Katz back-off is a generative n-gram language model that estimates the conditional probability of a word given its history in the n-gram. It accomplishes this estimation by backing off through progressively shorter history models under certain conditions. By doing so, the model with the most reliable information about a given history is used to provide the better results. The model was introduced in 1987 by Slava M. Katz. Prior to that, n-gram language models were constructed by training individual models for different n-gram orders using maximum likelihood estimation and then interpolating them together. == Method == The equation for Katz's back-off model is: P b o ( w i ∣ w i − n + 1 ⋯ w i − 1 ) = { d w i − n + 1 ⋯ w i C ( w i − n + 1 ⋯ w i − 1 w i ) C ( w i − n + 1 ⋯ w i − 1 ) if C ( w i − n + 1 ⋯ w i ) > k α w i − n + 1 ⋯ w i − 1 P b o ( w i ∣ w i − n + 2 ⋯ w i − 1 ) otherwise {\displaystyle {\begin{aligned}&P_{bo}(w_{i}\mid w_{i-n+1}\cdots w_{i-1})\\[4pt]={}&{\begin{cases}d_{w_{i-n+1}\cdots w_{i}}{\dfrac {C(w_{i-n+1}\cdots w_{i-1}w_{i})}{C(w_{i-n+1}\cdots w_{i-1})}}&{\text{if }}C(w_{i-n+1}\cdots w_{i})>k\\[10pt]\alpha _{w_{i-n+1}\cdots w_{i-1}}P_{bo}(w_{i}\mid w_{i-n+2}\cdots w_{i-1})&{\text{otherwise}}\end{cases}}\end{aligned}}} where C(x) = number of times x appears in training wi = ith word in the given context Essentially, this means that if the n-gram has been seen more than k times in training, the conditional probability of a word given its history is proportional to the maximum likelihood estimate of that n-gram. Otherwise, the conditional probability is equal to the back-off conditional probability of the (n − 1)-gram. The more difficult part is determining the values for k, d and α. k {\displaystyle k} is the least important of the parameters. It is usually chosen to be 0. However, empirical testing may find better values for k. d {\displaystyle d} is typically the amount of discounting found by Good–Turing estimation. In other words, if Good–Turing estimates C {\displaystyle C} as C ∗ {\displaystyle C^{}} , then d = C ∗ C {\displaystyle d={\frac {C^{}}{C}}} To compute α {\displaystyle \alpha } , it is useful to first define a quantity β, which is the left-over probability mass for the (n − 1)-gram: β w i − n + 1 ⋯ w i − 1 = 1 − ∑ { w i : C ( w i − n + 1 ⋯ w i ) > k } d w i − n + 1 ⋯ w i C ( w i − n + 1 ⋯ w i − 1 w i ) C ( w i − n + 1 ⋯ w i − 1 ) {\displaystyle \beta _{w_{i-n+1}\cdots w_{i-1}}=1-\sum _{\{w_{i}:C(w_{i-n+1}\cdots w_{i})>k\}}d_{w_{i-n+1}\cdots w_{i}}{\frac {C(w_{i-n+1}\cdots w_{i-1}w_{i})}{C(w_{i-n+1}\cdots w_{i-1})}}} Then the back-off weight, α, is computed as follows: α w i − n + 1 ⋯ w i − 1 = β w i − n + 1 ⋯ w i − 1 ∑ { w i : C ( w i − n + 1 ⋯ w i ) ≤ k } P b o ( w i ∣ w i − n + 2 ⋯ w i − 1 ) {\displaystyle \alpha _{w_{i-n+1}\cdots w_{i-1}}={\frac {\beta _{w_{i-n+1}\cdots w_{i-1}}}{\sum _{\{w_{i}:C(w_{i-n+1}\cdots w_{i})\leq k\}}P_{bo}(w_{i}\mid w_{i-n+2}\cdots w_{i-1})}}} The above formula only applies if there is data for the "(n − 1)-gram". If not, the algorithm skips n-1 entirely and uses the Katz estimate for n-2. (and so on until an n-gram with data is found) == Discussion == This model generally works well in practice, but fails in some circumstances. For example, suppose that the bigram "a b" and the unigram "c" are very common, but the trigram "a b c" is never seen. Since "a b" and "c" are very common, it may be significant (that is, not due to chance) that "a b c" is never seen. Perhaps it's not allowed by the rules of the grammar. Instead of assigning a more appropriate value of 0, the method will back off to the bigram and estimate P(c | b), which may be too high.
