Isolation forest is an unsupervised learning algorithm for anomaly detection that works on the principle of isolating anomalies, instead of the most common techniques of profiling normal points. In statistics, an anomaly (a.k.a. outlier) is an observation or event that deviates so much from other events to arouse suspicion it was generated by a different mean. For example, the graph in Fig.1 represents ingress traffic to a web server, expressed as the number of requests in 3-hours intervals, for a period of one month. It is quite evident by simply looking at the picture that some points (marked with a red circle) are unusually high, to the point of inducing suspect that the web server might have been under attack at that time. On the other hand, the flat segment indicated by the red arrow also seems unusual and might possibly be a sign that the server was down during that time period. Anomalies in a big dataset may follow very complicated patterns, which are difficult to detect "by eye" in the great majority of cases. This is the reason why the field of anomaly detection is well suited for the application of machine learning techniques. The most common techniques employed for anomaly detection are based on the construction of a profile of what is "normal": anomalies are reported as those instances in the dataset that do not conform to the normal profile. Isolation Forest uses a different approach: instead of trying to build a model of normal instances, it explicitly isolates anomalous points in the dataset. The main advantage of this approach is the possibility of exploiting sampling techniques to an extent that is not allowed to the profile-based methods, creating a very fast algorithm with a low memory demand. == History == The Isolation Forest (iForest) algorithm was initially proposed by Fei Tony Liu, Kai Ming Ting and Zhi-Hua Zhou in 2008. The authors took advantage of two quantitative properties of anomalous data points in a sample, that is: they are the minority consisting of fewer instances and they have attribute-values that are very different from those of normal instances Since anomalies are typically few and very different from the other points in the sample, they must be easier to "isolate" compared to normal points. On the basis of this principle, Isolation Forest builds an ensemble of "Isolation Trees" (iTrees) for the data set and marks as anomalies the points that have short average path lengths on the iTrees. In a later paper, published in 2012 the same authors described a set of experiments to prove that iForest: has a low linear time complexity and a small memory requirement is able to deal with high dimensional data with irrelevant attributes can be trained with or without anomalies in the training set can provide detection results with different levels of granularity without re-training In 2013 Zhiguo Ding and Minrui Fei proposed a framework based on iForest to resolve the problem of detecting anomalies in streaming data. More application of iForest to streaming data are described in papers by Swee Chuan Tan et al., G. A. Susto et al. and Yu Weng et al. One of the main problems of the application of iForest to anomaly detection was not with the model itself, but rather in the way the "anomaly score" was computed. This problem was highlighted by Sahand Hariri, Matias Carrasco Kind and Robert J. Brunner in a 2018 paper, wherein they proposed an improved iForest model named Extended Isolation Forest (EIF). In the same paper the authors describe the improvements made to the original model and how they are able to enhance the consistency and reliability of the anomaly score produced for a given data point. == Algorithm == At the basis of the Isolation Forest algorithm there is the tendency of anomalous instances in a dataset to be easier to separate from the rest of the sample (isolate), compared to normal points. In order to isolate a data point the algorithm recursively generates partitions on the sample by randomly selecting an attribute and then randomly selecting a split value for the attribute, between the minimum and maximum values allowed for that attribute. An example of random partitioning in a 2D dataset of normally distributed points is given in Fig. 2 for a non-anomalous point and Fig. 3 for a point that's more likely to be an anomaly. It is apparent from the pictures how anomalies require fewer random partitions to be isolated, compared to normal points. From a mathematical point of view, recursive partitioning can be represented by a tree structure named Isolation Tree, while the number of partitions required to isolate a point can be interpreted as the length of the path, within the tree, to reach a terminating node starting from the root. For example, the path length of point xi in Fig. 2 is greater than the path length of xj in Fig. 3. More formally, let X = { x1, ..., xn } be a set of d-dimensional points and X' ⊂ X a subset of X. An Isolation Tree (iTree) is defined as a data structure with the following properties: for each node T in the Tree, T is either an external-node with no child, or an internal-node with one "test" and exactly two daughter nodes (Tl, Tr) a test at node T consists of an attribute q and a split value p such that the test q < p determines the traversal of a data point to either Tl or Tr. In order to build an iTree, the algorithm recursively divides X' by randomly selecting an attribute q and a split value p, until either (i) the node has only one instance or (ii) all data at the node have the same values. When the iTree is fully grown, each point in X is isolated at one of the external nodes. Intuitively, the anomalous points are those (easier to isolate, hence) with the smaller path length in the tree, where the path length h(xi) of point x i ∈ X {\displaystyle x_{i}\in X} is defined as the number of edges xi traverses from the root node to get to an external node. A probabilistic explanation of iTree is provided in the iForest original paper. == Properties of Isolation Forest == Sub-sampling: since iForest does not need to isolate all of normal instances, it can frequently ignore the big majority of the training sample. As a consequence, iForest works very well when the sampling size is kept small, a property that is in