AI Coding Neovim

AI Coding Neovim — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Unfold (app)

  Unfold is a mobile application that allows users to create social media content using a variety of templates and other tools. It was founded in 2018 by Alfonso Cobo and Andy McCune. It enables users to add photos, video, and text with a variety of tools. In 2019, Unfold was acquired by Squarespace. == History == In January 2017, Alfonso Cobo was studying at Parsons School of Design when he realized there was no software or app that could create a portfolio of his work on an iPad. Cobo created an app called Portfolio, a basic version of a portfolio layout app, and the first one to exist for iPad. He launched it in 2017. After launching the first version of Portfolio, Cobo realized the more popular market and use case was on mobile. Around that time, Instagram was launching Stories. As a result, Cobo pivoted the app away from portfolios and instead focused on an app to showcase one's stories. Cobo later contacted Andy McCune, founder of social media account Earth, to collaborate with Unfold. Unfold also partnered with various companies to create custom templates. These include Equinox, Tommy Hilfiger, NARS, Billboard Music Awards, and Product Red. Unfold also launched a collection of Product Red templates to help eliminate HIV/AIDS in several African countries. In 2019, Squarespace acquired Unfold. The Unfold app has been downloaded over 60 million times and has been used to create over 1 billion Instagram stories. == Features == With Unfold, users can utilize hundreds of templates to make social content for social media platforms such as Instagram, Snapchat, and Facebook. The free app offers users basic templates and standard fonts, filters, and stickers, and there are also premium templates available for a monthly subscription. With Unfold+ and Unfold Pro (previously Unfold for Brands), users can access premium templates and tools, as well as upload custom brand assets and fonts. In 2020, Unfold launched Bio Sites, which allows users to link to multiple sites and platforms.

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  Knapsack problem

  The knapsack problem is the following problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine which items to include in the collection so that the total weight is less than or equal to a given limit and the total value is as large as possible. It derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items. The problem often arises in resource allocation where the decision-makers have to choose from a set of non-divisible projects or tasks under a fixed budget or time constraint, respectively. The knapsack problem has been studied for more than a century, with early works dating back to 1897. The subset sum problem is a special case of the decision and 0-1 problems where for each kind of item, the weight equals the value: w i = v i {\displaystyle w_{i}=v_{i}} . In the field of cryptography, the term knapsack problem is often used to refer specifically to the subset sum problem. The subset sum problem is one of Karp's 21 NP-complete problems. == Applications == Knapsack problems appear in real-world decision-making processes in a wide variety of fields, such as finding the least wasteful way to cut raw materials, selection of investments and portfolios, selection of assets for asset-backed securitization, and generating keys for the Merkle–Hellman and other knapsack cryptosystems. One early application of knapsack algorithms was in the construction and scoring of tests in which the test-takers have a choice as to which questions they answer. For small examples, it is a fairly simple process to provide the test-takers with such a choice. For example, if an exam contains 12 questions each worth 10 points, the test-taker need only answer 10 questions to achieve a maximum possible score of 100 points. However, on tests with a heterogeneous distribution of point values, it is more difficult to provide choices. Feuerman and Weiss proposed a system in which students are given a heterogeneous test with a total of 125 possible points. The students are asked to answer all of the questions to the best of their abilities. Of the possible subsets of problems whose total point values add up to 100, a knapsack algorithm would determine which subset gives each student the highest possible score. A 1999 study of the Stony Brook University Algorithm Repository showed that, out of 75 algorithmic problems related to the field of combinatorial algorithms and algorithm engineering, the knapsack problem was the 19th most popular and the third most needed after suffix trees and the bin packing problem. == Definition == The most common problem being solved is the 0-1 knapsack problem, which restricts the number x i {\displaystyle x_{i}} of copies of each kind of item to zero or one. Given a set of n {\displaystyle n} items numbered from 1 up to n {\displaystyle n} , each with a weight w i {\displaystyle w_{i}} and a value v i {\displaystyle v_{i}} , along with a maximum weight capacity W {\displaystyle W} , maximize ∑ i = 1 n v i x i {\displaystyle \sum _{i=1}^{n}v_{i}x_{i}} subject to ∑ i = 1 n w i x i ≤ W {\displaystyle \sum _{i=1}^{n}w_{i}x_{i}\leq W} and x i ∈ { 0 , 1 } {\displaystyle x_{i}\in \{0,1\}} . Here x i {\displaystyle x_{i}} represents the number of instances of item i {\displaystyle i} to include in the knapsack. Informally, the problem is to maximize the sum of the values of the items in the knapsack so that the sum of the weights is less than or equal to the knapsack's capacity. The bounded knapsack problem (BKP) removes the restriction that there is only one of each item, but restricts the number x i {\displaystyle x_{i}} of copies of each kind of item to a maximum non-negative integer value c {\displaystyle c} : maximize ∑ i = 1 n v i x i {\displaystyle \sum _{i=1}^{n}v_{i}x_{i}} subject to ∑ i = 1 n w i x i ≤ W {\displaystyle \sum _{i=1}^{n}w_{i}x_{i}\leq W} and x i ∈ { 0 , 1 , 2 , … , c } . {\displaystyle x_{i}\in \{0,1,2,\dots ,c\}.} The unbounded knapsack problem (UKP) places no upper bound on the number of copies of each kind of item and can be formulated as above except that the only restriction on x i {\displaystyle x_{i}} is that it is a non-negative integer. maximize ∑ i = 1 n v i x i {\displaystyle \sum _{i=1}^{n}v_{i}x_{i}} subject to ∑ i = 1 n w i x i ≤ W {\displaystyle \sum _{i=1}^{n}w_{i}x_{i}\leq W} and x i ∈ N . {\displaystyle x_{i}\in \mathbb {N} .} One example of the unbounded knapsack problem is given using the figure shown at the beginning of this article and the text "if any number of each book is available" in the caption of that figure. == Computational complexity == The knapsack problem is interesting from the perspective of computer science for many reasons: The decision problem form of the knapsack problem (Can a value of at least V be achieved without exceeding the weight W?) is NP-complete, thus there is no known algorithm that is both correct and fast (polynomial-time) in all cases. There is no known polynomial algorithm which can tell, given a solution, whether it is optimal (which would mean that there is no solution with a larger V). This problem is co-NP-complete. There is a pseudo-polynomial time algorithm using dynamic programming. There is a fully polynomial-time approximation scheme, which uses the pseudo-polynomial time algorithm as a subroutine, described below. Many cases that arise in practice, and "random instances" from some distributions, can nonetheless be solved exactly. There is a link between the "decision" and "optimization" problems in that if there exists a polynomial algorithm that solves the "decision" problem, then one can find the maximum value for the optimization problem in polynomial time by applying this algorithm iteratively while increasing the value of k. On the other hand, if an algorithm finds the optimal value of the optimization problem in polynomial time, then the decision problem can be solved in polynomial time by comparing the value of the solution output by this algorithm with the value of k. Thus, both versions of the problem are of similar difficulty. One theme in research literature is to identify what the "hard" instances of the knapsack problem look like, or viewed another way, to identify what properties of instances in practice might make them more amenable than their worst-case NP-complete behaviour suggests. The goal in finding these "hard" instances is for their use in public-key cryptography systems, such as the Merkle–Hellman knapsack cryptosystem. More generally, better understanding of the structure of the space of instances of an optimization problem helps to advance the study of the particular problem and can improve algorithm selection. Furthermore, notable is the fact that the hardness of the knapsack problem depends on the form of the input. If the weights and profits are given as integers, it is weakly NP-complete, while it is strongly NP-complete if the weights and profits are given as rational numbers. However, in the case of rational weights and profits it still admits a fully polynomial-time approximation scheme. === Unit-cost models === The NP-hardness of the Knapsack problem relates to computational models in which the size of integers matters (such as the Turing machine). In contrast, decision trees count each decision as a single step. Dobkin and Lipton show an 1 2 n 2 {\displaystyle {1 \over 2}n^{2}} lower bound on linear decision trees for the knapsack problem, that is, trees where decision nodes test the sign of affine functions. This was generalized to algebraic decision trees by Steele and Yao. If the elements in the problem are real numbers or rationals, the decision-tree lower bound extends to the real random-access machine model with an instruction set that includes addition, subtraction and multiplication of real numbers, as well as comparison and either division or remaindering ("floor"). This model covers more algorithms than the algebraic decision-tree model, as it encompasses algorithms that use indexing into tables. However, in this model all program steps are counted, not just decisions. An upper bound for a decision-tree model was given by Meyer auf der Heide who showed that for every n there exists an O(n4)-deep linear decision tree that solves the subset-sum problem with n items. Note that this does not imply any upper bound for an algorithm that should solve the problem for any given n. == Solving == Several algorithms are available to solve knapsack problems, based on the dynamic programming approach, the branch and bound approach or hybridizations of both approaches. === Dynamic programming in-advance algorithm === The unbounded knapsack problem (UKP) places no restriction on the number of copies of each kind of item. Besides, here we assume that x i > 0 {\displaystyle x_{i}>0} m [ w ′ ] = max ( ∑ i = 1 n v i x i ) {\displaystyle m[w']=\max \left(\sum _{i=1}^{n}v_{i}x_{i}\right)} subject to ∑