AltStore
AltStore is an alternative app store for the iOS and iPadOS[1] mobile operating systems, which allows users to download applications that are not available on the App Store, most commonly tweaked apps, jailbreak apps, and apps including paid apps on the app store. It was publicly announced on September 25, 2019, and launched on September 28. == History == Riley Testut is an American developer who began to work on AltStore after Apple declined to allow his Nintendo emulator Delta on the App Store. Since Xcode allowed him to temporarily install his Delta app to his iOS device for 7 days of testing, he created AltStore in 2019 to replicate this functionality, which could be extended to other .ipa files. As of 2022, AltStore had been downloaded 1.5 million times. In the following years, AltStore expanded beyond its initial sideloading functionality. The platform was founded by Testut, with Shane Gill later joining as co-founder. AltStore was initially supported through Patreon contributions from its user community, and later saw increased adoption following regulatory developments in the European Union that enabled broader third-party app distribution. The project has also been involved in notable industry collaborations, including a partnership with Epic Games. == Features == AltStore exploits a loophole in the Xcode developer platform, which allows developers to sideload their own apps which they are working on without needing to jailbreak. Sideloaded apps are signed like a developer project for testing and will expire after 7 days with a free account or one year with a paid developer account, by which they will need to be refreshed or reinstalled.
Digital media service
A digital media service (DMS) is an online service provider that sells access to digital library of content such as films, software, games, images, literature, etc. While no transfer of property is made, a nearly perfect duplicate of the data (song movie, etc.) is made on a customer's computer. Content is either primarily hosted on a dedicated server, which is owned by the service provider, or it is hosted primarily on the hard drives of its customers using a P2P protocol with, perhaps, a dedicated server to supplement. == History == One example of the older business model is the iTunes Store, which still markets and prices data as individual retail products. There are no examples of the latter business model in operation yet, but one is currently in development by Global Gaming Factory X and expected to begin operation some time after they acquire The Pirate Bay domain on August 27, 2009. A key difference between the two models is that the model which relies on its customer base for offering their bandwidth for other customers to access customer hosted data can operate at significantly lower costs than a company that seeks to limit data access to a per-download fee in order to supplement the cost of using its own hosting and bandwidth. The P2P model holds the potential for companies to offer unlimited access to the largest data library in the history of the internet to its customers for a reasonably low membership rate that is relevant to the cost of operation. While the market is virtually untouched, the P2P supplemented model will need entrepreneurs who are able to overcome a series of challenges in order to compete with the older business model as well as that which is offered for free (and often against the wishes of copyright holders) by hundreds of P2P communities on the internet. These challenges include, but are not limited to: Offering better data quality, speed, convenience and ease of use, protocol, sense of security, indexing and search organization, site up time, data library size, customer support, advertising, artist/copyright holder incentives and compensation, incentives and compensation for customers hosting data and providing bandwidth, guaranteed seeding (available access to indexed data at all times), than competitors.
Problematic social media use
Excessive use of social media can lead to problems including impaired functioning and a reduction in overall wellbeing, for both users and those around them. Such usage is associated with a risk of mental health problems, sleep problems, academic struggles, and daytime fatigue. Psychological or behavioural dependence on social media platforms can result in significant negative functions in peoples daily lives. The risk of problems is also related to the type of platform of social media or online community being used. People of different ages and genders may be affected in different ways by problematic social media use. == Signs and symptoms == Signs of social media addiction or excessive use of social media include many behaviours similar to substance use disorders, including mood modification, salience, tolerance, stress withdrawal symptoms, psychological distress, anxiety and depression, conflict, and relapse, and low self esteem. People with problematic social media habits are at risk of being addicted and may require more time on social media as time passes. Frequent social media use may also be associated with self-reported symptoms of attention deficit hyperactivity disorder. Social anxiety (or fear of missing out) is another potential symptom. Social anxiety is defined as having intense anxiety or fear of being judged, negatively evaluated, or rejected in a social or performance situation. The fear of missing out can contribute to excessive usage due to frequent checking the media constantly throughout the day to check in and see what others are doing instead of doing other activities. Common signs include displacement, or replacing meaningful other activities with social media, and loneliness. == Causes and mechanisms == There are many theories for the mechanism or cause behind a person having problematic social media use. The transition from normal to problematic social media use occurs when a person relies on it to relieve stress, loneliness, depression, or provide continuous rewards. Cognitive-behavioral model – People increase their use of social media when they are in unfamiliar environments or awkward situations; Social skill model – People pull out their phones and use social media when they prefer virtual communication as opposed to face-to-face interactions because they lack self-presentation skills; Socio-cognitive model – This person uses social media because they love the feeling of people liking and commenting on their photos and tagging them in pictures. They