contrast with the great majority of existing methods, where large sampling size is usually desirable. Swamping: when normal instances are too close to anomalies, the number of partitions required to separate anomalies increases, a phenomena known as swamping, which makes it more difficult for iForest to discriminate between anomalies and normal points. One of the main reasons for swamping is the presence of too many data for the purpose of anomaly detection, which implies one possible solution to the problem is sub-sampling. Since iForest respond very well to sub-sampling in terms of performance, the reduction of the number of points in the sample is also a good way to reduce the effect of swamping. Masking: when the number of anomalies is high it is possible that some of those aggregate in a dense and large cluster, making it more difficult to separate the single anomalies and, in turn, to detect such points as anomalous. Similarly to swamping, this phenomena (known as "masking") is also more likely when the number of points in the sample is big, and can be alleviated through sub-sampling. High Dimensional Data: one of the main limitation to standard, distance-based methods is their inefficiency in dealing with high dimensional datasets:. The main reason for that is, in a high dimensional space every point is equally sparse, so using a distance-based measure of separation is pretty ineffective. Unfortunately, high-dimensional data also affects the detection performance of iForest, but the performance can be vastly improved by adding a features selection test like Kurtosis to reduce the dimensionality of the sample space. Normal Instances Only: iForest performs well even if the training set does not contain any anomalous point, the reason being that iForest describes data distributions in such a way that high values of the path length h(xi) correspond to the presence of data points. As a consequence, the presence of anomalies is pretty irrelevant to iForest's detection performance. == Anomaly Detection with Isolation Forest == Anomaly detection with Isolation Forest is a process composed of two main stages: in the first stage, a training dataset is used to build iTrees as described in previous sections. in the second stage, each instance in test set is passed through the iTrees build in the previous stage, and a proper "anomaly score" is assigned to the instance using the algorithm described below Once all the instances in the test set have been assigned an anomaly score, it is possible to mark as "anomaly" any point whose score is greater than a predefined threshold, which depends on the domain the analysis is being applied to. === Anomaly Score === Th
Rapid prototyping
Rapid prototyping is a group of techniques used to quickly fabricate a scale model of a physical part or assembly using three-dimensional computer aided design (CAD) data. Construction of the part or assembly is usually done using 3D printing or "additive layer manufacturing" technology. The first methods for rapid prototyping became available in mid 1987 and were used to produce models and prototype parts. Today, they are used for a wide range of applications and are used to manufacture production-quality parts in relatively small numbers if desired without the typical unfavorable short-run economics. This economy has encouraged online service bureaus. Historical surveys of RP technology start with discussions of simulacra production techniques used by 19th-century sculptors. Some modern sculptors use the progeny technology to produce exhibitions and various objects. The ability to reproduce designs from a dataset has given rise to issues of rights, as it is now possible to interpolate volumetric data from 2D images. As with CNC subtractive methods, the computer-aided-design – computer-aided manufacturing CAD -CAM workflow in the traditional rapid prototyping process starts with the creation of geometric data, either as a 3D solid using a CAD workstation, or 2D slices using a scanning device. For rapid prototyping this data must represent a valid geometric model; namely, one whose boundary surfaces enclose a finite volume, contain no holes exposing the interior, and do not fold back on themselves. In other words, the object must have an "inside". The model is valid if for each point in 3D space the computer can determine uniquely whether that point lies inside, on, or outside the boundary surface of the model. CAD post-processors will approximate the application vendors' internal CAD geometric forms (e.g., B-splines) with a simplified mathematical form, which in turn is expressed in a specified data format which is a common feature in additive manufacturing: STL file format, a de facto standard for transferring solid geometric models to SFF machines. To obtain the necessary motion control trajectories to drive the actual SFF, rapid prototyping, 3D printing or additive manufacturing mechanism, the prepared geometric model is typically sliced into layers, and the slices are scanned into lines (producing a "2D drawing" used to generate trajectory as in CNC's toolpath), mimicking in reverse the layer-to-layer physical building process. == Application areas == Rapid prototyping is also commonly applied in software engineering to try out new business models and application architectures such as Aerospace, Automotive, Financial Services, Product development, and Healthcare. Aerospace design and industrial teams rely on prototyping in order to create new AM methodologies in the industry. Using SLA they can quickly make multiple versions of their projects in a few days and begin testing quicker. Rapid Prototyping allows designers/developers to provide an accurate idea of how the finished product will turn out before putting too much time and money into the prototype. 