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  Trace zero cryptography

  First proposed by Gerhard Frey in 1998, trace zero cryptography refers to the use of trace zero varieties (TZV) for cryptographic purpose. Trace zero varieties are subgroups of the divisor class group on a low genus hyperelliptic curve defined over a finite field. These groups can be used to establish asymmetric cryptography using the discrete logarithm problem as cryptographic primitive. Trace zero varieties feature a better scalar multiplication performance than elliptic curves. This allows fast arithmetic in these groups, which can speed up the calculations with a factor 3 compared with elliptic curves and hence speed up the cryptosystem. Another advantage is that for groups of cryptographically relevant size, the order of the group can simply be calculated using the characteristic polynomial of the Frobenius endomorphism. This is not the case, for example, in elliptic curve cryptography when the group of points of an elliptic curve over a prime field is used for cryptographic purpose. However, to represent an element of the trace zero variety more bits are needed compared with elements of elliptic or hyperelliptic curves. Another disadvantage is the fact that it is possible to reduce the security of the TZV of 1/6th of the bit length using cover attack. == Mathematical background == A hyperelliptic curve C of genus g over a prime field F q {\displaystyle \mathbb {F} _{q}} where q = pn (p prime) of odd characteristic is defined as C : y 2 + h ( x ) y = f ( x ) , {\displaystyle C:~y^{2}+h(x)y=f(x),} where f monic, deg(f) = 2g + 1 and deg(h) ≤ g. The curve has at least one F q {\displaystyle \mathbb {F} _{q}} -rational Weierstraßpoint. The Jacobian variety J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} of C is for all finite extension F q n {\displaystyle \mathbb {F} _{q^{n}}} isomorphic to the ideal class group Cl ⁡ ( C / F q n ) {\displaystyle \operatorname {Cl} (C/\mathbb {F} _{q^{n}})} . With the Mumford's representation it is possible to represent the elements of J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} with a pair of polynomials [u, v], where u, v ∈ F q n [ x ] {\displaystyle \mathbb {F} _{q^{n}}[x]} . The Frobenius endomorphism σ is used on an element [u, v] of J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} to raise the power of each coefficient of that element to q: σ([u, v]) = [uq(x), vq(x)]. The characteristic polynomial of this endomorphism has the following form: χ ( T ) = T 2 g + a 1 T 2 g − 1 + ⋯ + a g T g + ⋯ + a 1 q g − 1 T + q g , {\displaystyle \chi (T)=T^{2g}+a_{1}T^{2g-1}+\cdots +a_{g}T^{g}+\cdots +a_{1}q^{g-1}T+q^{g},} where ai in Z {\displaystyle \mathbb {Z} } With the Hasse–Weil theorem it is possible to receive the group order of any extension field F q n {\displaystyle \mathbb {F} _{q^{n}}} by using the complex roots τi of χ(T): | J C ( F q n ) | = ∏ i = 1 2 g ( 1 − τ i n ) {\displaystyle |J_{C}(\mathbb {F} _{q^{n}})|=\prod _{i=1}^{2g}(1-\tau _{i}^{n})} Let D be an element of the J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} of C, then it is possible to define an endomorphism of J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} , the so-called trace of D: Tr ⁡ ( D ) = ∑ i = 0 n − 1 σ i ( D ) = D + σ ( D ) + ⋯ + σ n − 1 ( D ) {\displaystyle \operatorname {Tr} (D)=\sum _{i=0}^{n-1}\sigma ^{i}(D)=D+\sigma (D)+\cdots +\sigma ^{n-1}(D)} Based on this endomorphism one can reduce the Jacobian variety to a subgroup G with the property, that every element is of trace zero: G = { D ∈ J C ( F q n ) | Tr ( D ) = 0 } , ( 0 neutral element in J C ( F q n ) {\displaystyle G=\{D\in J_{C}(\mathbb {F} _{q^{n}})~|~{\text{Tr}}(D)={\textbf {0}}\},~~~({\textbf {0}}{\text{ neutral element in }}J_{C}(\mathbb {F} _{q^{n}})} G is the kernel of the trace endomorphism and thus G is a group, the so-called trace zero (sub)variety (TZV) of J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} . The intersection of G and J C ( F q ) {\displaystyle J_{C}(\mathbb {F} _{q})} is produced by the n-torsion elements of J C ( F q ) {\displaystyle J_{C}(\mathbb {F} _{q})} . If the greatest common divisor gcd ( n , | J C ( F q ) | ) = 1 {\displaystyle \gcd(n,|J_{C}(\mathbb {F} _{q})|)=1} the intersection is empty and one can compute the group order of G: | G | = | J C ( F q n ) | | J C ( F q ) | = ∏ i = 1 2 g ( 1 − τ i n ) ∏ i = 1 2 g ( 1 − τ i ) {\displaystyle |G|={\dfrac {|J_{C}(\mathbb {F} _{q^{n}})|}{|J_{C}(\mathbb {F} _{q})|}}={\dfrac {\prod _{i=1}^{2g}(1-\tau _{i}^{n})}{\prod _{i=1}^{2g}(1-\tau _{i})}}} The actual group used in cryptographic applications is a subgroup G0 of G of a large prime order l. This group may be G itself. There exist three different cases of cryptographical relevance for TZV: g = 1, n = 3 g = 1, n = 5 g = 2, n = 3 == Arithmetic == The arithmetic used in the TZV group G0 based on the arithmetic for the whole group J C ( F q n ) {\displaystyle J_{C}(\mathbb {F} _{q^{n}})} , But it is possible to use the Frobenius endomorphism σ to speed up the scalar multiplication. This can be archived if G0 is generated by D of order l then σ(D) = sD, for some integers s. For the given cases of TZV s can be computed as follows, where ai come from the characteristic polynomial of the Frobenius endomorphism : For g = 1, n = 3: s = q − 1 1 − a 1 mod ℓ {\displaystyle s={\dfrac {q-1}{1-a_{1}}}{\bmod {\ell }}} For g = 1, n = 5: s = q 2 − q − a 1 2 q + a 1 q + 1 q − 2 a 1 q + a 1 3 − a 1 2 + a 1 − 1 mod ℓ {\displaystyle s={\dfrac {q^{2}-q-a_{1}^{2}q+a_{1}q+1}{q-2a_{1}q+a_{1}^{3}-a_{1}^{2}+a_{1}-1}}{\bmod {\ell }}} For g = 2, n = 3: s = − q 2 − a 2 + a 1 a 1 q − a 2 + 1 mod ℓ {\displaystyle s=-{\dfrac {q^{2}-a_{2}+a_{1}}{a_{1}q-a_{2}+1}}{\bmod {\ell }}} Knowing this, it is possible to replace any scalar multiplication mD (|m| ≤ l/2) with: m 0 D + m 1 σ ( D ) + ⋯ + m n − 1 σ n − 1 ( D ) , where m i = O ( ℓ 1 / ( n − 1 ) ) = O ( q g ) {\displaystyle m_{0}D+m_{1}\sigma (D)+\cdots +m_{n-1}\sigma ^{n-1}(D),~~~~{\text{where }}m_{i}=O(\ell ^{1/(n-1)})=O(q^{g})} With this trick the multiple scalar product can be reduced to about 1/(n − 1)th of doublings necessary for calculating mD, if the implied constants are small enough. == Security == The security of cryptographic systems based on trace zero subvarieties according to the results of the papers comparable to the security of hyper-elliptic curves of low genus g' over F p ′ {\displaystyle \mathbb {F} _{p'}} , where p' ~ (n − 1)(g/g' ) for |G| ~128 bits. For the cases where n = 3, g = 2 and n = 5, g = 1 it is possible to reduce the security for at most 6 bits, where |G| ~ 2256, because one can not be sure that G is contained in a Jacobian of a curve of genus 6. The security of curves of genus 4 for similar fields are far less secure. == Cover attack on a trace zero crypto-system == The attack published in shows, that the DLP in trace zero groups of genus 2 over finite fields of characteristic diverse than 2 or 3 and a field extension of degree 3 can be transformed into a DLP in a class group of degree 0 with genus of at most 6 over the base field. In this new class group the DLP can be attacked with the index calculus methods. This leads to a reduction of the bit length 1/6th.

