following rule is equivalent to the example above: NOTE: Because of a quirk in Ruby syntax, parentheses are required around a rule when the first argument is a regular expression. The following rule might be used for Java files: === Namespaces === To better organize big Rakefiles, tasks can be grouped into namespaces. Below is an example of a simple Rake recipe:
Service-oriented software engineering
Service-oriented software engineering (SOSE), also referred to as service engineering, is a software engineering methodology focused on the development of software systems by composition of reusable services (service-orientation) often provided by other service providers. Since it involves composition, it shares many characteristics of component-based software engineering, the composition of software systems from reusable components, but it adds the ability to dynamically locate necessary services at run-time. These services may be provided by others as web services, but the essential element is the dynamic nature of the connection between the service users and the service providers. == Service-oriented interaction pattern == There are three types of actors in a service-oriented interaction: service providers, service users and service registries. They participate in a dynamic collaboration which can vary from time to time. Service providers are software services that publish their capabilities and availability with service registries. Service users are software systems (which may be services themselves) that accomplish some task through the use of services provided by service providers. Service users use service registries to discover and locate the service providers they can use. This discovery and location occurs dynamically when the service user requests them from a service registry.
Cloud9 (service provider)
Cloud9 is a mobile network operator focussed on providing mobile subscriptions over the air to programmable SIM cards, SoftSIMs and eSIMs. Their service is used in both smartphones and IoT devices. The company is privately held with headquarters in the United Kingdom. == History == Cloud9, originally owned by Wire9 Telecom Plc, funded and established by investor and telecom specialist, Lee Jones, before being sold for an undisclosed sum by Jones to billionaire Romain Zaleski. It established in the UK, Gibraltar, and Isle of Man as a domestic Mobile Network Operator. Cloud9 obtained spectrum licenses in the Isle of Man in 2007 and Gibraltar in 2010. Around 2011, Cloud9 decided to focus on supplying global SIM cards to save roaming charges. The Gibraltar spectrum licence was sold to another company. The business relocated its core network to Telehouse in London and became a subsidiary of BlueMango Technologies Ltd. Later the company was acquired by Wireless Logic Ltd. In 2013, Cloud9 acquired the IPR of Zynetix Ltd. Through this acquisition, the company achieved sales as an MVNE. In 2014, the company was voted as a Red Herring Top 100 Europe finalist. == Features == Cloud9 has shipped several million 'Travel SIMs'; all SIM cards have been branded with the logo of these resellers. Additionally, the company provides the digital signatures ('profiles' or 'IMSIs') that provide a SIM card with the ability to register with a network and function. These can be provisioned over the air to dynamic SIM cards such as programmable removable UICCs, SoftSIMs and eSIMs. They are members of the GSM Association and are involved in the GSMA remote SIM provisioning standard for eSIMs that will be released soon. The Cloud9 core network also supports 4G (HSS/PDG). Its Mobile Country Code is 234 and its Mobile Network Code is 18. TADIG code is GBRC9. The company has been allocated the following UK number ranges by Ofcom: 4478722, 4477000, 4474409, 4479782, 4479783 and 4475588 The core network is hosted on Cloud9 servers at Telehouse near Canary Wharf in London. Additional components are hosted in Amazon Web Services facilities around the world in order to minimise latency and provide scalability.