are attracted to the positive outcomes they receive on social media. There are parallels to the gambling industry inherent to the design of various social media sites, with "'ludic loops' or repeated cycles of uncertainty, anticipation and feedback" potentially contributing to problematic social media use. Another factor directly facilitating the development of addiction to social media is the implicit attitude toward the IT artifact. Social media use may also stimulate the reward pathway in the brain. There is also a theory that social media addiction fulfills a basic evolutionary drives in the wake of mass urbanization worldwide. The basic psychological needs of "secure, predictable community life that evolved over millions of years" remain unchanged, leading some to find online communities to cope with the new individualized way of life in some modern societies. The "Evolutionary Mismatch" hypothesis holds that modern digital platforms amplify social competition and comparison in ways our ancestors never faced, possibly triggering maladaptive patterns such as anxiety, depression, or compulsive use. Similarly, some scholars compare social media to "junk food": The approach taken to develop social media platforms may contribute to problematic social media use. The ability to scroll and stream content endlessly and how app developers distort time by affecting the 'flow' of content when scrolling, potentially resulting in the Zeigarnik effect (the human brain will continue to pursue an unfinished task until a satisfying closure. Autoplay modes, the personalized nature of the content results in emotional attachment (the user values this above its actual value, which is referred to as the endowment effect), and the exposure effect (repeated exposure to a distinct stimulus by the user can condition the user into an enhanced or improved attitude toward it). The interactive nature of the platforms, including the ability to "like" content has also been linked. Even though social media can satisfy personal communication needs, those who use it at higher rates are shown to have higher levels of psychological distress. == Diagnosis == While there is no official diagnostic term or measurement, problematic social media use is conceptualized as a non-substance-related disorder, resulting in preoccupation and compulsion to engage excessively in social media platforms despite negative consequences. No diagnosis exists for problematic social media use in either the ICD-11 or DSM-5. Excessive use of an activity, like social media, does not directly equate with addiction. There are other factors that could lead to someone's social media addiction including personality traits and pre-existing tendencies. While the extent of social media use and addiction are positively correlated, it is erroneous to employ use (the degree to which one makes use of the site's features, the effort exerted during use sessions, access frequency, etc.) as a proxy for addiction. Indicators of a potential dependence on social media include: Mood swings: a person uses social media to regulate his or her mood, or as a means of escaping real world conflicts. Relevance: social media starts to dominate a person's thoughts at the expense of other activities. Salience: social media becomes the most important part of someone's life. Tolerance: a person increases their time spent on social media to experience previously associated feelings they had while using social media. Withdrawal: when a person can not access social media their sleeping or eating habits change or signs of depression or anxiety can become present. Conflicts in real life: when social media is used excessively, it can affect real-life relationships with family and friends. Relapse: the tendency for previously affected individuals to revert to previous patterns of excessive social media use. There have been several scales developed and validated that help to understand the issues regarding problematic social media use. There is not one single scale that is being used by all researchers. == Treatment == Screen time recommendations for children and families have been developed by the American Academy of Pediatrics. Possible therapeutic interventions published include: Self-help interventions, including application-specific timers; Cognitive behavioural therapy; and Organisational and schooling support. Medications have not been shown to be effective in randomized, controlled trials for the related conditions of Internet addiction disorder or gaming disorder. == Prevention == Prevention approaches include screen time monitoring apps and other tech-based approaches to improve efficiency and decrease screen time and tools to help with addiction to online platform products. Parents' methods for monitoring, regulating, and understanding their children's social media use are referred to as parental mediation. Parental mediation strategies include active, restrictive, and co-using methods. Active mediation involves direct parent-child conversations that are intended to educate children on social media norms and safety, as well as the variety and purposes of online content. Restrictive mediation entails the implementation of rules, expectations, and limitations regarding children's social media use and interactions. Co-use is when parents jointly use social media alongside their children, and is most effective when parents are actively participating (like asking questions, making inquisitive/supportive comments) versus being passive about it. Active mediation is the most common strategy used by parents, though the key to success for any mediation strategy is consistency/reliability. When parents reinforce rules inconsistently, have no mediation strategy, or use highly restrictive strategies for monitoring their children's social media use, there is an observable increase in children's aggressive behaviours. When parents openly express that they are supportive of their child's autonomy and provide clear, consistent rules for media use, problematic usage and aggression decreases. Knowing that consistent, autonomy-supportive mediation has more positive outcomes than inconsistent, controlling mediation, parents can consciously foster more direct, involved, and genuine dialogue with their children. This can help prevent or reduce problematic social media use in children and teenagers. == Outcomes == === Adolescents and teens === Increased social medi
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.