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  Social media background check

  A social media background check is an investigative technique that involves scrutinizing the social media profiles and activities of individuals, primarily for pre-employment screening and other official verifications. These checks are performed to review people's online behavioral history on social media websites such as Facebook, Twitter, and LinkedIn. Social media background checks have become a common part of recruitment processes, among other verification procedures. == History == In the early 21st century, with the rapid expansion of social media platforms such as Facebook, Twitter, and LinkedIn, employers began to use these channels to gather additional information about prospective employees. Initially, social media background checks were an informal aspect of recruitment, but they have gradually gained formal recognition as a crucial element in candidate screening. Proponents of social media background checks argue that such reviews provide insight into a candidate's professional interests and networks, though the reliability of such assessments remains contested among researchers. == Rise in society == The practice of social media background checks has seen a significant surge in the last decade. This rise can be attributed to the exponential increase in social media users and the growing awareness among organizations regarding the importance of hiring individuals who align with their values and culture. Various platforms provide services explicitly designed to conduct social media background checks efficiently, simplifying the process for businesses. Companies providing social media background check services, such as Ferretly and Certn, have received venture capital funding, reflecting investor interest in the sector. The incorporation of artificial intelligence into conducting AI-powered social media background checks also illustrates its continued popularity and that businesses are looking to ramp up and even automate their use. High-profile cases in which individuals faced employment or admission consequences for past social media posts have raised awareness of social media background checking practices. For example, director James Gunn faced termination from Marvel Studios in 2018 over past offensive tweets, though he was later rehired. Additionally, multiple college admissions officers have acknowledged reviewing applicants' social media profiles, though such practices vary by institution. == Evolution of ethical considerations == Social media background checks are not without controversy, raising significant ethical considerations that have evolved in recent years. Privacy advocates argue that social media background checks raise concerns about data use and discrimination, particularly given the use of personal information that may not reflect job-relevant behavior. Legal scholars debate whether reviewing publicly posted information constitutes a privacy violation under U.S. law. Researchers and critics note that social media profiles often present curated representations of users' lives and may not reflect workplace behavior or professional competence. Moreover, the accuracy of social media background checks has been called into question, with critics pointing out that these checks may not always yield reliable or comprehensive results. Critics also warn about potential misuse of information obtained from social media, including cyberbullying and harassment. A 2023 study by found that approximately 90% of employers incorporate social media into hiring processes, with over half of those surveyed reporting they had rejected candidates based on social media content. This informal approach operates largely outside federal compliance frameworks. Critics argue that without regulation, candidates lack dispute mechanisms available under regulatory frameworks like the Fair Credit Reporting Act (FCRA), which requires compliance when background checks formally influence employment decisions. In a hiring environment where the practice is already performed often on an individual basis, the introduction of systematic, regulated screening practices that meet federal compliance standards can present a better, fairer alternative for both employers and candidates. == Business considerations == From a business perspective, social media background checks can be a valuable tool in protecting an organization's reputation and maintaining a safe and respectful workplace environment. A well-conducted social media background check can identify potential red flags, helping to prevent instances of workplace harassment or other negative behaviors. However, businesses also face potential legal repercussions if social media background checks are conducted improperly, such as non-compliance with the Fair Credit Reporting Act (FCRA) in the United States. Critics argue that over-reliance on social media data may exclude qualified candidates whose professional competence is not reflected in their online presence. The proliferation of social media screening services has prompted legal and industry experts to emphasize the importance of compliance with the Fair Credit Reporting Act and relevant state privacy laws when conducting such checks.

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  ViEWER

  ViEWER, the Virtual Environment Workbench for Education and Research, is a proprietary, freeware computer program for Microsoft Windows written by researchers at the University of Idaho for the study of visual perception and complex immersive three-dimensional environments. It was created using C++ and OpenGL, and has been used by Dr. Brian Dyre, Dr. Steffen Werner, Dr. Ernesto Bustamante, Dr. Ben Barton, and their undergraduate and graduate researchers in visual perception, signal detection, and child-safety experiments.

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  Radical trust

  Radical trust is the confidence that any structured organization, such as a government, library, business, religion, or museum, has in collaboration and empowerment within online communities. Specifically, it pertains to the use of blogs, wiki and online social networking platforms by organizations to cultivate relationships with an online community that then can provide feedback and direction for the organization's interest. The organization 'trusts' and uses that input in its management. One of the first appearances of the notion of radical trust appears in an info graphic outlining the base principles of web 2.0 in Tim O'Reilly's weblog post "What is Web 2.0". Radical Trust is listed as the guiding example of trusting the validity of consumer generated media. This concept is considered to be an underlying assumption of Library 2.0. The adoption of radical trust by a library would require its management let go of some of its control over the library and building an organization without an end result in mind. The direction a library would take would be based on input provided by people through online communities. These changes in the organization may merely be anecdotal in nature, making this method of organization management dramatically distinct from data-based or evidence based management. In marketing, Collin Douma further describes the notion of radical trust as a key mindset required for marketers and advertisers to enter the social media marketing space. Conventional marketing dictates and maintains control of messages to cause the greatest persuasion in consumer decisions, but Douma argued that in the social media space, brands would need to cede that control in order to build brand loyalty.

