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Russell Epstein
Russell Epstein
Russell Epstein is a professor of psychology at the University of Pennsylvania, who studies neural mechanisms underlying visual scene perception, event perception, object recognition, and spatial navigation in humans. His lab studies the role of the Parahippocampal and retrosplenial cortices in determining how people orient themselves relative to their surroundings.
Russell Epstein
Education
Epstein received an undergraduate degree in physics at the University of Chicago and a Ph.D. in computer vision with Alan Yuille at Harvard.
Ambient device
Ambient device
Ambient devices are a type of consumer electronics, characterized by their ability to be perceived at-a-glance, also known as "glanceable". Ambient devices use pre-attentive processing to display information and are aimed at minimizing mental effort. Associated fields include ubiquitous computing and calm technology. The concept is closely related to the Internet of Things.The New York Times Magazine announced ambient devices as one of its Ideas of the Year in 2002. The award recognized a start-up company, Ambient Devices, whose first product Ambient Orb, was a frosted-glass ball lamp, which maps information to a linear color spectrum and displays the trend in the data. Other products in the genre include the 2008 Chumby, and the 2012 52-LED device MooresCloud (a reference to Moore's Law) from Australia.Research on ambient devices began at Xerox Parc, with a paper co-written by Mark Weiser and John Seely Brown, entitled Calm Computing.
Ambient device
Purpose
The purpose of ambient devices is to enable immediate and effortless access to information. The original developers of the idea state that an ambient device is designed to provide support to people carrying out everyday activities. Ambient devices decrease the effort needed to process incoming data, thus rendering individuals more productive.The key issue lies with taking Internet-based content (e.g. traffic congestion, weather condition, stock market quotes) and mapping it into a single, usually one-dimensional spectrum (e.g. angle, colour). According to Rose, this presents data to an end user seamlessly, with an insignificant amount of cognitive load.
Ambient device
History
The concept of ambient devices can be traced back to the early 2000s, when preliminary research was carried at Xerox PARC, according to the company’s official website. The MIT Media Lab website lists the venture as founded by David L. Rose, Ben Resner, Nabeel Hyatt and Pritesh Gandhi as a lab spin-off.
Ambient device
Examples
Ambient Orb was introduced by Ambient Devices in 2002. The device was a glowing sphere that displayed data through changes in color. Ambient Orb was customizable in terms of content and its subsequent visual representation. For instance, when the device was set to monitor a stock market index (e.g. NASDAQ), the Orb glowed green/red to represent the upward/downward price movements; alternatively, it turned amber when the index is unchanged. Nabeel Hyatt stated that the device was marketed as an interior design item with additional functionality.
Ambient device
Examples
Another prominent ambient device is Chumby, released in 2008. It served as an at-a-glance widget station. Chumby was able to push relevant customizable data (weather, news, music, photos) to a touchscreen through Wi-Fi. It greatly surpassed the products resembling Ambient Orb, in terms of functionality, and was proclaimed one of the top gadgets of 2008, production ceased in April 2012. Since 1 July 2014 Chumby is available only as a paid subscription service.More recent products such as Amazon Alexa can be seen as adopting the spirit of ambient devices, in that they operate in the background, responding to both users and external data sources.
Electron excitation
Electron excitation
Electron excitation is the transfer of a bound electron to a more energetic, but still bound state. This can be done by photoexcitation (PE), where the electron absorbs a photon and gains all its energy or by collisional excitation (CE), where the electron receives energy from a collision with another, energetic electron. Within a semiconductor crystal lattice, thermal excitation is a process where lattice vibrations provide enough energy to transfer electrons to a higher energy band such as a more energetic sublevel or energy level. When an excited electron falls back to a state of lower energy, it undergoes electron relaxation (deexcitation). This is accompanied by the emission of a photon (radiative relaxation/spontaneous emission) or by a transfer of energy to another particle. The energy released is equal to the difference in energy levels between the electron energy states.In general, the excitation of electrons in atoms strongly varies from excitation in solids, due to the different nature of the electronic levels and the structural properties of some solids. The electronic excitation (or deexcitation) can take place by several processes such as: collision with more energetic electrons (Auger recombination, impact ionization, ...) absorption / emission of a photon, absorption of several photons (so called multiphoton ionization); e.g., quasi-monochromatic laser light.There are several rules that dictate the transition of an electron to an excited state, known as selection rules. First, as previously noted, the electron must absorb an amount of energy equivalent to the energy difference between the electron's current energy level and an unoccupied, higher energy level in order to be promoted to that energy level. The next rule follows from the Frank-Condon Principle, which states that the absorption of a photon by an electron and the subsequent jump in energy levels is near-instantaneous. The atomic nucleus with which the electron is associated cannot adjust to the change in electron position on the same time scale as the electron (because nuclei are much heavier), and thus the nucleus may be brought into a vibrational state in response to the electron transition. Then, the rule is that the amount of energy absorbed by an electron may allow for the electron to be promoted from a vibrational and electronic ground state to a vibrational and electronic excited state. A third rule is the Laporte Rule, which necessitates that the two energy states between which an electron transitions must have different symmetry. A fourth rule is that when an electron undergoes a transition, the spin state of the molecule/atom that contains the electron must be conserved.Under some circumstances, certain selection rules may be broken and excited electrons may make "forbidden" transitions. The spectral lines associated with such transitions are known as forbidden lines.