UCSD Pascal
UCSD Pascal is a Pascal programming language system that runs on the UCSD p-System, a portable, highly machine-independent operating system. UCSD Pascal was first released in 1977. It was developed at the University of California, San Diego (UCSD). == The p-System == In 1977, the University of California, San Diego (UCSD) Institute for Information Systems developed UCSD Pascal to provide students with a common environment that could run on any of the then available microcomputers as well as campus DEC PDP-11 minicomputers. The operating system became known as UCSD p-System. There were three operating systems that IBM offered for its original IBM PC: the UCSD p-System, CP/M-86, and IBM PC DOS. Vendor SofTech Microsystems emphasized p-System's application portability, with virtual machines for 20 CPUs as of the IBM PC's release. It predicted that users would be able to use applications they purchased on future computers running p-System; advertisements called it "the Universal Operating System". PC Magazine denounced UCSD p-System on the IBM PC, stating in a review of Context MBA, written in the language, that it "simply does not produce good code". The p-System did not sell very well for the IBM PC, because of a lack of applications and because it was more expensive than the other choices. Previously, IBM had offered the UCSD p-System as an option for IBM Displaywriter, an 8086-based dedicated word processing machine. (The Displaywriter's native operating system had been developed completely internally and was not opened for end-user programming.) Notable extensions to standard Pascal include separately compilable Units and a String type. Some intrinsics were provided to accelerate string processing (e.g. scanning in an array for a particular search pattern); other language extensions were provided to allow the UCSD p-System to be self-compiling and self-hosted. UCSD Pascal was based on a p-code machine architecture. Its contribution to these early virtual machines was to extend p-code away from its roots as a compiler intermediate language into a full execution environment. The UCSD Pascal p-Machine was optimized for the new small microcomputers with addressing restricted to 16-bit (only 64 KB of memory). James Gosling cites UCSD Pascal as a key influence (along with the Smalltalk virtual machine) on the design of the Java virtual machine. UCSD p-System achieved machine independence by defining a virtual machine, called the p-Machine (or pseudo-machine, which many users began to call the "Pascal-machine" like the OS—although UCSD documentation always used "pseudo-machine") with its own instruction set called p-code (or pseudo-code). Urs Ammann, a student of Niklaus Wirth, originally presented a p-code in his PhD thesis, from which the UCSD implementation was derived, the Zurich Pascal-P implementation. The UCSD implementation changed the Zurich implementation to be "byte oriented". The UCSD p-code was optimized for execution of the Pascal programming language. Each hardware platform then only needed a p-code interpreter program written for it to port the entire p-System and all the tools to run on it. Later versions also included additional languages that compiled to the p-code base. For example, Apple Computer offered a Fortran Compiler (written by Silicon Valley Software, Sunnyvale California) producing p-code that ran on the Apple version of the p-system. Later, TeleSoft (also located in San Diego) offered an early Ada development environment that used p-code and was therefore able to run on a number of hardware platforms including the Motorola 68000, the System/370, and the Pascal MicroEngine. UCSD p-System shares some concepts with the later Java platform. Both use a virtual machine to hide operating system and hardware differences, and both use programs written to that virtual machine to provide cross-platform support. Likewise both systems allow the virtual machine to be used either as the complete operating system of the target computer or to run in a "box" under another operating system. The UCSD Pascal compiler was distributed as part of a portable operating system, the p-System. == History == UCSD p-System began around 1974 as the idea of UCSD's Kenneth Bowles, who believed that the number of new computing platforms coming out at the time would make it difficult for new programming languages to gain acceptance. He based UCSD Pascal on the Pascal-P2 release of the portable compiler from Zurich. He was particularly interested in Pascal as a language to teach programming. UCSD introduced two features that were important improvements on the original Pascal: variable length strings, and "units" of independently compiled code (an idea included into the then-evolving Ada (programming language)). Niklaus Wirth credits the p-System, and UCSD Pascal in particular, with popularizing Pascal. It was not until the release of Turbo Pascal that UCSD's version started to slip from first place among Pascal users. The Pascal dialect of UCSD Pascal came from the subset of Pascal implemented in Pascal-P2, which was not designed to be a full implementation of the language, but rather "the minimum subset that would self-compile", to fit its function as a bootstrap kit for Pascal compilers. UCSD added strings from BASIC, and several other