3D printing being used for Rapid Prototyping allows for Industrial 3D printing to take place. With this, you could have large-scale moulds to spare parts being pumped out quickly within a short period of time. == Types of Rapid Prototyping == Stereolithography (SLA) → a laser-cured photopolymer for materials such as thermoplastic-like photopolymers. Selective Laser Sintering (SLS) → a laser-sintered powder for materials such as Nylon or TPU. Direct Metal Laser Sintering (DMLS) → laser-sintered metal powder for materials like stainless steel, titanium, chrome, and aluminum. Fused Deposition Modeling (FDM) → fused extrusions of filaments like ABS, PC, and PPCU. Multi Jet Fusion (MJF) → it is an inkjet array selective fusing across bed of nylon powder for Black Nylon 12. PolyJet (PJET) → it is a uv-cured jetted photopolymer to work with acrylic-based and elastomeric photopolymers. Computer Numerical Controlled Machine (CNC) → it is used for manipulating engineering-grade thermoplastics and metals. Injection Molding (IM) → the injection is done using aluminum molds and it is used for thermoplastics, metals and liquid silicone rubber. Vacuum Casting→ is a manufacturing process used to create high-quality prototypes and small batches of parts. == History == In the 1970s, Joseph Henry Condon and others at Bell Labs developed the Unix Circuit Design System (UCDS), automating the laborious and error-prone task of manually converting drawings to fabricate circuit boards for the purposes of research and development. By the 1980s, U.S. policy makers and industrial managers were forced to take note that America's dominance in the field of machine tool manufacturing evaporated, in what was named the machine tool crisis. Numerous projects sought to counter these trends in the traditional CNC CAM area, which had begun in the US. Later when Rapid Prototyping Systems moved out of labs to be commercialized, it was recognized that developments were already international and U.S. rapid prototyping companies would not have the luxury of letting a lead slip away. The National Science Foundation was an umbrella for the National Aeronautics and Space Administration (NASA), the US Department of Energy, the US Department of Commerce NIST, the US Department of Defense, Defense Advanced Research Projects Agency (DARPA), and the Office of Naval Research coordinated studies to inform strategic planners in their deliberations. One such report was the 1997 Rapid Prototyping in Europe and Japan Panel Report in which Joseph J. Beaman founder of DTM Corporation [DTM RapidTool pictured] provides a historical perspective: The roots of rapid prototyping technology can be traced to practices in topography and photosculpture. Within TOPOGRAPHY Blanther (1892) suggested a layered method for making a mold for raised relief paper topographical maps .The process involved cutting the contour lines on a series of plates which were then stacked. Matsubara (1974) of Mitsubishi proposed a topographical process with a photo-hardening photopolymer resin to form thin layers stacked to make a casting mold. PHOTOSCULPTURE was a 19th-century technique to create exact three-dimensional replicas of objects. Most famously Francois Willeme (1860) placed 24 cameras in a circular array and simultaneously photographed an object. The silhouette of each photograph was then used to carve a replica. Morioka (1935, 1944) developed a hybrid photo sculpture and topographic process using structured light to photographically create contour lines of an object. The lines could then be developed into sheets and cut and stacked, or projected onto stock material for carving. The Munz (1956) Process reproduced a three-dimensional image of an object by selectively exposing, layer by layer, a photo emulsion on a lowering piston. After fixing, a solid transparent cylinder contains an image of the object. "The Origins of Rapid Prototyping - RP stems from the ever-growing CAD industry, more specifically, the solid modeling side of CAD. Before solid modeling was introduced in the late 1980's, three-dimensional models were created with wire frames and surfaces. But not until the development of true solid modeling could innovative processes such as RP be developed. Charles Hull, who helped found 3D Systems in 1986, developed the first RP process. This process, called stereolithography, builds objects by curing thin consecutive layers of certain ultraviolet light-sensitive liquid resins with a low-power laser. With the introduction of RP, CAD solid models could suddenly come to life". The technologies referred to as Solid Freeform Fabrication are what we recognize today as rapid prototyping, 3D printing or additive manufacturing: Swainson (1977), Schwerzel (1984) worked on polymerization of a photosensitive polymer at the intersection of two computer controlled laser beams. Ciraud (1972) considered magnetostatic or electrostatic deposition with electron beam, laser or plasma for sintered surface cladding. These were all proposed but it is unknown if working machines were built. Hideo Kodama of Nagoya Municipal Industrial Research Institute was the first to publish an account of a solid model fabricated using a photopolymer rapid prototyping system (1981). The first 3D rapid prototyping system relying on Fused Deposition Modeling (FDM) was made in April 1992 by Stratasys but the patent did not issue until June 9, 1992. Sanders Prototype, Inc introduced the first desktop inkjet 3D Printer (3DP) using an invention from August 4, 1992 (Helinski), Modelmaker 6Pro in late 1993 and then the larger industrial 3D printer, Modelmaker 2, in 1997. Z-Corp using the MIT 3DP powder binding for Direct Shell Casting (DSP) invented 1993 was introduced to the market in 1995. Even at that early date the technology was seen as having a place in manufacturing practice. A low resol
Macroelectronics
Macroelectronics are flexible electronics that cover a large area. The most visible example of macroelectronics is flat-panel displays. Other emerging applications include rollable display, printable thin film solar cell and electronic skin. Flat-panel displays fabricated on glass substrates are fragile so fabricating directly on flexible substrates, such as polymers is being explored. Displays made on thin polymer substrates can be more rugged than glass. In September 2005, Philips Polymer Vision revealed the world's first prototype of a rollable electronic reader, which can unfold to a 5-inch display and roll back into a pocket-size (100×60×20 mm) device. Thin-film devices on flexible polymer substrates can lend themselves to low-cost fabrication processes (i.e., roll-to-roll printing), resulting in lightweight, rugged and flexible macroelectronic products.