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  Social media measurement

  Social media measurement, also called social media controlling, is the management practice of evaluating successful social media communications of brands, companies, or other organizations. Key performance indicators may be measured by extracting information from social media channels, such as blogs, wikis, micro-blogs such as Twitter, social networking sites, or video/photo sharing websites, forums from time to time. It is also used by companies to gauge current trends in the industry. The process first gathers data from different websites and then performs analysis based on different metrics like time spent on the page, click through rate, content share, comments, text analytics to identify positive or negative emotions about the brand. Some other social media metrics include share of voice, owned mentions, and earned mentions. The social media measurement process starts with defining a goal that needs to be achieved and defining the expected outcome of the process. The expected outcome varies per the goal and is usually measured by a variety of metrics. This is followed by defining possible social strategies to be used to achieve the goal. Then the next step is designing strategies to be used and setting up configuration tools that ease the process of collecting the data. In the next step, strategies and tools are deployed in real-time. This step involves conducting Quality Assurance tests of the methods deployed to collect the data. And in the final step, data collected from the system is analyzed and if the need arises, it is refined on the run time to enhance the methodologies used. The last step ensures that the result obtained is more aligned with the goal defined in the first step. == Data Acquisition == Acquiring data from social media is in demand of an exploring the user participation and population with the purpose of retrieving and collecting so many kinds of data(ex: comments, downloads etc.). There are several prevalent techniques to acquire data such as Network traffic analysis, Ad-hoc application and Crawling Network Traffic Analysis - Network traffic analysis is the process of capturing network traffic and observing it closely to determine what is happening in the network. It is primarily done to improve the performance, security and other general management of the network. However concerned about the potential tort of privacy on the Internet, network traffic analysis is always restricted by the government. Furthermore, high-speed links are not adaptable to traffic analysis because of the possible overload problem according to the packet sniffing mechanism Ad-hoc Application - Ad-hoc application is a kind of application that provides services and games to social network users by developing the APIs offered by social network companies (Facebook Developer Platform). The infrastructure of Ad-hoc application allows the user to interact with the interface layer instead of the application servers. The API provides a path for application to access information after the user login. Moreover, the size of the data set collected vary with the popularity of the social media platform i.e. social media platforms having high number of users will have more data than platforms having less user base. Scraping is a process in which the APIs collect online data from social media. The data collected from Scraping is in raw format. However, having access to these types of data is a bit difficult because of its commercial value. Crawling - Crawling is a process in which a web crawler creates indexes of all the words in a web-page, stores them, then follows all the hyperlinks and indexes on that page and again stores them. It is the most popular technique for data acquisition and is also well known for its easy operation based on prevalent Object-Orientated Programming Language (Java or Python etc.). And most important, social network companies (YouTube, Flicker, Facebook, Instagram, etc.) are friendly to crawling techniques by providing public APIs == Applications == === For branding === Monitoring social media allows researchers to find insights into a brand's overall visibility on social media, to measure the impact of campaigns, to identify opportunities for engagement, to assess competitor activity and share of voice, and to detect impending crises. It can also provide valuable information about emerging trends and what consumers and clients think about specific topics, brands or products. This is the work of a cross-section of groups that include market researchers, PR staff, marketing teams, social-engagement, and community staff, agencies and sales teams. Several different providers have developed tools to facilitate the monitoring of a variety of social media channels - from blogging to internet video to internet forums. This allows companies to track what consumers say about their brands and actions. Companies can then react to these conversations and interact with consumers through social media platforms. === In government === Apart from commercial applications, social media monitoring has become a pervasive technique applied by public organizations and governments. Monitoring is a tradition within the public sector, and social-media monitoring provides a real-time approach to detecting and responding to social developments. Governments have come to realize the need for strategies to cope with surprises from the rapid expansion of public issues. Sobkowicz introduced a framework with three blocks of social-media opinion tracking, simulating and forecasting. It includes: real-time detection of emotions, topics and opinions information-flow modelling and agent-based simulation modeling of opinion networks Bekkers introduced the application of social media monitoring in the Netherlands. Public organizations in the Netherlands (such as the Tax Agency and the Education Ministry) have started to use social media monitoring to obtain better insights into the sentiments of target groups. On the one hand, the public sector will be enabled to provide timely and efficient answers to the public by using social media monitoring techniques, but on the other hand, they also have to deal with concerns about ethical issues such as transparency and privacy. == Quantifying social media == Social media management software (SMMS) is an application program or software that facilitates an organization's ability to successfully engage in social media across different communication channels. SMMS is used to monitor inbound and outbound conversations, support customer interaction, audit or document social marketing initiatives and evaluate the usefulness of a social media presence. It can be difficult to measure all social media conversations. Due to privacy settings and other issues, not all social media conversations can be found and reported by monitoring tools. However, whilst social media monitoring cannot give absolute figures, it can be extremely useful for identifying trends and for benchmarking, in addition to the uses mentioned above. These findings can, in turn, influence and shape future business decisions. In order to access social media data (posts, Tweets, and meta-data) and to analyze and monitor social media, many companies use software technologies built for business. These range from in-platform analytics dashboards to dedicated third-party platforms, which offer more advanced capabilities including cross-platform audience intelligence, sentiment analysis, and trend detection at scale. == Location-based == Most social media networks allow users to add a location to their posts (reference all of our feeds). The location can be classified as either 'at-the-location' or 'about-the-location'. "'At-the-location' services can be defined as services where location-based content is created at the geographic location. 'About-the-location' services can be defined as services which are referring to a particular location but the content is not necessarily created in this particular physical place." The added information available from geotagged (link to Geotagging article) posts means that they can be displayed on a map. This means that a location can be used as the start of a social media search rather than a keyword or hashtag. This has major implications for disaster relief, event monitoring, safety and security professionals since a large portion of their job is related to tracking and monitoring specific locations. == Technologies used == Various monitoring platforms use different technologies for social media monitoring and measurement. These technology providers may connect to the API provided by social platforms that are created for 3rd party developers to develop their own applications and services that access data. Facebook's Graph API is one such API that social media monitoring solution products would connect to pull data from. Some social media monitoring and analytics companies use calls to data providers each time an end-user d

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  Cloud Data Management Interface

  ISO/IEC 17826 Information technology — Cloud Data Management Interface (CDMI) Version 2.0.0 is an international standard that specifies a protocol for self-provisioning, administering and managing access to data stored in cloud storage, object storage, storage area network and network attached storage systems. The CDMI standard is developed and maintained by the Storage Networking Industry Association, who makes a publicly accessible version of the specification available. CDMI defines new resource representations to enable standardized management of any URI-accessible data, and defines RESTful HTTP operations using these representations to discover the capabilities of the storage system, discover stored data, access and update management metadata, specify data storage protocols (such as iSCSI and NFS) through which the stored data is accessed, and provide cross-system and cross-cloud import and export in order to enable data portability. Management functions enabled by CDMI include managing data ownership, identity mapping, access controls, user-specified metadata, and to declaratively specify desired data protection, data retention, constraints on geographic placement, desired quality of service, data versioning and security requirements. CDMI also defines utility services to facilitate data management, such the ability to query data matching specific criteria, and includes extensions to perform bulk updates using CDMI Jobs. == Capabilities == Compliant implementations must provide access to a set of configuration parameters known as capabilities. These are either boolean values that represent whether or not a system supports things such as queues, export via other protocols, path-based storage and so on, or numeric values expressing system limits, such as how much metadata may be placed on an object. As a minimal compliant implementation can be quite small, with few features, clients need to check the cloud storage system for a capability before attempting to use the functionality it represents. Resource allocation assignments limited to the data management interface protocols must possess access bypass capabilities which extend beyond the layered framework. This integral function is vital to the prevention of transport layer session hijacking by unauthorized entities which may circumvent standard interfacing security parameters. == Containers == A CDMI client may access objects, including containers, by either name or object id (OID), assuming the CDMI server supports both methods. When storing objects by name, it is natural to use nested named containers; the resulting structure corresponds exactly to a traditional filesystem directory structure. == Objects == Objects are similar to files in a traditional file system, but are enhanced with an increased amount and capacity for metadata. As with containers, they may be accessed by either name or OID. When accessed by name, clients use URLs that contain the full pathname of objects to create, read, update and delete them. When accessed by OID, the URL specifies an OID string in the cdmi-objectid container; this container presents a flat name space conformant with standard object storage system semantics. Subject to system limits, objects may be of any size or type and have arbitrary user-supplied metadata attached to them. Systems that support query allow arbitrary queries to be run against the metadata. == Domains, Users and Groups == CDMI supports the concept of a domain, similar in concept to a domain in the Windows Active Directory model. Users and groups created in a domain share a common administrative database and are known to each other on a "first name" basis, i.e. without reference to any other domain or system. Domains also function as containers for usage and billing summary data. == Access Control == CDMI exactly follows the ACL and ACE model used for file authorization operations by NFSv4. This makes it also compatible with Microsoft Windows systems. == Metadata == CDMI draws much of its metadata model from the XAM specification. Objects and containers have "storage system metadata", "data system metadata" and arbitrary user specified metadata, in addition to the metadata maintained by an ordinary filesystem (atime etc.). == Queries == CDMI specifies a way for systems to support arbitrary queries against CDMI containers, with a rich set of comparison operators, including support for regular expressions. == Queues == CDMI supports the concept of persistent FIFO (first-in, first-out) queues. These are useful for job scheduling, order processing and other tasks in which lists of things must be processed in order. == Compliance == Both retention intervals and retention holds are supported by CDMI. A retention interval consists of a start time and a retention period. During this time interval, objects are preserved as immutable and may not be deleted. A retention hold is usually placed on an object because of judicial action and has the same effect: objects may not be changed nor deleted until all holds placed on them are removed. == Billing == Summary information suitable for billing clients for on-demand services can be obtained by authorized users from systems that support it. == Serialization == Serialization of objects and containers allows export of all data and metadata on a system and importation of that data into another cloud system. == Foreign protocols == CDMI supports export of containers as NFS or CIFS shares. Clients that mount these shares see the container hierarchy as an ordinary filesystem directory hierarchy, and the objects in the containers as normal files. Metadata outside of ordinary filesystem metadata may or may not be exposed. Provisioning of iSCSI LUNs is also supported. == Client SDKs == CDMI Reference Implementation Droplet libcdmi-java libcdmi-python .NET SDK

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  TAPPS2

  TAPPS2 (Technische Alternative Planungs- und Programmier-System) is a tool used for developing the program logic for the universal, heating and solar thermal controllers by Austrian manufacturer Technische Alternative. Its primary usecase is defining the exact reaction of the controller to a certain event. Other than its predecessor, TAPPS, which could only be used to program controllers of type UVR1611, TAPPS2 is mainly used to program the UVR16x2 and RSM610 controllers, as well as several extension modules. == Development == Development in TAPPS2 is done on a vector-based drawing surface using components that can be placed via drag and drop. The components, which can be separated into inputs, functions and outputs are then being connected according to their individual features. Available components vary according to the current solar thermal control unit.