implementation dependent features. Although UCSD Pascal later obtained many of the other features of the full Pascal language, the Pascal-P2 subset persisted in other dialects, notably Borland Pascal, which copied much of the UCSD dialect. == Versions == There were four versions of UCSD p-code engine, each with several revisions of the p-System and UCSD Pascal. A revision of the p-code engine (i.e., the p-Machine) meant a change to the p-code language, and therefore compiled code is not portable between different p-Machine versions. Each revision was represented with a leading Roman Numeral, while operating system revisions were enumerated as the "dot" number following the p-code Roman Numeral. For example, II.3 represented the third revision of the p-System running on the second revision of the p-Machine. === Version I === Original version, never officially distributed outside of the University of California, San Diego. However, the Pascal sources for both Versions I.3 and I.5 were freely exchanged between interested users. Specifically, the patch revision I.5a was known to be one of the most stable. === Version II === Widely distributed, available on many early microcomputers. Numerous versions included Apple II ultimately Apple Pascal, DEC PDP-11, Intel 8080, Zilog Z80, and MOS 6502 based machines, Motorola 68000 and the IBM PC (Version II on the PC was restricted to one 64K code segment and one 64K stack/heap data segment; Version IV removed the code segment limit but cost a lot more). Project members from this era include Dr Kenneth L Bowles, Mark Allen, Richard Gleaves, Richard Kaufmann, Pete Lawrence, Joel McCormack, Mark Overgaard, Keith Shillington, Roger Sumner, and John Van Zandt. === Version III === Custom version written for Western Digital to run on their Pascal MicroEngine microcomputer. Included support for parallel processes for the first time. === Version IV === Commercial version, developed and sold by SofTech. Based on Version II; did not include changes from Version III. Did not sell well due to combination of their pricing structure, performance problems due to p-code interpreter, and competition with native operating systems (on top of which it often ran). After SofTech dropped the product, it was picked up by Pecan Systems, a relatively small company formed of p-System users and fans. Sales revived somewhat, due mostly to Pecan's reasonable pricing structure, but the p-System and UCSD Pascal gradually lost the market to native operating systems and compilers. Available for the TI-99/4A equipped with p-code card, Commodore CBM 8096, Sage II/IV, HP 9000, and BBC Micro with 6502 second processor. == Further use == The Corvus Systems computer used UCSD Pascal for all its user software. The "innovative concept" of the Constellation OS was to run Pascal (interpretively or compiled) and include all common software in the manual, so users could modify as needed.
Spintronics
Spintronics (a portmanteau of spin transport electronics), also known as spin electronics, is the study of the intrinsic spin of the electron and its associated magnetic moment, in addition to its fundamental electronic charge, in solid-state devices. The field of spintronics concerns spin-charge coupling in metallic systems. The analogous effects in insulators fall into the field of multiferroics. Spintronics fundamentally differs from traditional electronics in that, in addition to charge state, electron spins are used as a further degree of freedom, with implications in the efficiency of data storage and transfer. Spintronic systems are most often realised in dilute magnetic semiconductors (DMS) and Heusler alloys and are of particular interest in the field of quantum computing, such as atomtronics computation. == History == Spintronics emerged from discoveries in the 1980s concerning spin-dependent electron transport phenomena in solid-state devices. This includes the observation of spin-polarized electron injection from a ferromagnetic metal to a normal metal by Johnson and Silsbee (1985) and the discovery of giant magnetoresistance independently by Albert Fert et al. and Peter Grünberg et al. (1988). The origin of spintronics can be traced to the ferromagnet/superconductor tunneling experiments pioneered by Meservey and Tedrow and initial experiments on magnetic tunnel junctions by Julliere in the 1970s. The use of semiconductors for spintronics began with the theoretical proposal of a spin field-effect-transistor by Datta and Das in 1990 and of the electric dipole spin resonance by Rashba in 1960. In 2012, persistent spin helices of synchronized electrons were made to persist for more than a nanosecond, a 30-fold increase over earlier efforts, and longer than the duration of a modern processor clock cycle. In 2025, at 60 K (−213.2 °C; −351.7 °F) crystalline nickel(II) iodide (NiI2) was reported to exhibit p-wave magnetism, in which the spins of nickel atoms became arranged in a spiral pattern in two orientations. The orientations can be switched via a small electrical current. Applied in digital devices, this spintronics behavior requires far less current than the conventional charge-based electronics that powers devices such as computers and phones. == Theory == The spin of the electron is an intrinsic angular momentum that is separate from the angular