Electron excitation
Electron excitation in solids
Ground state preparation The energy and momentum of electrons in solids can be described by introducing Bloch waves into the Schrödinger equation with applying periodic boundary conditions. Solving this eigenvalue equation, one obtains sets of solutions that are describing bands of energies that are allowed to the electrons: the electronic band structure. The latter page contains a summary of the techniques that are nowadays available for modeling the properties of solid crystals at equilibrium, i.e., when they are not illuminated by light.
Electron excitation
Electron excitation in solids
Electron excitation by light: polariton The behavior of electrons excited by photons can be described by the quasi-particle named "polariton". A number of methods exist to describe these, both using classical and quantum electrodynamics. One of the methods is to use the concept of dressed particle.
Addition chain
Addition chain
In mathematics, an addition chain for computing a positive integer n can be given by a sequence of natural numbers starting with 1 and ending with n, such that each number in the sequence is the sum of two previous numbers. The length of an addition chain is the number of sums needed to express all its numbers, which is one less than the cardinality of the sequence of numbers.
Addition chain
Examples
As an example: (1,2,3,6,12,24,30,31) is an addition chain for 31 of length 7, since 2 = 1 + 1 3 = 2 + 1 6 = 3 + 3 12 = 6 + 6 24 = 12 + 12 30 = 24 + 6 31 = 30 + 1Addition chains can be used for addition-chain exponentiation. This method allows exponentiation with integer exponents to be performed using a number of multiplications equal to the length of an addition chain for the exponent. For instance, the addition chain for 31 leads to a method for computing the 31st power of any number n using only seven multiplications, instead of the 30 multiplications that one would get from repeated multiplication, and eight multiplications with exponentiation by squaring: n2 = n × n n3 = n2 × n n6 = n3 × n3 n12 = n6 × n6 n24 = n12 × n12 n30 = n24 × n6 n31 = n30 × n
Addition chain
Methods for computing addition chains
Calculating an addition chain of minimal length is not easy; a generalized version of the problem, in which one must find a chain that simultaneously forms each of a sequence of values, is NP-complete. There is no known algorithm which can calculate a minimal addition chain for a given number with any guarantees of reasonable timing or small memory usage. However, several techniques are known to calculate relatively short chains that are not always optimal.One very well known technique to calculate relatively short addition chains is the binary method, similar to exponentiation by squaring. In this method, an addition chain for the number n is obtained recursively, from an addition chain for n′=⌊n/2⌋ . If n is even, it can be obtained in a single additional sum, as n=n′+n′ . If n is odd, this method uses two sums to obtain it, by computing n−1=n′+n′ and then adding one.The factor method for finding addition chains is based on the prime factorization of the number n to be represented. If n has a number p as one of its prime factors, then an addition chain for n can be obtained by starting with a chain for n/p , and then concatenating onto it a chain for p , modified by multiplying each of its numbers by n/p . The ideas of the factor method and binary method can be combined into Brauer's m-ary method by choosing any number m (regardless of whether it divides n ), recursively constructing a chain for ⌊n/m⌋ , concatenating a chain for m (modified in the same way as above) to obtain m⌊n/m⌋ , and then adding the remainder. Additional refinements of these ideas lead to a family of methods called sliding window methods.
Addition chain
Chain length
Let l(n) denote the smallest s so that there exists an addition chain of length s which computes n It is known that log log 2.13 log log log log 2⁡(n)) ,where ν(n) is the Hamming weight (the number of ones) of the binary expansion of n .One can obtain an addition chain for 2n from an addition chain for n by including one additional sum 2n=n+n , from which follows the inequality l(2n)≤l(n)+1 on the lengths of the chains for n and 2n . However, this is not always an equality, as in some cases 2n may have a shorter chain than the one obtained in this way. For instance, 382 191 11 , observed by Knuth. It is even possible for 2n to have a shorter chain than n , so that l(2n)<l(n) ; the smallest n for which this happens is 375494703 , which is followed by 602641031 , 619418303 , and so on (sequence A230528 in the OEIS).
Addition chain
Brauer chain
A Brauer chain or star addition chain is an addition chain in which each of the sums used to calculate its numbers uses the immediately previous number. A Brauer number is a number for which a Brauer chain is optimal.Brauer proved that l*(2n−1) ≤ n − 1 + l*(n)where l∗ is the length of the shortest star chain. For many values of n, and in particular for n < 12509, they are equal: l(n) = l*(n). But Hansen showed that there are some values of n for which l(n) ≠ l*(n), such as n = 26106 + 23048 + 22032 + 22016 + 1 which has l*(n) = 6110, l(n) ≤ 6109. The smallest such n is 12509.