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  Atomicity (database systems)

  In database systems, atomicity (; from Ancient Greek: ἄτομος, romanized: átomos, lit. 'undividable') is the property of a database transaction consisting of an indivisible and irreducible series of database operations such that either all occur, or none occur. It is one of the ACID transaction properties: Atomicity, Consistency, Isolation, Durability. A guarantee of atomicity prevents partial database updates from occurring, because they can cause greater problems than rejecting the whole series outright. As a consequence, an atomic transaction cannot be observed to be in progress by another database client: at one moment in time, it has not yet happened, and at the next it has already occurred in whole (or nothing happened if the transaction was cancelled in progress). An example of transaction atomicity could be a digital monetary transfer from bank account A to account B. It consists of two operations, debiting the money from account A and crediting it to account B. Performing both of these operations inside of an atomic transaction ensures that the database remains in a consistent state, if either operation fails there will not be any unaccountable credits or debits affecting either account. The same term is also used in the definition of First normal form in database systems, where it instead refers to the concept that the values for fields may not consist of multiple smaller values to be decomposed, such as a string into which multiple names, numbers, dates, or other types may be packed. == Orthogonality == Atomicity does not behave completely orthogonally with regard to the other ACID properties of transactions. For example, isolation relies on atomicity to roll back the enclosing transaction in the event of an isolation violation such as a deadlock; consistency also relies on atomicity to roll back the enclosing transaction in the event of a consistency violation by an illegal transaction. As a result of this, a failure to detect a violation and roll back the enclosing transaction may cause an isolation or consistency failure. == Implementation == Typically, systems implement Atomicity by providing some mechanism to indicate which transactions have started and which finished; or by keeping a copy of the data before any changes occurred (Read-copy-update). Several filesystems have developed methods for avoiding the need to keep multiple copies of data, using journaling (see journaling file system). Databases usually implement this using some form of logging/journaling to track changes. The system synchronizes the logs (often the metadata) as necessary after changes have successfully taken place. Afterwards, crash recovery ignores incomplete entries. Although implementations vary depending on factors such as concurrency issues, the principle of atomicity – i.e. complete success or complete failure – remain. Ultimately, any application-level implementation relies on operating-system functionality. At the file-system level, POSIX-compliant systems provide system calls such as open(2) and flock(2) that allow applications to atomically open or lock a file. At the process level, POSIX Threads provide adequate synchronization primitives. The hardware level requires atomic operations such as Test-and-set, Fetch-and-add, Compare-and-swap, or Load-Link/Store-Conditional, together with memory barriers. Portable operating systems cannot simply block interrupts to implement synchronization, since hardware that lacks concurrent execution such as hyper-threading or multi-processing is now extremely rare. In distributed and sharded databases, atomicity is complicated by network latency and the potential for partial failures. While traditional distributed systems often employ locking protocols (like 2PC) to ensure cross-shard atomicity, these can introduce performance bottlenecks. Recent research into distributed ledger consensus suggests alternative models, such as "braided synchronization". This technique, utilized in protocols like Cerberus, intertwines the consensus phases of multiple shards to enforce atomic guarantees without a global ordering of all transactions.

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  Social media use in African politics

  Since the Egyptian Revolution in 2011 and the Tunisian Revolution, social media, especially Facebook, Twitter, and YouTube, began to gain traction as a political tool in Africa. Various political actors have used social media to pursue a wide range of political objectives. State actors can use social media to encourage political discourse, campaign, or implement censorship and surveillance. Non-state actors, such as civil society organizations and opposition movements, can use social media to address political concerns and to organize widespread uprisings, such as the 2014 Burkinabé uprising. Meanwhile, extremist organizations can use social media to further their propaganda and recruitment. However, social media has been criticized for its limited accessibility and for facilitating the spread of misinformation, causing some skepticism about its effectiveness. Due to low entry barriers and user-generated content, social media provides a platform where people from different social classes can engage and interact with one another. Under traditional media, the public had limited opportunities to voice their political opinions. Social media enables people to both create and consume content. The public has become increasingly comfortable and confident in expressing political opinions online, often away from government scrutiny. Scholars argue that social media use has democratizing effects in African countries. == State actors == === Promoting political discourse === Through social media, the government and its citizens can discuss policy ideas, policy implementation, and political actions. Regardless of geographical location and distance, people are able to voice their opinions to the government. Social media includes citizens who were previously not able to express their discontent or share their ideas to the government. As state actors keep the public informed, social media can increase civic engagement. With more civic engagement, policies can be discussed without politicization. Before the commonplace use of social media, African countries faced weak feedback mechanisms that effectively excluded the average African citizen from policy discourse. In South Africa, the government uses social media to connect with constituencies. The South African president runs an official Twitter, Facebook, YouTube, and Flickr accounts to engage with the public. === Campaigning === Political parties also use social media for political campaigns during election periods. In South Africa, the ANC (African National Congress) and DA (Democratic Alliance) use social media for political purposes. These parties specifically use Facebook as a tool for campaigning and engaging with the public to improve their relationship with citizens. Nigerian President Goodluck Jonathan employed social media to campaign for the presidential election in 2011, which he won. When President Goodluck Jonathan announced his bid for the presidency on social media in 2010, it reached about 217,000 people. As his campaign progressed, President Goodluck Jonathan was able to increase his followers to half a million by early 2011. === Censorship & Surveillance === While state actors can use social media to encourage their party or discourse, social media can be used to censor and surveil citizens. For example, the ANC and DA use Facebook to monitor South Africans. The government is able to track down people who have spoken against the government and translate this information into physical action to stop any possibility of a revolution. Social media platforms can be shut down to manipulate the flow of information. In Chad, citizens cannot access information through online platforms. This censorship blocked "Facebook, Twitter, WhatsApp and Viber". In the Democratic Republic of Congo, the government shut down the internet before contested elections. In Zimbabwe, the government shut down the internet to hide civilian protests against fuel price increases. == Non-state actors == === Civil society organizations (CSOs) === Civil society organizations have also used social media networks in an effort to recruit supporters and communicate with the public. CSOs can use social media to mobilize people to support their cause, such as the Ghanaian Committee for Joint Action (CJA). In 2005 and 2006, the CJA gathered support to protest against the 50% fuel price increase. CSOs can play the role of a counterforce against state actors and state propaganda during times of crises, such as protests and military clashes. In some cases, CSOs release their own videos and photos on social media which challenges traditional forms of media. CSOs have also served to monitor elections to reduce corruption and violence during election day. For instance, the Zambian Bantu Watch started the #bantuwatch social media campaign to monitor the 2011 presidential election. Zambians used Facebook and Twitter to report polling station results to mitigate election fraud and election violence. In South Africa, CSOs created 'amandla.mobi' to campaign for public policies by creating petitions. Through 'amandla.mobi', CSOs are able to circulate petitions on social media to collect signatures. South African CSOs reported how social media helped their organizations to gain support and share ideas. However, CSOs struggle to attract media attention and often have to pay for media coverage. === Opposition forces against the government === Social media is also used by the public or opposition forces against the government. Through horizontal social media, organizing can lead to street protests and revolutions, some of which are successful. For instance, during the Egyptian revolution of 2011, "The Day of the Revolution Against Torture, Poverty, Corruption, and Unemployment" and "We Are All Khaled Said" gathered support against President Hosni Mubarak. In particular, "We Are All Khaled Said" had Egyptian citizens gather around the death of Khaled Said who was brutally tortured and killed by the Egyptian government because Said wanted to uncover government corruption. As unrest erupted into public demonstrations, President Hosni Mubarak was forced to resign. Witnessing the success of social media during the Egyptian revolution, the Tunisian Revolution, or the Jasmine Revolution, mobilized through Facebook and Twitter. Likewise, in South Africa, Malawi, and Mozambique, these countries have used social media as "new protest drums." Due to social media's low entry barrier, opposition forces against the government can facilitate political discourse that can lead to accountability. Whistleblowers and opposition forces are able to expose corruption through social media, where they face less repression while reaching a larger audience. For example, the youth of Zimbabwe and South Africa use Facebook to discuss politics without judgment. Specifically, in Zimbabwe, political youth used Facebook to avoid state surveillance. Social media is used as a supplemental tool for activism. In 2015, South African student activists started the hashtag #RhodesMustFall to push the issue of colonialism and racism at the forefront of the public. === Extremist organizations === Social media is easily accessible and created by user-based content. Therefore, marginalized groups are able to use social media to spread extremist ideas. For instance, Boko Haram created the Media Office of West Africa Province and perpetuated propaganda through Twitter and YouTube. Boko Haram's online propaganda campaign targets and persuades young dissuaded Nigerians to join their cause. It is important to note that social media has also been used against Boko Haram. In April 2014, Boko Haram kidnapped 276 schoolgirls and an international campaign fought for their return through #BringBackOurGirls. Another extremist group, Al-Shabaab, has created an online presence through Twitter and YouTube. Through these social media networks, Al-Shabaab recruits new members to their extremist group through their propaganda which emphasizes the group's successes. Albeit their efforts, Al-Shabaab has not been very successful in coordinating their members but they are successful in financing their group. Furthermore, the Islamic State of Iraq and the Levant (ISIL) use social media to target and recruit individuals to their cause. ISIL's social media usage is more diverse compared to Boko Haram and Al-Shabaab; ISIL uses "Facebook, Twitter, YouTube, WhatsApp, Telegram, JustPaste.it, Kik and Ask.fm." Since ISIL's Twitter accounts kept getting shut down, ISIL uses Telegram and WhatsApp chat rooms to privately conduct meetings. Due to the spread of extremist ideology, Zhuravskaya et al. acknowledge social media's potential to be misused. == Challenges == Although social media can be used as a political tool, it faces challenges in Africa. Due to low literacy rates in Africa, social media networks exclude many of the population members. In addition, lack of access to electricity and the internet can fur