momentum due to its orbital motion. The magnitude of the projection of the electron's spin along an arbitrary axis is 1 2 ℏ {\displaystyle {\tfrac {1}{2}}\hbar } , implying that the electron acts as a fermion by the spin-statistics theorem. Like orbital angular momentum, the spin has an associated magnetic moment, the magnitude of which is expressed as μ = 3 2 q m e ℏ {\displaystyle \mu ={\tfrac {\sqrt {3}}{2}}{\frac {q}{m_{e}}}\hbar } . In a solid, the spins of many electrons can act together to affect the magnetic and electronic properties of a material, for example endowing it with a permanent magnetic moment as in a ferromagnet. In many materials, electron spins are equally present in both the up and the down state, and no transport properties are dependent on spin. A spintronic device requires generation or manipulation of a spin-polarized population of electrons, resulting in an excess of spin up or spin down electrons. The polarization of any spin dependent property X can be written as P X = X ↑ − X ↓ X ↑ + X ↓ {\displaystyle P_{X}={\frac {X_{\uparrow }-X_{\downarrow }}{X_{\uparrow }+X_{\downarrow }}}} . A net spin polarization can be achieved either through creating an equilibrium energy split between spin up and spin down. Methods include putting a material in a large magnetic field (Zeeman effect), the exchange energy present in a ferromagnet or forcing the system out of equilibrium. The period of time that such a non-equilibrium population can be maintained is known as the spin lifetime, τ {\displaystyle \tau } . In a diffusive conductor, a spin diffusion length λ {\displaystyle \lambda } can be defined as the distance over which a non-equilibrium spin population can propagate. Spin lifetimes of conduction electrons in metals are relatively short (typically less than 1 nanosecond). An important research area is devoted to extending this lifetime to technologically relevant timescales. The mechanisms of decay for a spin polarized population can be broadly classified as spin-flip scattering and spin dephasing. Spin-flip scattering is a process inside a solid that does not conserve spin, and can therefore switch an incoming spin up state into an outgoing spin down state. Spin dephasing is the process wherein a population of electrons with a common spin state becomes less polarized over time due to different rates of electron spin precession. In confined structures, spin dephasing can be suppressed, leading to spin lifetimes of milliseconds in semiconductor quantum dots at low temperatures. Superconductors can enhance central effects in spintronics such as magnetoresistance effects, spin lifetimes and dissipationless spin-currents. The simplest method of generating a spin-polarised current in a metal is to pass the current through a ferromagnetic material. The most common applications of this effect involve giant magnetoresistance (GMR) devices. A typical GMR device consists of at least two layers of ferromagnetic materials separated by a spacer layer. When the two magnetization vectors of the ferromagnetic layers are aligned, the electrical resistance will be lower (so a higher current flows at constant voltage) than if the ferromagnetic layers are anti-aligned. This constitutes a magnetic field sensor. Two variants of GMR have been applied in devices: Current-in-plane (CIP), where the electric current flows parallel to the layers and, Current-perpendicular-to-plane (CPP), where the electric current flows in a direction perpendicular to the layers. Other metal-based spintronics devices: Tunnel magnetoresistance (TMR), where CPP transport is achieved by using quantum-mechanical tunneling of electrons through a thin insulator separating ferromagnetic layers. Spin-transfer torque, where a current of spin-polarized electrons is used to control the magnetization direction of ferromagnetic electrodes in the device. Spin-wave logic devices carry information in the phase. Interference and spin-wave scattering can perform logic operations. == Device types == === Spintronic-logic === Non-volatile spin-logic devices to enable scaling are being extensively studied. Spin-transfer, torque-based logic devices that use spins and magnets for information processing have been proposed. These devices are part of the ITRS exploratory road map. Logic-in memory applications are already in the development stage. A 2017 review article can be found in Materials Today. A generalized circuit theory for spintronic integrated circuits has been proposed so that the physics of spin transport can be utilized by SPICE developers and subsequently by circuit and system designers for the exploration of spintronics for "beyond CMOS computing". === Semiconductor === Doped semiconductor materials display dilute ferromagnetism. In recent years, dilute magnetic oxides (DMOs) including ZnO based DMOs and TiO2-based DMOs have been the subject of numerous experimental and computational investigations. N`0 sources (like manganese-doped gallium arsenide (Ga,Mn)As), increase the interface resistance with a tunnel barrier, or using hot-electron injection. Spin detection in semiconductors has been addressed with multiple techniques: Faraday/Kerr rotation of transmitted/reflected photons Circular polarization analysis of electroluminescence Nonlocal spin valve (adapted from Johnson and