List of operating systems
This is a list of operating systems. Computer operating systems can be categorized by technology, ownership, licensing, working state, usage, and by many other characteristics. In practice, many of these groupings may overlap. Criteria for inclusion is notability, as shown either through an existing Wikipedia article or citation to a reliable source. == Proprietary == === Acorn Computers === Arthur ARX MOS RISC iX RISC OS === Amazon === Fire OS === Amiga Inc. === AmigaOS AmigaOS 1.0-3.9 (Motorola 68000) AmigaOS 4 (PowerPC) Amiga Unix (a.k.a. Amix) === Amstrad === AMSDOS Contiki CP/M 2.2 CP/M Plus SymbOS === Apple === Apple II Apple DOS Apple Pascal ProDOS GS/OS GNO/ME Contiki Apple III Apple SOS Apple Lisa Mac Classic Mac OS A/UX (UNIX System V with BSD extensions) Copland MkLinux Pink Rhapsody macOS (formerly Mac OS X and OS X) macOS Server (formerly Mac OS X Server and OS X Server) Apple Network Server IBM AIX (Apple-customized) Apple MessagePad Newton OS iPhone and iPod Touch iOS (formerly iPhone OS) iPad iPadOS Apple Watch watchOS Apple TV tvOS Embedded operating systems bridgeOS Apple Vision Pro visionOS Embedded operating systems A/ROSE iPod software (unnamed embedded OS for iPod) Unnamed NetBSD variant for Airport Extreme and Time Capsule === Apollo Computer, Hewlett-Packard === Domain/OS – One of the first network-based systems. Run on Apollo/Domain hardware. Later bought by Hewlett-Packard. === Atari === Atari DOS (for 8-bit computers) Atari TOS Atari MultiTOS Contiki (for 8-bit, ST, Portfolio) === BAE Systems === XTS-400 === Be Inc. === BeOS BeIA BeOS r5.1d0 magnussoft ZETA (based on BeOS r5.1d0 source code, developed by yellowTAB) === Bell Labs === Unix ("Ken's new system," for its creator (Ken Thompson), officially Unics and then Unix, the prototypic operating system created in Bell Labs in 1969 that formed the basis for the Unix family of operating systems) UNIX Time-Sharing System v1 UNIX Time-Sharing System v2 UNIX Time-Sharing System v3 UNIX Time-Sharing System v4 UNIX Time-Sharing System v5 UNIX Time-Sharing System v6 MINI-UNIX PWB/UNIX USG CB Unix UNIX Time-Sharing System v7 (It is from Version 7 Unix (and, to an extent, its descendants listed below) that almost all Unix-based and Unix-like operating systems descend.) Unix System III Unix System IV Unix System V Unix System V Releases 2.0, 3.0, 3.2, 4.0, and 4.2 UNIX Time-Sharing System v8 UNIX Time-Sharing System v9 UNIX Time-Sharing System v10 Non-Unix Operating Systems: BESYS Plan 9 from Bell Labs Inferno === Burroughs Corporation, Unisys === Burroughs MCP === CII === Siris 8 === Commodore International === GEOS AmigaOS AROS Research Operating System === Control Data Corporation === ==== Lower 3000 series ==== SCOPE (Supervisory Control Of Program Execution) ==== Upper 3000 series ==== SCOPE (Supervisory Control Of Program Execution) Drum SCOPE ==== 6x00 and related Cyber ==== Chippewa Operating System (COS) MACE (Mansfield and Cahlander Executive) Kronos (Kronographic OS) NOS (Network Operating System) NOS/VE (NOS Virtual Environment) SCOPE (Supervisory Control Of Program Execution) NOS/BE NOS Batch Environment SIPROS (Simultaneous Processing Operating System) ==== Star-100 ==== Multiple Console Time Sharing System (MCTS), from General Motors Research === CloudMosa === Puffin OS === Convergent Technologies === Convergent Technologies Operating System (CTOS) – later acquired by Unisys === Cromemco === Cromemco DOS (CDOS) – a Disk Operating system compatible with CP/M Cromix – a multitasking, multi-user, Unix-like OS for Cromemco microcomputers with Z80A and/or 68000 CPU === Data General === AOS for 16-bit Data General Eclipse computers and AOS/VS for 32-bit (MV series) Eclipses, MP/AOS for microNOVA-based computers DG/UX RDOS Real-time Disk Operating System, with variants: RTOS and DOS (not related to PC DOS, MS-DOS etc.) === Datapoint === CTOS Cassette Tape Operating System for the Datapoint 2200 DOS Disk Operating System for the Datapoint 2200, 5500, and 1100 === DDC-I, Inc. === Deos – Time & Space Partitioned RTOS, Certified to DO-178B, Level A since 1998 HeartOS – POSIX-based Hard Real-Time Operating System === Digital Research, Inc. === CP/M CP/M CP/M for Intel 8080/8085 and Zilog Z80 Personal CP/M, a refinement of CP/M CP/M Plus with BDOS 3.0 CP/M-68K CP/M for Motorola 68000 CP/M-8000 CP/M for Zilog Z8000 CP/M-86 CP/M for Intel 8088/8086 CP/M-86 Plus Personal CP/M-86 MP/M Multi-user version of CP/M-80 MP/M II MP/M-86 Multi-user version of CP/M-86 MP/M 8-16, a dual-processor variant of MP/M for 8086 and 8080 CPUs. Concurrent CP/M, the successor of CP/M-80 and MP/M-80 Concurrent CP/M-86, the successor of CP/M-86 and MP/M-86 Concurrent CP/M 8-16, a dual-processor variant of Concurrent CP/M for 8086 and 8080 CPUs. Concurrent CP/M-68K, a variant for the 