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  Signals intelligence

  Signals intelligence (SIGINT) is the act and field of intelligence-gathering by interception of signals, whether communications between people (communications intelligence—abbreviated to COMINT) or from electronic signals not directly used in communication (electronic intelligence—abbreviated to ELINT). As classified and sensitive information is usually encrypted, signals intelligence may necessarily involve cryptanalysis (to decipher the messages). Traffic analysis—the study of who is signaling to whom and in what quantity—is also used to integrate information, and it may complement cryptanalysis. == History == === Origins === Electronic interceptions appeared as early as 1900, during the Boer War of 1899–1902. The British Royal Navy had installed wireless sets produced by Marconi on board their ships in the late 1890s, and the British Army used some limited wireless signalling. The Boers captured some wireless sets and used them to make vital transmissions. Since the British were the only people transmitting at the time, the British did not need special interpretation of the signals that they were. The birth of signals intelligence in a modern sense dates from the Russo-Japanese War of 1904–1905. As the Russian fleet prepared for conflict with Japan in 1904, the British ship HMS Diana stationed in the Suez Canal intercepted Russian naval wireless signals being sent out for the mobilization of the fleet, for the first time in history. === Development in World War I === Over the course of the First World War, a new method of signals intelligence reached maturity. Russia's failure to properly protect its communications fatally compromised the Russian Army's advance early in World War I and led to their disastrous defeat by the Germans under Ludendorff and Hindenburg at the Battle of Tannenberg. In 1918, French intercept personnel captured a message written in the new ADFGVX cipher, which was cryptanalyzed by Georges Painvin. This gave the Allies advance warning of the German 1918 Spring Offensive. The British in particular, built up great expertise in the newly emerging field of signals intelligence and codebreaking (synonymous with cryptanalysis). On the declaration of war, Britain cut all German undersea cables. This forced the Germans to communicate exclusively via either (A) a telegraph line that connected through the British network and thus could be tapped; or (B) through radio which the British could then intercept. Rear Admiral Henry Oliver appointed Sir Alfred Ewing to establish an interception and decryption service at the Admiralty; Room 40. An interception service known as 'Y' service, together with the post office and Marconi stations, grew rapidly to the point where the British could intercept almost all official German messages. The German fleet was in the habit each day of wirelessing the exact position of each ship and giving regular position reports when at sea. It was possible to build up a precise picture of the normal operation of the High Seas Fleet, to infer from the routes they chose where defensive minefields had been placed and where it was safe for ships to operate. Whenever a change to the normal pattern was seen, it immediately signalled that some operation was about to take place, and a warning could be given. Detailed information about submarine movements was also available. The use of radio-receiving equipment to pinpoint the location of any single transmitter was also developed during the war. Captain H.J. Round, working for Marconi, began carrying out experiments with direction-finding radio equipment for the army in France in 1915. By May 1915, the Admiralty was able to track German submarines crossing the North Sea. Some of these stations also acted as 'Y' stations to collect German messages, but a new section was created within Room 40 to plot the positions of ships from the directional reports. Room 40 played an important role in several naval engagements during the war, notably in detecting major German sorties into the North Sea. The battle of Dogger Bank was won in no small part due to the intercepts that allowed the Navy to position its ships in the right place. It played a vital role in subsequent naval clashes, including at the Battle of Jutland as the British fleet was sent out to intercept them. The direction-finding capability allowed for the tracking and location of German ships, submarines, and Zeppelins. The system was so successful that by the end of the war, over 80 million words, comprising the totality of German wireless transmission over the course of the war, had been intercepted by the operators of the Y-stations and decrypted. However, its most astonishing success was in decrypting the Zimmermann Telegram, a telegram from the German Foreign Office sent via Washington to its ambassador Heinrich von Eckardt in Mexico. === Postwar consolidation === With the importance of interception and decryption firmly established by the wartime experience, countries established permanent agencies dedicated to this task in the interwar period. In 1919, the British Cabinet's Secret Service Committee, chaired by Lord Curzon, recommended that a peace-time codebreaking agency should be created. The Government Code and Cypher School (GC&CS) was the first peace-time codebreaking agency, with a public function "to advise as to the security of codes and cyphers used by all Government departments and to assist in their provision", but also with a secret directive to "study the methods of cypher communications used by foreign powers". GC&CS officially formed on 1 November 1919, and produced its first decrypt on 19 October. By 1940, GC&CS was working on the diplomatic codes and ciphers of 26 countries, tackling over 150 diplomatic cryptosystems. The US Cipher Bureau was established in 1919 and achieved some success at the Washington Naval Conference in 1921, through cryptanalysis by Herbert Yardley. Secretary of War Henry L. Stimson closed the US Cipher Bureau in 1929 with the words "Gentlemen do not read each other's mail." === World War II === The use of SIGINT had even greater implications during World War II. The combined effort of intercepts and cryptanalysis for the whole of the British forces in World War II came under the code name "Ultra", managed from Government Code and Cypher School at Bletchley Park. Properly used, the German Enigma and Lorenz ciphers should have been virtually unbreakable, but flaws in German cryptographic procedures, and poor discipline among the personnel carrying them out, created vulnerabilities which made Bletchley's attacks feasible. Bletchley's work was essential to defeating the U-boats in the Battle of the Atlantic, and to the British naval victories in the Battle of Cape Matapan and the Battle of North Cape. In 1941, Ultra exerted a powerful effect on the North African desert campaign against German forces under General Erwin Rommel. General Sir Claude Auchinleck wrote that were it not for Ultra, "Rommel would have certainly got through to Cairo". Ultra decrypts featured prominently in the story of Operation SALAM, László Almásy's mission across the desert behind Allied lines in 1942. Prior to the Normandy landings on D-Day in June 1944, the Allies knew the locations of all but two of Germany's fifty-eight Western Front divisions. Winston Churchill was reported to have told King George VI: "It is thanks to the secret weapon of General Menzies, put into use on all the fronts, that we won the war!" Supreme Allied Commander, Dwight D. Eisenhower, at the end of the war, described Ultra as having been "decisive" to Allied victory. Official historian of British Intelligence in World War II Sir Harry Hinsley argued that Ultra shortened the war "by not less than two years and probably by four years"; and that, in the absence of Ultra, it is uncertain how the war would have ended. At a lower level, German cryptanalysis, direction finding, and traffic analysis were vital to Rommel's early successes in the Western Desert Campaign until British forces tightened their communications discipline and Australian raiders destroyed his principal SIGINT Company. == Technical definitions == The United States Department of Defense has defined the term "signals intelligence" as: A category of intelligence comprising either individually or in combination all communications intelligence (COMINT), electronic intelligence (ELINT), and foreign instrumentation signals intelligence (FISINT), however transmitted. Intelligence derived from communications, electronic, and foreign instrumentation signals. Being a broad field, SIGINT has many sub-disciplines. The two main ones are communications intelligence (COMINT) and electronic intelligence (ELINT). == Disciplines shared across the branches == === Targeting === A collection system has to know to look for a particular signal. "System", in this context, has several nuances. Targeting is the process of developing collection requirements: "1. A