Image fusion
The image fusion process is defined as gathering all the important information from multiple images, and their inclusion into fewer images, usually a single one. This single image is more informative and accurate than any single source image, and it consists of all the necessary information. The purpose of image fusion is not only to reduce the amount of data but also to construct images that are more appropriate and understandable for the human and machine perception. In computer vision, multisensor image fusion is the process of combining relevant information from two or more images into a single image. The resulting image will be more informative than any of the input images. In remote sensing applications, the increasing availability of space borne sensors gives a motivation for different image fusion algorithms. Several situations in image processing require high spatial and high spectral resolution in a single image. Most of the available equipment is not capable of providing such data convincingly. Image fusion techniques allow the integration of different information sources. The fused image can have complementary spatial and spectral resolution characteristics. However, the standard image fusion techniques can distort the spectral information of the multispectral data while merging. In satellite imaging, two types of images are available. The panchromatic image acquired by satellites is transmitted with the maximum resolution available and the multispectral data are transmitted with coarser resolution. This will usually be two or four times lower. At the receiver station, the panchromatic image is merged with the multispectral data to convey more information. Many methods exist to perform image fusion. The very basic one is the high-pass filtering technique. Later techniques are based on Discrete Wavelet Transform, uniform rational filter bank, and Laplacian pyramid. == Motivation == Multi sensor data fusion has become a discipline which demands more general formal solutions to a number of application cases. Several situations in image processing require both high spatial and high spectral information in a single image. This is important in remote sensing. However, the instruments are not capable of providing such information either by design or because of observational constraints. One possible solution for this is data fusion. == Methods == Image fusion methods can be broadly classified into two groups – spatial domain fusion and transform domain fusion. The fusion methods such as averaging, Brovey method, principal component analysis (PCA) and IHS based methods fall under spatial domain approaches. Another important spatial domain fusion method is the high-pass filtering based technique. Here the high frequency details are injected into upsampled version of MS images. The disadvantage of spatial domain approaches is that they produce spatial distortion in the fused image. Spectral distortion becomes a negative factor while we go for further processing, such as classification problem. Spatial distortion can be very well handled by frequency-domain approaches on image fusion. The multiresolution analysis has become a very useful tool for analysing remote sensing images. The discrete wavelet transform has become a very useful tool for fusion. Some other fusion methods are also there, such as Laplacian pyramid based, curvelet transform based etc. These methods show a better performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. The images used in image fusion should already be registered. Misregistration is a major source of error in image fusion. Some well-known image fusion methods are: High-pass filtering technique IHS transform based image fusion PCA-based image fusion Wavelet transform image fusion Pair-wise spatial frequency matching Comparative analysis of image fusion methods demonstrates that different metrics support different user needs, sensitive to different image fusion methods, and need to be tailored to the application. Categories of image fusion metrics are based on information theory features, structural similarity, or human perception. === Multi-focus image fusion === Multi-focus image fusion is used to collect useful and necessary information from input images with different focus depths in order to create an output image that ideally has all information from input images. In visual sensor network (VSN), sensors are cameras which record images and video sequences. In many applications of VSN, a camera can’t give a perfect illustration including all details of the scene. This is because of the limited depth of focus exists in the optical lens of cameras. Therefore, just the object located in the focal length of camera is focused and cleared and the other parts of image are blurred. VSN has an ability to capture images with different depth of focuses in the scene using several cameras. Due to the large amount of data generated by camera compared to other sensors such as pressure and temperature sensors and some limitation such as limited band width, energy consumption and processing time, it is essential to process the local input images to decrease the amount of transmission data. The aforementioned reasons emphasize the necessary of multi-focus images fusion. Multi-focus image fusion is a process which combines the input multi-focus images into a single image including all important information of the input images and it’s more accurate explanation of the scene than every single input image. == Applications == === In remote sensing === Image fusion in remote sensing has several application domains. An important domain is the multi-resolution image fusion (commonly referred to pan-sharpening). In satellite imagery we can have two types of images: Panchromatic images – An image collected in the broad visual wavelength range but rendered in black and white. Multispectral images – Images optically acquired in more than one spectral or wavelength interval. Each individual image is usually of the same physical area and scale but of a different spectral band. The SPOT PAN satellite provides high resolution (10m pixel) panchromatic data. While the LANDSAT TM satellite provides low resolution (30m pixel) multispectral images. Image fusion attempts to merge these images and produce a single high resolution multispectral image. The standard merging methods of image fusion are based on Red–Green–Blue (RGB) to Intensity–Hue–Saturation (IHS) transformation. The usual steps involved in satellite image fusion are as follows: Resize the low resolution multispectral images to the same size as the panchromatic image. Transform the R, G and B bands of the multispectral image into IHS components. Modify the panchromatic image with respect to the multispectral image. This is usually performed by histogram matching of the panchromatic image with Intensity component of the multispectral images as reference. Replace the intensity component by the panchromatic image and perform inverse transformation to obtain a high resolution multispectral image. Pan-sharpening can be done with Photoshop. Other applications of image fusion in remote sensing are available. === In medical imaging === Image fusion has become a common term used within medical diagnostics and treatment. The term is used when multiple images of a patient are registered and overlaid or merged to provide additional information. Fused images may be created from multiple images from the same imaging modality, or by combining information from multiple modalities, such as magnetic resonance image (MRI), computed tomography (CT), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). In radiology and radiation oncology, these images serve different purposes. For example, CT images are used more often to ascertain differences in tissue density while MRI images are typically used to diagnose brain tumors. For accurate diagnosis, radiologists must integrate information from multiple image formats. Fused, anatomically consistent images are especially beneficial in diagnosing and treating cancer. With the advent of these new technologies, radiation oncologists can take full advantage of intensity modulated radiation therapy (IMRT). Being able to overlay diagnostic images into radiation planning images results in more accurate IMRT target tumor volumes.