68000 DOS Concurrent DOS, the successor of Concurrent CP/M-86 with PC-MODE Concurrent PC DOS, a Concurrent DOS variant for IBM compatible PCs Concurrent DOS 8-16, a dual-processor variant of Concurrent DOS for 8086 and 8080 CPUs Concurrent DOS 286 Concurrent DOS XM, a real-mode variant of Concurrent DOS with EEMS support Concurrent DOS 386 Concurrent DOS 386/MGE, a Concurrent DOS 386 variant with advanced graphics terminal capabilities Concurrent DOS 68K, a port of Concurrent DOS to Motorola 68000 CPUs with DOS source code portability capabilities FlexOS 1.0 – 2.34, a derivative of Concurrent DOS 286 FlexOS 186, a variant of FlexOS for terminals FlexOS 286, a variant of FlexOS for hosts Siemens S5-DOS/MT, an industrial control system based on FlexOS IBM 4680 OS, a POS operating system based on FlexOS IBM 4690 OS, a POS operating system based on FlexOS Toshiba 4690 OS, a POS operating system based on IBM 4690 OS and FlexOS FlexOS 386, a later variant of FlexOS for hosts IBM 4690 OS, a POS operating system based on FlexOS Toshiba 4690 OS, a POS operating system based on IBM 4690 OS and FlexOS FlexOS 68K, a derivative of Concurrent DOS 68K Multiuser DOS, the successor of Concurrent DOS 386 CCI Multiuser DOS Datapac Multiuser DOS Datapac System Manager, a derivative of Datapac Multiuser DOS IMS Multiuser DOS IMS REAL/32, a derivative of Multiuser DOS IMS REAL/NG, the successor of REAL/32 DOS Plus 1.1 – 2.1, a single-user, multi-tasking system derived from Concurrent DOS 4.1 – 5.0 DR-DOS 3.31 – 6.0, a single-user, single-tasking native DOS derived from Concurrent DOS 6.0 Novell PalmDOS 1.0 Novell "Star Trek" Novell DOS 7, a single-user, multi-tasking system derived from DR DOS Caldera OpenDOS 7.01 Caldera DR-DOS 7.02 and higher === Digital Equipment Corporation, Compaq, Hewlett-Packard, Hewlett Packard Enterprise === Batch-11/DOS-11 OS/8 RSTS/E – multi-user time-sharing OS for PDP-11s RSX-11 – multiuser, multitasking OS for PDP-11s RT-11 – single user OS for PDP-11 TOPS-10 – for the PDP-10 TENEX – an ancestor of TOPS-20 from BBN, for the PDP-10 TOPS-20 – for the PDP-10 DEC MICA – for the DEC PRISM Digital UNIX – derived from OSF/1, became HP's Tru64 UNIX Ultrix VMS – originally by DEC (now by VMS Software Inc.) for the VAX mini-computer range; later renamed OpenVMS and ported to Alpha, and subsequently ported to Intel Itanium and then to x86-64 WAITS – for the PDP-6 and PDP-10 === ENEA AB === OSE – Flexible, small footprint, high-performance RTOS for control processors === Fujitsu === Towns OS XSP OS/IV MSP MSP-EX === GEC Computers === COS DOS OS4000 === General Electric, Honeywell, Bull === Real-Time Multiprogramming Operating System GCOS Multics === Google === ChromiumOS is an open source operating system development version of ChromeOS. Both operating systems are based on the Linux kernel. ChromeOS is designed to work exclusively with web applications, though has been updated to run Android apps with full support for Google Play Store. Announced on July 7, 2009, ChromeOS is currently publicly available and was released summer 2011. The ChromeOS source code was released on November 19, 2009, under the BSD license as ChromiumOS. Container-Optimized OS (COS) is an operating system that is optimized for running Docker containers, based on ChromiumOS. Android is an operating system for mobile devices. It consists of Android Runtime (userland) with Linux (kernel), with its Linux kernel modified to add drivers for mobile device hardware and to remove unused Vanilla Linux drivers. gLinux, a Linux distribution that Google uses internally Fuchsia is a capability-based real-time operating system (RTOS) scalable to universal devices, in early development, from the tiniest embedded hardware, wristwatches, tablets to the largest personal computers. Unlike ChromeOS and Android, it is not based on the Linux kernel, but instead began on a new microkernel called "Zircon", derived from "Little Kernel". Wear OS a version of Google's Android operating system designed for smartwatches and other wearables. === Green Hills Software === INTEGRITY – Reliable Operating system INTEGRITY-178B – A DO-178B certified version of INTEGRITY. μ-
LTE (telecommunication)