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  Manual override

  A manual override (MO) or manual analog override (MAO) is a mechanism where control is taken from an automated system and given to the user. For example, a manual override in photography refers to the ability for the human photographer to turn off the automatic aperture sizing, automatic focusing, or any other automated system on the camera. Some manual overrides can be used to veto an automated system's judgment when the system is in error. An example of this is a printer's ink level detection: in one case, a researcher found that when he overrode the system, up to 38% more pages could be printed at good quality by the printer than the automated system would have allowed. Automated systems are becoming increasingly common and integrated into everyday objects such as automobiles and domestic appliances. This development of ubiquitous computing raises general issues of policy and law about the need for manual overrides for matters of great importance such as life-threatening situations and major economic decisions. The loyalty of such autonomous devices then becomes an issue. If they follow rules installed by the manufacturer or required by law and refuse to cede control in some situations then the owners of the devices may feel disempowered, alienated and lacking true ownership. == Major incidents == China Airlines Flight 140 crashed, causing many deaths, due to a misunderstanding about the manual overrides for the autopilot. The Take-Off/Go Around system had been activated to abort a landing. It was programmed to ignore manual controls in this situation but the human pilots tried to continue the landing. The conflicting control signals from the pilots and autopilot then resulted in the aircraft stalling and crashing. The autopilot for this aircraft type was then reprogrammed so that it would never ignore a manual override.

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  Computer network

  In computer science, computer engineering, and telecommunications, a network is a group of communicating computers and peripherals known as hosts, which communicate data to other hosts via communication protocols, as facilitated by networking hardware. Within a computer network, hosts are identified by network addresses, which allow networking hardware to locate and identify hosts. Hosts may also have hostnames, memorable labels for the host nodes, which can be mapped to a network address using a hosts file or a name server such as Domain Name Service. The physical medium that supports information exchange includes wired media like copper cables, optical fibers, and wireless radio-frequency media. The arrangement of hosts and hardware within a network architecture is known as the network topology. The first computer network was created in 1940 when George Stibitz connected a terminal at Dartmouth to his Complex Number Calculator at Bell Labs in New York. Today, almost all computers are connected to a computer network, such as the global Internet or embedded networks such as those found in many modern electronic devices. Many applications have only limited functionality unless they are connected to a network. Networks support applications and services, such as access to the World Wide Web, digital video and audio, application and storage servers, printers, and email and instant messaging applications. == History == === Early origins (1940 – 1960s) === In 1940, George Stibitz of Bell Labs connected a teletype at Dartmouth to a Bell Labs computer running his Complex Number Calculator to demonstrate the use of computers at long distance. This was the first real-time, remote use of a computing machine. In the late 1950s, a network of computers was built for the U.S. military Semi-Automatic Ground Environment (SAGE) radar system using the Bell 101 modem. It was the first commercial modem for computers, released by AT&T Corporation in 1958. The modem allowed digital data to be transmitted over regular unconditioned telephone lines at a speed of 110 bits per second (bit/s). In 1959, Christopher Strachey filed a patent application for time-sharing in the United Kingdom and John McCarthy initiated the first project to implement time-sharing of user programs at MIT. Strachey passed the concept on to J. C. R. Licklider at the inaugural UNESCO Information Processing Conference in Paris that year. McCarthy was instrumental in the creation of three of the earliest time-sharing systems (the Compatible Time-Sharing System in 1961, the BBN Time-Sharing System in 1962, and the Dartmouth Time-Sharing System in 1963). In 1959, Anatoly Kitov proposed to the Central Committee of the Communist Party of the Soviet Union a detailed plan for the re-organization of the control of the Soviet armed forces and of the Soviet economy on the basis of a network of computing centers. Kitov's proposal was rejected, as later was the 1962 OGAS economy management network project. During the 1960s, Paul Baran and Donald Davies independently invented the concept of packet switching for data communication between computers over a network. Baran's work addressed adaptive routing of message blocks across a distributed network, but did not include routers with software switches, nor the idea that users, rather than the network itself, would provide the reliability. Davies' hierarchical network design included high-speed routers, communication protocols and the essence of the end-to-end principle. The NPL network, a local area network at the National Physical Laboratory (United Kingdom), pioneered the implementation of the concept in 1968-69 using 768 kbit/s links. Both Baran's and Davies' inventions were seminal contributions that influenced the development of computer networks. === ARPANET (1969 – 1974) === In 1962 and 1963, J. C. R. Licklider sent a series of memos to office colleagues discussing the concept of the "Intergalactic Computer Network", a computer network intended to allow general communications among computer users. This ultimately became the basis for the ARPANET, which began in 1969. That year, the first four nodes of the ARPANET were connected using 50 kbit/s circuits between the University of California at Los Angeles, the Stanford Research Institute, the University of California, Santa Barbara, and the University of Utah. Designed principally by Bob Kahn, the network's routing, flow control, software design and network control were developed by the IMP team working for Bolt Beranek & Newman. In the early 1970s, Leonard Kleinrock carried out mathematical work to model the performance of packet-switched networks, which underpinned the development of the ARPANET. His theoretical work on hierarchical routing in the late 1970s with student Farouk Kamoun remains critical to the operation of the Internet today. In 1973, Peter Kirstein put internetworking into practice at University College London (UCL), connecting the ARPANET to British academic networks, the first international heterogeneous computer network. That same year, Robert Metcalfe wrote a formal memo at Xerox PARC describing Ethernet, a local area networking system he created with David Boggs. It was inspired by the packet radio ALOHAnet, started by Norman Abramson and Franklin Kuo at the University of Hawaii in the late 1960s. Metcalfe and Boggs, with John Shoch and Edward Taft, also developed the PARC Universal Packet for internetworking. That year, the French CYCLADES network, directed by Louis Pouzin was the first to make the hosts responsible for the reliable delivery of data, rather than this being a centralized service of the network itself. === The internet (1974 – present) === In 1974, Vint Cerf and Bob Kahn published their seminal 1974 paper on internetworking, A Protocol for Packet Network Intercommunication. Later that year, Cerf, Yogen Dalal, and Carl Sunshine wrote the first Transmission Control Protocol (TCP) specification, RFC 675, coining the term Internet as a shorthand for internetworking. In July 1976, Metcalfe and Boggs published their paper "Ethernet: Distributed Packet Switching for Local Computer Networks" and in December 1977, together with Butler Lampson and Charles P. Thacker, they received U.S. patent 4063220A for their invention. In 1976, John Murphy of Datapoint Corporation created ARCNET, a token-passing network first used to share storage devices. In 1979, Robert Metcalfe pursued making Ethernet an open standard. In 1980, Ethernet was upgraded from the original 2.94 Mbit/s protocol to the 10 Mbit/s protocol, which was developed by Ron Crane, Bob Garner, Roy Ogus, Hal Murray, Dave Redell and Yogen Dalal. In 1986, the National Science Foundation (NSF) launched the National Science Foundation Network (NSFNET) as a general-purpose research network connecting various NSF-funded sites to each other and to regional research and education networks. In 1995, the transmission speed capacity for Ethernet increased from 10 Mbit/s to 100 Mbit/s. By 1998, Ethernet supported transmission speeds of 1 Gbit/s. Subsequently, higher speeds of up to 800 Gbit/s were added (as of 2025). The scaling of Ethernet has been a contributing factor to its continued use. In the 1980s and 1990s, as embedded systems were becoming increasingly important in factories, cars, and airplanes, network protocols were developed to allow the embedded computers to communicate. In the late 1990s and 2000s, ubiquitous computing and an Internet of Things became popular. === Commercial usage === In 1960, the commercial airline reservation system semi-automatic business research environment (SABRE) went online with two connected mainframes. In 1965, Western Electric introduced the first widely used telephone switch that implemented computer control in the switching fabric. In 1972, commercial services were first deployed on experimental public data networks in Europe. Public data networks in Europe, North America and Japan began using X.25 in the late 1970s and interconnected with X.75. This underlying infrastructure was used for expanding TCP/IP networks in the 1980s. In 1977, the first long-distance fiber network was deployed by GTE in Long Beach, California. == Hardware == === Network links === The transmission media used to link devices to form a computer network include electrical cable, optical fiber, and free space. In the OSI model, the software to handle the media is defined at layers 1 and 2 — the physical layer and the data link layer. Common examples of networking technologies include: Ethernet is a widely adopted family of networking technologies that use copper and fiber media in local area networks (LAN). The media and protocol standards that enable communication between networked devices over Ethernet are defined by IEEE 802.3. Wireless LAN standards, which use radio waves. Some standards use infrared signals as a transmission medium. Power line communication uses a building's power cabling to transmit