Temporal resolution
Temporal resolution (TR) refers to the discrete resolution of a measurement with respect to time. It is defined as the amount of time needed to revisit and acquire data for the same location. When applied to remote sensing, this amount of time is influenced by the sensor platform's orbital characteristics and the features of the sensor itself. The temporal resolution is low when the revisiting delay is high and vice versa. Temporal resolution is typically expressed in days. == Physics == Often there is a trade-off between the temporal resolution of a measurement and its spatial resolution, due to Heisenberg's uncertainty principle. In some contexts, such as particle physics, this trade-off can be attributed to the finite speed of light and the fact that it takes a certain period of time for the photons carrying information to reach the observer. In this time, the system might have undergone changes itself. Thus, the longer the light has to travel, the lower the temporal resolution. == Technology == === Computing === In another context, there is often a tradeoff between temporal resolution and computer storage. A transducer may be able to record data every millisecond, but available storage may not allow this, and in the case of 4D PET imaging the resolution may be limited to several minutes. === Electronic displays === In some applications, temporal resolution may instead be equated to the sampling period, or its inverse, the refresh rate, or update frequency in Hertz, of a TV, for example. The temporal resolution is distinct from temporal uncertainty. This would be analogous to conflating image resolution with optical resolution. One is discrete, the other, continuous. The temporal resolution is a resolution somewhat the 'time' dual to the 'space' resolution of an image. In a similar way, the sample rate is equivalent to the pixel pitch on a display screen, whereas the optical resolution of a display screen is equivalent to temporal uncertainty. Note that both this form of image space and time resolutions are orthogonal to measurement resolution, even though space and time are also orthogonal to each other. Both an image or an oscilloscope capture can have a signal-to-noise ratio, since both also have measurement resolution. === Oscilloscopy === An oscilloscope is the temporal equivalent of a microscope, and it is limited by temporal uncertainty the same way a microscope is limited by optical resolution. A digital sampling oscilloscope has also a limitation analogous to image resolution, which is the sample rate. A non-digital non-sampling oscilloscope is still limited by temporal uncertainty. The temporal uncertainty can be related to the maximum frequency of continuous signal the oscilloscope could respond to, called the bandwidth and given in Hertz. But for oscilloscopes, this figure is not the temporal resolution. To reduce confusion, oscilloscope manufacturers use 'Sa/s' instead of 'Hz' to specify the temporal resolution. Two cases for oscilloscopes exist: either the probe settling time is much shorter than the real time sampling rate, or it is much larger. The case where the settling time is the same as the sampling time is usually undesirable in an oscilloscope. It is more typical to prefer a larger ratio either way, or if not, to be somewhat longer than two sample periods. In the case where it is much longer, the most typical case, it dominates the temporal resolution. The shape of the response during the settling time also has as strong effect on the temporal resolution. For this reason probe leads usually offer an arrangement to 'compensate' the leads to alter the trade off between minimal settling time, and minimal overshoot. If it is much shorter, the oscilloscope may be prone to aliasing from radio frequency interference, but this can be removed by repeatedly sampling a repetitive signal and averaging the results together. If the relationship between the 'trigger' time and the sample clock can be controlled with greater accuracy than the sampling time, then it is possible to make a measurement of a repetitive waveform with much higher temporal resolution than the sample period by upsampling each record before averaging. In this case the temporal uncertainty may be limited by clock jitter.