In telecommunications, Long Term Evolution (LTE) is a standard for wireless broadband communication for cellular mobile devices and data terminals. It is considered to be a "transitional" 4G technology, and is therefore also referred to as 3.95G as a step above 3G. LTE is based on the 2G GSM/EDGE and 3G UMTS/HSPA standards. It improves on those standards' capacity and speed by using a different radio interface and core network improvements. LTE is the upgrade path for carriers with both GSM/UMTS networks and CDMA2000 networks. LTE has been succeeded by LTE Advanced, which is officially defined as a "true" 4G technology and also named "LTE+". == Terminology == The standard is developed by the 3GPP (3rd Generation Partnership Project) and is specified in its Release 8 document series, with minor enhancements described in Release 9. LTE is also called 3.95G and has been marketed as 4G LTE and Advanced 4G; but the original version did not meet the technical criteria of a 4G wireless service, as specified in the 3GPP Release 8 and 9 document series for LTE Advanced. The requirements were set forth by the ITU-R organisation in the IMT Advanced specification; but, because of market pressure and the significant advances that WiMAX, Evolved High Speed Packet Access, and LTE bring to the original 3G technologies, ITU-R later decided that LTE and the aforementioned technologies can be called 4G technologies. The LTE Advanced standard formally satisfies the ITU-R requirements for being considered IMT-Advanced. To differentiate LTE Advanced and WiMAX-Advanced from current 4G technologies, ITU has defined the latter as "True 4G". == Overview == LTE stands for Long Term Evolution and is a registered trademark owned by ETSI (European Telecommunications Standards Institute) for the wireless data communications technology and development of the GSM/UMTS standards. However, other nations and companies do play an active role in the LTE project. The goal of LTE was to increase the capacity and speed of wireless data networks using new DSP (digital signal processing) techniques and modulations that were developed around the turn of the millennium. A further goal was the redesign and simplification of the network architecture to an IP-based system with significantly reduced transfer latency compared with the 3G architecture. The LTE wireless interface is incompatible with 2G and 3G networks, so it must be operated on a separate radio spectrum. The idea of LTE was first proposed in 1998, with the use of the COFDM radio access technique to replace the CDMA and studying its Terrestrial use in the L band at 1428 MHz (TE) In 2004 by Japan's NTT Docomo, with studies on the standard officially commenced in 2005. In May 2007, the LTE/SAE Trial Initiative (LSTI) alliance was founded as a global collaboration between vendors and operators with the goal of verifying and promoting the new standard to ensure the global introduction of the technology as quickly as possible. The LTE standard was finalized in December 2008, and the first publicly available LTE service was launched by TeliaSonera in Oslo and Stockholm on December 14, 2009, as a data connection with a USB modem. The LTE services were launched by major North American carriers as well, with the Samsung SCH-r900 being the world's first LTE Mobile phone starting on September 21, 2010, and Samsung Galaxy Indulge being the world's first LTE smartphone starting on February 10, 2011, both offered by MetroPCS, and the HTC ThunderBolt offered by Verizon starting on March 17 being the second LTE smartphone to be sold commercially. In Canada, Rogers Wireless was the first to launch LTE network on July 7, 2011, offering the Sierra Wireless AirCard 313U USB mobile broadband modem, known as the "LTE Rocket stick" then followed closely by mobile devices from both HTC and Samsung. Initially, CDMA operators planned to upgrade to rival standards called UMB and WiMAX, but major CDMA operators (such as Verizon, Sprint and MetroPCS in the United States, Bell and Telus in Canada, au by KDDI in Japan, SK Telecom in South Korea and China Telecom/China Unicom in China) have announced instead they intend to migrate to LTE. The next version of LTE is LTE Advanced, which was standardized in March 2011. Services commenced in 2013. Additional evolution known as LTE Advanced Pro was approved in 2015. The LTE specification provides downlink peak rates of 300 Mbit/s, uplink peak rates of 75 Mbit/s, and QoS provisions permitting a transfer latency of less than 5 ms in the radio access network. LTE has the ability to manage fast-moving mobiles and supports multicast and broadcast streams. LTE supports scalable carrier bandwidths, from 1.4 MHz to 20 MHz and supports both frequency division duplexing (FDD) and time-division duplexing (TDD). The IP-based network architecture, called the Evolved Packet Core (EPC) designed to replace the GPRS Core Network, supports seamless handovers for both voice and data to cell towers with older network technology such as GSM, UMTS and CDMA2000. The simpler architecture results in lower operating costs (for example, each E-UTRA cell will support up to four times the data and voice capacity supported by HSPA). Because LTE frequencies and bands differ from country to country, only multi-band phones can use LTE in all countries where it is supported. == History == === 3GPP standard development timeline === In 2004, NTT Docomo of Japan proposes LTE as