Silsbee's work with metals) Ballistic spin filtering The latter technique was used to overcome the lack of spin-orbit interaction and materials issues to achieve spin transport in silicon. Because external magnetic fields (and stray fields from magnetic contacts) can cause large Hall effects and magnetoresistance in semiconductors (which mimic spin-valve effects), the only conclusive evidence of spin transport in semiconductors is demonstration of spin precession and dephasing in a magnetic field non-collinear to the injected spin orientation, called the Hanle effect. === Storage media === Antiferromagnetic storage media have been studied as an alternative to ferromagnetism, especially since with antiferromagnetic material the bits can be stored as well as with ferromagnetic material. Instead of the usual definition 0 ↔ 'magnetisation upwards', 1 ↔ 'magnetisation downwards', the states can be, e.g., 0 ↔ 'vertically alternating spin configuration' and 1 ↔ 'horizontally-alternating spin configuration'.). The main advantages of antiferromagnetic material are: insensitivity to data-damaging perturbations by stray fields due to zero net external magnetization; no effect on near particles, implying that antiferromagnetic device elements wo
Outline of automation
The following outline is provided as an overview of and topical guide to automation: Automation – use of control systems and information technologies to reduce the need for human work in the production of goods and services. In the scope of industrialization, automation is a step beyond mechanization. == Essence of automation == Control system – a device, or set of devices to manage, command, direct or regulate the behavior of other devices or systems. Industrial control system (ICS) – encompasses several types of control systems used in industrial production, including supervisory control and data acquisition (SCADA) systems, distributed control systems (DCS), and other smaller control system configurations such as skid-mounted programmable logic controllers (PLC) often found in industrial sectors and critical infrastructures. Industrialization – period of social and economic change that transforms a human group from an agrarian society into an industrial one. Numerical control (NC) – refers to the automation of machine tools that are operated by abstractly programmed commands encoded on a storage medium, as opposed to controlled manually via handwheels or levers, or mechanically automated via cams alone. Robotics – the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots and computer systems for their control, sensory feedback, and information processing. == Branches of automation == === General purpose === Autonomous automation – autonomous software agents to adapt the controllers of computer controlled industrial machinery and processes Banking automation Broadcast automation Building automation – advanced functionality provided by the control system of a building. A building automation system (BAS) is an example of a distributed control system. Home automation – control system of a home. Office automation – the varied computer machinery and software used to digitally create, collect, store, manipulate, and relay office information needed for accomplishing basic tasks such as business process automation and robotic process automation. Console automation Database automation Integrated library system Laboratory automation === Specific purpose === Automated attendant Automated guided vehicle Autonomous mobile robot Automated highway system Automated pool cleaner Automated teller machine Automatic painting (robotic) Pop music automation Remotely operated vehicle Robotic lawn mower Telephone switchboard Vending machine == Fields contributing to automation == Cybernetics – the interdisciplinary study of the structure of regulatory systems. Cognitive science – interdisciplinary scientific study of the mind and its processes. It examines what cognition is, what it does and how it works. Robotics – the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots and computer systems for their control, sensory feedback, and information processing. == History of automation == History of mass production – Prerequisites of mass production were interchangeable parts, machine tools and power, especially in the form of electricity. Mass production was popularized in the 1910s and 1920s by Henry Ford's Ford Motor Company, which introduced electric motors to the then-well-known technique of chain or sequential production. History of home automation == Automated machines == Machine to Machine OLE for process control (OPC) Process control – a statistics and engineering discipline that deals with architectures, mechanisms and algorithms for maintaining the output of a specific process within a desired range. Run Book Automation (RBA) Robot – a mechanical or virtual intelligent agent that can perform tasks automatically or with guidance, typically by remote control. == Automated machine components == Artificial intelligence – the intelligence of machines and the branch of computer science that aims to create it. Friendly artificial intelligence – an artificial intelligence that has a positive rather than negative effect on humanity, and the field of knowledge required to build such an artificial