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  Instant messaging

  Instant messaging (IM) technology is a type of synchronous computer-mediated communication involving the immediate (real-time) transmission of messages between two or more parties over the Internet or another computer network. Originally involving simple text message exchanges, modern instant messaging applications and services (also variously known as instant messenger, messaging app, chat app, chat client, or simply a messenger) tend to also feature the exchange of multimedia, emojis, file transfer, VoIP (voice calling), and video chat capabilities. Instant messaging systems facilitate connections between specified known users (often using a contact list also known as a "buddy list" or "friend list") or in chat rooms, and can be standalone apps or integrated into a wider social media platform, or in a website where it can, for instance, be used for conversational commerce. Originally the term "instant messaging" was distinguished from "text messaging" by being run on a computer network instead of a cellular/mobile network, being able to write longer messages, real-time communication, presence ("status"), and being free (only cost of access instead of per SMS message sent). Instant messaging was pioneered in the early Internet era; the IRC protocol was the earliest to achieve wide adoption. Later in the 1990s, ICQ was among the first closed and commercialized instant messengers, and several rival services appeared afterwards as it became a popular use of the Internet. Beginning with its first introduction in 2005, BlackBerry Messenger became the first popular example of mobile-based IM, combining features of traditional IM and mobile SMS. Instant messaging remains very popular today; IM apps are the most widely used smartphone apps: in 2018 for instance there were 980 million monthly active users of WeChat and 1.3 billion monthly users of WhatsApp, the largest IM network. == Overview == Instant messaging (IM), sometimes also called "messaging" or "texting", consists of computer-based human communication between two users (private messaging) or more (chat room or "group") in real-time, allowing immediate receipt of acknowledgment or reply. This is in direct contrast to email, where conversations are not in real-time, and the perceived quasi-synchrony of the communications by the users (although many systems allow users to send offline messages that the other user receives when logging in). Earlier IM networks were limited to text-based communication, not dissimilar to mobile text messaging. As technology has moved forward, IM has expanded to include voice calling using a microphone, videotelephony using webcams, file transfer, location sharing, image and video transfer, voice notes, and other features. IM is conducted over the Internet or other types of networks (see also LAN messenger). Depending on the IM protocol, the technical architecture can be peer-to-peer (direct point-to-point transmission) or client–server (when all clients have to first connect to the central server). Primary IM services are controlled by their corresponding companies and usually follow the client-server model. At one point, the term "Instant Messenger" was a service mark of AOL Time Warner and could not be used in software not affiliated with AOL in the United States. For this reason, in April 2007, the instant messaging client formerly named Gaim (or gaim) announced that they would be renamed "Pidgin". === Clients === Modern IM services generally provide their own client, either a separately installed application or a browser-based client. They are normally centralised networks run by the servers of the platform's operators, unlike peer-to-peer protocols like XMPP. These usually only work within the same IM network, although some allow limited function with other services (see #Interoperability). Third-party client software applications exist that will connect with most of the major IM services. There is the class of instant messengers that uses the serverless model, which doesn't require servers, and the IM network consists only of clients. There are several serverless messengers: RetroShare, Tox, Bitmessage, Ricochet. See also: LAN messenger. Some examples of popular IM services today include Signal, Telegram, WhatsApp Messenger, WeChat, QQ Messenger, Viber, Line, and Snapchat. The popularity of certain apps greatly differ between different countries. Certain apps have an emphasis on certain uses - for example, Skype focuses on video calling, Slack focuses on messaging and file sharing for work teams, and Snapchat focuses on image messages. Some social networking services offer messaging services as a component of their overall platform, such as Facebook's Facebook Messenger, who also own WhatsApp. Others have a direct IM function as an additional adjunct component of their social networking platforms, like Instagram, Reddit, Tumblr, TikTok, Clubhouse and Twitter; this also includes for example dating websites, such as OkCupid or Plenty of Fish, and online gaming chat platforms. === Features === ==== Private and group messaging ==== Private chat allows users to converse privately with another person or a group. Privacy can also be enhanced in several ways, such as end-to-end encryption by default. Public and group chat features allow users to communicate with multiple people simultaneously. ==== Calling ==== Many major IM services and applications offer a call feature for user-to-user voice calls, conference calls, and voice messages. The call functionality is useful for professionals who utilize the application for work purposes and as a hands-free method. Videotelephony using a webcam is also possible by some. ==== Games and entertainment ==== Some IM applications include in-app games for entertainment. Yahoo! Messenger, for example, introduced these where users could play a game and viewed by friends in real-time. MSN Messenger featured a number of playable games within the interface. Facebook's Messenger has had a built-in option to play games with people in a chat, including games like Tetris and Blackjack. Discord features multiple games built inside the "activities" tab in voice channels. ==== Payments ==== A relatively new feature to instant messaging, peer-to-peer payments are available for financial tasks on top of communication. The lack of a service fee also makes these advantageous to financial applications. IM services such as Facebook Messenger and the WeChat 'super-app' for example offer a payment feature. == History == === Early systems === Though the term dates from the 1990s, instant messaging predates the Internet, first appearing on multi-user operating systems like Compatible Time-Sharing System (CTSS) and Multiplexed Information and Computing Service (Multics) in the mid-1960s. Initially, some of these systems were used as notification systems for services like printing, but quickly were used to facilitate communication with other users logged into the same machine. CTSS facilitated communication via text message for up to 30 people. Parallel to instant messaging were early online chat facilities, the earliest of which was Talkomatic (1973) on the PLATO system, which allowed 5 people to chat simultaneously on a 512 x 512 plasma display (5 lines of text + 1 status line per person). During the bulletin board system (BBS) phenomenon that peaked during the 1980s, some systems incorporated chat features which were similar to instant messaging; Freelancin' Roundtable was one prime example. The first such general-availability commercial online chat service (as opposed to PLATO, which was educational) was the CompuServe CB Simulator in 1980, created by CompuServe executive Alexander "Sandy" Trevor in Columbus, Ohio. As networks developed, the protocols spread with the networks. Some of these used a peer-to-peer protocol (e.g. talk, ntalk and ytalk), while others required peers to connect to a server (see talker and IRC). The Zephyr Notification Service (still in use at some institutions) was invented at MIT's Project Athena in the 1980s to allow service providers to locate and send messages to users. Early instant messaging programs were primarily real-time text, where characters appeared as they were typed. This includes the Unix "talk" command line program, which was popular in the 1980s and early 1990s. Some BBS chat programs (i.e. Celerity BBS) also used a similar interface. Modern implementations of real-time text also exist in instant messengers, such as AOL's Real-Time IM as an optional feature. In the latter half of the 1980s and into the early 1990s, the Quantum Link online service for Commodore 64 computers offered user-to-user messages between concurrently connected customers, which they called "On-Line Messages" (or OLM for short), and later "FlashMail." Quantum Link later became America Online and made AOL Instant Messenger (AIM, discussed later). While the Quantum Link client software ran on a Commodore 64, using only

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