the international standard. In September 2006, Siemens Networks (today Nokia Networks) showed in collaboration with Nomor Research the first live emulation of an LTE network to the media and investors. As live applications, two users streaming an HDTV video in the downlink and playing an interactive game in the uplink have been demonstrated. In February 2007, Ericsson demonstrated for the first time in the world, LTE with bit rates up to 144 Mbit/s In September 2007, NTT Docomo demonstrated LTE data rates of 200 Mbit/s with power level below 100 mW during the test. In November 2007, Infineon presented the world's first RF transceiver named SMARTi LTE, supporting LTE functionality in a single-chip RF silicon processed in CMOS In early 2008, LTE test equipment began shipping from several vendors and at the Mobile World Congress 2008 in Barcelona, Ericsson demonstrated the world's first end-to-end mobile call enabled by LTE on a small handheld device. Motorola demonstrated an LTE RAN (Radio Access Network) standard compliant eNodeB and LTE chipset at the same event. At the February 2008 Mobile World Congress: Motorola demonstrated how LTE can accelerate the delivery of personal media experience with HD video demo streaming, HD video blogging, online gaming, and VoIP over LTE running a RAN standard-compliant LTE network & LTE chipset. Ericsson EMP (later ST-Ericsson) demonstrated the world's first end-to-end LTE call on handheld Ericsson demonstrated LTE FDD and TDD mode on the same base station platform. Freescale Semiconductor demonstrated streaming HD video with peak data rates of 96 Mbit/s downlink and 86 Mbit/s uplink. NXP Semiconductors (later part of ST-Ericsson) demonstrated a multi-mode LTE modem as the basis for a software-defined radio system for use in cellphones. picoChip and Mimoon demonstrated a base station reference design. This runs on a common hardware platform (multi-mode / software-defined radio) with their WiMAX architecture. In April 2008, Motorola demonstrated the first EV-DO to LTE hand-off handling over streaming a video from LTE to a commercial EV-DO network and back to LTE. In April 2008, LG Electronics and Nortel demonstrated LTE data rates of 50 Mbit/s while travelling at 110 km/h (68 mph). In November 2008, Motorola demonstrated industry first over-the-air LTE session in 700 MHz spectrum. Researchers at Nokia Siemens Networks and Heinrich Hertz Institut have demonstrated LTE with 100 Mbit/s Uplink transfer speeds. At the February 2009 Mobile World Congress: Infineon demonstrated a single-chip 65 nm CMOS RF transceiver providing 2G/3G/LTE functionality Launch of ng Connect program, a multi-industry consortium founded by Alcatel-Lucent to identify and develop wireless broadband applications. Motorola provided LTE drive tour on the streets of Barcelona to demonstrate LTE system performance in a real-life metropolitan RF environment In July 2009, Nujira demonstrated efficiencies of more than 60% for an 880 MHz LTE Power Amplifier In August 2009, Nortel and LG Electronics demonstrated the first successful handoff between CDMA and LTE networks in a standards-compliant manner In August 2009, Alcatel-Lucent receives FCC certification for LTE base stations for the 700 MHz spectrum band. In September 2009, Nokia Siemens Networks demonstrated the world's first LTE call on standards-compliant commercial software. In October 2009, Ericsson and Samsung demonstrated interoperability between the first ever commercial LTE device and the live network in
Inverse consistency
In image registration, inverse consistency measures the consistency of mappings between images produced by a registration algorithm. The inverse consistency error, introduced by Christiansen and Johnson in 2001, quantifies the distance between the composition of the mappings from each image to the other, produced by the registration procedure, and the identity function, and is used as a regularisation constraint in the loss function of many registration algorithms to enforce consistent mappings. Inverse consistency is necessary for good image registration but it is not sufficient, since a mapping can be perfectly consistent but not register the images at all. == Definition == Image registration is the process of establishing a common coordinate system between two images, and given two images I 1 : Ω 1 → R I 2 : Ω 2 → R {\displaystyle {\begin{aligned}I_{1}:\Omega _{1}\to \mathbb {R} \\I_{2}:\Omega _{2}\to \mathbb {R} \end{aligned}}} registering a source image I 1 {\displaystyle I_{1}} to a target image I 2 {\displaystyle I_{2}} consists of determining a transformation f 1 : Ω 2 → Ω 1 {\displaystyle f_{1}:\Omega _{2}\to \Omega _{1}} that maps points from the target space to the source space. An ideal registration algorithm should not be sensitive to which image in the pair is