intelligence. === Automation tools === Artificial neural network (ANN) – mathematical model or computational model that is inspired by the structure or functional aspects of biological neural networks. Human machine interface (HMI) – operator level local control panel that monitors field devices Laboratory information management system (LIMS) – software package that offers a set of key features that support a modern laboratory's operations. Industrial control system – encompasses several types of control systems used in industrial production, including supervisory control and data acquisition (SCADA) systems, distributed control systems (DCS), and other smaller control system configurations such as skid-mounted programmable logic controllers (PLC) often found in the industrial sectors and critical infrastructures. Distributed control system (DCS) – control system usually of a manufacturing system, process or any kind of dynamic system, in which the controller elements are not central in location (like the brain) but are distributed throughout the system with each component sub-system controlled by one or more controllers. Manufacturing execution system (MES) – system that manages manufacturing operations in a factory, including management of resources, scheduling production processes, dispatching production orders, execution of production orders, etc. Programmable automation controller (PAC) – digital computer used for automation of electromechanical processes, such as control of machinery on factory assembly lines, amusement rides, or light fixtures. Programmable logic controller (PLC)A Programmable Logic Controller, PLC or Programmable Controller is a digital computer used for automation of electromechanical processes, such as control of machinery on factory assembly lines, amusement rides, or light fixtures. The abbreviation "PLC" and the term "Programmable Logic Controller" are registered trademarks of the Allen-Bradley Company (Rockwell Automation). PLCs are used in many industries and machines. Unlike general-purpose computers, the PLC is designed for multiple inputs and output arrangements, extended temperature ranges, immunity to electrical noise, and resistance to vibration and impact. Programs to control machine operation are typically stored in battery-backed-up or non-volatile memory. A PLC is an example of a hard real time system since output results must be produced in response to input conditions within a limited time, otherwise unintended operation will result. Supervisory control and data acquisition (SCADA) – generally refers to industrial control systems (ICS): computer systems that monitor and control industrial, infrastructure, or facility-based processes, as described below: Industrial processes include those of manufacturing, production, power generation, fabrication, and refining, and may run in continuous, batch, repetitive, or discrete modes. Simulation § Engineering Technology simulation or Process simulation == Social movements == Automation-related social movement – a movement that advocates semi- or fully automatic systems to provide for human needs globally. For example, automation of farming and food distribution throughout the world so that no one will go hungry. One goal is to automate all mundane labor, to free humans to engage in more creative activities (or less work). The Technocracy movement – social movement active from the Great Depression (1930s) to date that proposes replacing politicians and business people with scientists and engineers who have the technical expertise to manage the economy. The Zeitgeist Movement – movement advocating the replacement of the market economy with an economy in which all resources are equitably, commonly and sustainably shared. == Automation in the future == Android – a robot or synthetic organism designed to look and act like a human, and with a body having a flesh-like resemblance Technological singularity – the hypothetical future emergence of greater-than-human intelligence through technological means Semi-automation – using a centralized computer controller to orchestrate the activities of man and machine. == Automation-related publications == IEEE Spectrum – the flagship publication of the Institute of Electrical and Electronics Engineers (IEEE), explores the development, applications and implications of new technologies, and provides a forum for understanding, discussion and leadership in these areas. IEEE Transactions on Information Theory – peer-reviewed scientific journal published by the Institute of Electrical and Electronics Engineers (IEEE), focused on the study of information theory, the mathematics of communications, including computer communications, robotics communications, etc. IEEE Transactions on Control S
Blend4Web