used as source or target, and the registration operator should be antisymmetric such that the mappings f 1 : Ω 2 → Ω 1 f 2 : Ω 1 → Ω 2 {\displaystyle {\begin{aligned}f_{1}:\Omega _{2}\to \Omega _{1}\\f_{2}:\Omega _{1}\to \Omega _{2}\end{aligned}}} produced when registering I 1 {\displaystyle I_{1}} to I 2 {\displaystyle I_{2}} and I 2 {\displaystyle I_{2}} to I 1 {\displaystyle I_{1}} respectively should be the inverse of each other, i.e. f 2 = f 1 − 1 {\displaystyle f_{2}=f_{1}^{-1}} and f 1 = f 2 − 1 {\displaystyle f_{1}=f_{2}^{-1}} or, equivalently, f 2 ∘ f 1 = id Ω 2 {\displaystyle f_{2}\circ f_{1}=\operatorname {id} _{\Omega _{2}}} and f 1 ∘ f 2 = id Ω 1 {\displaystyle f_{1}\circ f_{2}=\operatorname {id} _{\Omega _{1}}} , where ∘ {\displaystyle \circ } denotes the function composition operator. Real algorithms are not perfect, and when swapping the role of source and target image in a registration problem the so obtained transformations are not the inverse of each other. Inverse consistency can be enforced by adding to the loss function of the registration a symmetric regularisation term that penalises inconsistent transformations ∫ Ω 2 ‖ f 2 ( f 1 ( x ) ) − x ‖ 2 d x + ∫ Ω 1 ‖ f 1 ( f 2 ( x ) ) − x ‖ 2 d x . {\displaystyle \int _{\Omega _{2}}\left\Vert f_{2}(f_{1}(x))-x\right\Vert ^{2}\mathrm {d} x+\int _{\Omega _{1}}\left\Vert f_{1}(f_{2}(x))-x\right\Vert ^{2}\mathrm {d} x.} Inverse consistency can be used as a quality metric to evaluate image registration results. The inverse consistency error ( I C E {\displaystyle ICE} ) measures the distance between the composition of the two transforms and the identity function, and it can be formulated in terms of both average ( I C E a {\displaystyle ICE_{a}} ) or maximum ( I C E m {\displaystyle ICE_{m}} ) over a region of interest Ω {\displaystyle \Omega } of the image: I C E a = 1 ∫ Ω d x ∫ Ω ‖ f 2 ( f 1 ( x ) ) − x ‖ d x I C E m = max x ∈ Ω ‖ f 2 ( f 1 ( x ) ) − x ‖ . {\displaystyle {\begin{aligned}ICE_{a}&={\frac {1}{\int _{\Omega }\mathrm {d} x}}\int _{\Omega }\left\Vert f_{2}(f_{1}(x))-x\right\Vert \mathrm {d} x\\ICE_{m}&=\max _{x\in \Omega }\left\Vert f_{2}(f_{1}(x))-x\right\Vert .\end{aligned}}} While inverse consistency is a necessary property of good registration algorithms, inverse consistency error alone is not a sufficient metric to evaluate the quality of image registration results, since a perfectly consistent mapping, with no other constraint, may be not even close to correctly register a pair of images.
Futel
Futel is a public arts organization in Portland, Oregon dedicated to preserving and maintaining public telephone hardware and offering free phone and basic information services. Futel was founded by Karl Anderson, a former software engineer, and Elijah St. Clair. == Technology == Karl Anderson stated that one motivation for the project was to explore the idea of urban furniture. Other reasons were to preserve an important part of hacker history, and to salvage and re-use manufactured items at the end of their lifecycle. The original Futel phones were set up in Portland, Oregon. The organization cleans and repurposes old public payphones which are often salvaged from Craigslist or scrappers. Using interface boxes, they are converted into VoIP phones which are made available publicly, with no cost for phone calls. Anderson has said the service runs on "Asterisk and OpenVPN and a lot of scripts." The payphones operate using publicly-available internet connections. The phones have automated phone trees and users can make a call to local social services, to a weather forecast line, or access local transit information. Volunteers act as telephone operators, offering information about the Futel service, or are available for conversation. Users using Futel's phones may also access voicemail boxes. The system has a "wildcard line" where people can listen to samples of audio left on the main voicemail line along with commentary from Anderson and others. == Network == In February 2021, there were 10 Futel phones in Portland and 3 in other cities. Phones were set up in Detroit and Ypsilanti, Michigan, and Long Beach, Washington. The organization has provided free phone service for a Portland-area homeless encampment after receiving funding from the Awesome Foundation. In 2019 the organization reported their phones being used to make 12,000 phone calls. Futel also said their usage went up and not down during the first year of the COVID-19 pandemic when they outfitted their phone kiosks with handwashing stations and used volunteers to keep the phones clean. The project is funded is primarily through grants and is staffed with volunteers. The project has inspired others such as the PhilTel project in Philadelphia and the RandTel project in Randolph, Vermont. Futel publishes a zine called Party Line.