Blend4Web is a free and open source framework for creating and displaying interactive 3D computer graphics in web browsers. == Overview == The Blend4Web framework leverages Blender to edit 3D scenes. Content rendering relies on WebGL, Web Audio, WebVR, and other web standards, without the use of plug-ins. It is dual-licensed. The framework is distributed under the free and open source GPLv3 and, a non-free license - with the source code being hosted on GitHub. A 3D scene can be prepared in Blender and then exported as a pair of JSON and binary files to load in a web application. It can also be exported as a single, self-contained HTML file, in which exported data, the web player GUI, and the engine itself are packed. The HTML option is considered to be the simplest way. The resulting file, which has a minimum size of 1 MB, can be embedded in a web page using a standard iframe HTML element. Blend4Web-powered web applications can be deployed on social networking websites such as Facebook. The Blend4Web toolchain consists of JavaScript libraries, the Blender add-on, and a set of tools for tweaking 3D scene parameters, debugging, and optimization. Developed by Moscow-based company Triumph in 2010, Blend4Web was publicly released on March 28, 2014. At the end of 2017, the project founders Yuri and Alex Kovelenov quit Triumph to start the development of a new WebGL framework Verge3D. In October 2019, an "Absolutely new Blend4Web" was announced, planned to make developing 3D apps easier and to add a new marketplace where people can offer their 3D models. == Features == The framework has a number of components typically found in game engines, including a positional audio system, physics engine (a fork of Bullet ported to JavaScript), animation system, and an abstraction layer for game logic programming. Up to 8 different types of animations can be assigned to a single object, including skeletal and per-vertex animation. The speed and the direction of animation (forward/backward play), as well as particle system parameters (size, initial velocity, and count), can be changed through the API. Among other supported features are: scene data dynamic loading and unloading, subsurface scattering simulation, and image-based lighting. Some out-of-box options exist for rendering extended outdoor environments, including foliage-wind interaction, water, atmosphere, and sunlight simulation. One example demonstrating these effects is "The Farm" tech demo, which also features multiple animated NPCs and the ability to walk, interact with objects and drive a vehicle in first-person mode. Being based on the cross-browser WebGL API, Blend4Web runs in the majority of web browsers, including mobile ones. There are some caveats for browsers with experimental WebGL support, such as Internet Explorer. There are also applications developed to run on Tizen-powered devices such as the Samsung Gear S2 smartwatch. Other features include: draw call batching, hidden surface determination, threaded physics simulation and ocean simulation. In version 14.09, Blend4Web introduced the possibility of adding interactivity to 3D scenes using a visual programming tool. The tool is reminiscent of the BGE's logic editor as it uses logic blocks that are placed inside Blender. It plays back animation tracks authored by an artist when the user interacts with predefined 3D objects. Since version 15.03, Blend4Web has supported attaching HTML elements (such as information windows) to 3D objects ("annotations") and copying objects in run time ("instancing"). The following post-processing effects are supported: glow, bloom, depth of field, crepuscular rays, motion blur, and screen space ambient occlusion. == Virtual reality and augmented reality == Virtual reality devices have been supported since the end of 2015. Specifically, Oculus Rift head-mounted display works over experimental WebVR API. The software also now includes preliminary support for gamepads, based on the Gamepad API. In 2017, the option to author augmented reality content was added. The system is based on the open-source tracking library ARToolKit and uses the WebRTC protocols. Starting from version 17.08, finger tracking is supported through the Leap Motion device. == Blender integration == The Blender add-on is written in Python and C and can be compiled for the Linux x86/x64, OS X x64, and MS Windows x86/x64 platforms. A Blend4Web-specific profile can be activated in the add-on settings. When switching to this profile, the Blender interface changes so that it only reveals settings relevant to Blend4Web. Blend4Web supports a set of Blender-specific features such as the node material editor (a tool for visual shader programming) and the particle system. There is basic support for Blender's non-linear animation (NLA) editor for creating simple scenarios. Blend4Web is based on Blender's real-time GLSL rendering engine, which users are recommended to use in order to enable WYSIWYG editing. == Notable uses == NASA developed an interactive web application called Experience Curiosity to celebrate the 3rd anniversary of the Curiosity rover landing on Mars. This Blend4Web-based app makes it possible to operate the rover, control its cameras and the robotic arm, and reproduce some of the prominent events of the Mars Science Laboratory mission. The application got presented at the beginning of the WebGL section at SIGGRAPH 2015. Experience Curiosity was ported to Verge3D for Blender in 2018 with several performance improvements and bug fixes. A General Motors authorized dealer in the United Arab Emirates has placed a functional Chevrolet Camaro 3D configurator on its website. Greenpeace created interactive 3D infographics to back Greenpeace's Detox campaign in Russia. Tallink featured an interactive 3D presentation of its MS Megastar vessel to allow visitors to browse details of the ship.