Addition chain
Scholz conjecture
The Scholz conjecture (sometimes called the Scholz–Brauer or Brauer–Scholz conjecture), named after Arnold Scholz and Alfred T. Brauer), is a conjecture from 1937 stating that l(2n−1)≤n−1+l(n). This inequality is known to hold for all Hansen numbers, a generalization of Brauer numbers; Neill Clift checked by computer that all 5784688 are Hansen (while 5784689 is not). Clift further verified that in fact l(2n−1)=n−1+l(n) for all 64
Frequency separation
Frequency separation
Frequency separation within astrophysics, is a term used in both Helioseismology and Asteroseismology. It refers to the spacing in frequency between adjacent modes of oscillation, having the same angular degree (l) but different radial order (n).
Frequency separation
Frequency separation
For a Sun-like star, the frequency can be further described using the 'large frequency spacing' between modes of different radial order (136 μHz in the Sun), and the 'small frequency spacing' between modes of even and odd angular degree within the same radial order (9.0 μHz in the Sun). The period corresponding to the large frequency spacing can be shown to be approximately the same as the time required for a sound wave to travel to the centre of the Sun and return, confirming the global nature of the oscillations seen.A further frequency separation, the rotational splitting can be seen in high-resolution solar data between modes of the same angular degree, but different azimuthal order (m). This gives information
Kaon
Kaon
In particle physics, a kaon (), also called a K meson and denoted K, is any of a group of four mesons distinguished by a quantum number called strangeness. In the quark model they are understood to be bound states of a strange quark (or antiquark) and an up or down antiquark (or quark).
Kaon
Kaon
Kaons have proved to be a copious source of information on the nature of fundamental interactions since their discovery in cosmic rays in 1947. They were essential in establishing the foundations of the Standard Model of particle physics, such as the quark model of hadrons and the theory of quark mixing (the latter was acknowledged by a Nobel Prize in Physics in 2008). Kaons have played a distinguished role in our understanding of fundamental conservation laws: CP violation, a phenomenon generating the observed matter–antimatter asymmetry of the universe, was discovered in the kaon system in 1964 (which was acknowledged by a Nobel Prize in 1980). Moreover, direct CP violation was discovered in the kaon decays in the early 2000s by the NA48 experiment at CERN and the KTeV experiment at Fermilab.
Kaon
Basic properties
The four kaons are : K−, negatively charged (containing a strange quark and an up antiquark) has mass 493.677±0.013 MeV and mean lifetime (1.2380±0.0020)×10−8 s. K+ (antiparticle of above) positively charged (containing an up quark and a strange antiquark) must (by CPT invariance) have mass and lifetime equal to that of K−. Experimentally, the mass difference is 0.032±0.090 MeV, consistent with zero; the difference in lifetimes is (0.11±0.09)×10−8 s, also consistent with zero. K0, neutrally charged (containing a down quark and a strange antiquark) has mass 497.648±0.022 MeV. It has mean squared charge radius of −0.076±0.01 fm2.
Kaon
Basic properties
K0, neutrally charged (antiparticle of above) (containing a strange quark and a down antiquark) has the same mass.As the quark model shows, assignments that the kaons form two doublets of isospin; that is, they belong to the fundamental representation of SU(2) called the 2. One doublet of strangeness +1 contains the K+ and the K0. The antiparticles form the other doublet (of strangeness −1).
Kaon
Basic properties
[*] See Notes on neutral kaons in the article List of mesons, and neutral kaon mixing, below.[§]^ Strong eigenstate. No definite lifetime (see neutral kaon mixing).[†]^ Weak eigenstate. Makeup is missing small CP–violating term (see neutral kaon mixing).[‡]^ The mass of the K0L and K0S are given as that of the K0. However, it is known that a relatively minute difference between the masses of the K0L and K0S on the order of 3.5×10−6 eV/c2 exists.Although the K0 and its antiparticle K0 are usually produced via the strong force, they decay weakly. Thus, once created the two are better thought of as superpositions of two weak eigenstates which have vastly different lifetimes: The long-lived neutral kaon is called the KL ("K-long"), decays primarily into three pions, and has a mean lifetime of 5.18×10−8 s.
Kaon
Basic properties
The short-lived neutral kaon is called the KS ("K-short"), decays primarily into two pions, and has a mean lifetime 8.958×10−11 s.(See discussion of neutral kaon mixing below.) An experimental observation made in 1964 that K-longs rarely decay into two pions was the discovery of CP violation (see below). Main decay modes for K+: Decay modes for the K− are charge conjugates of the ones above.
Kaon
Parity violation
Two different decays were found for charged strange mesons: The intrinsic parity of a pion is P = −1, and parity is a multiplicative quantum number. Therefore, the two final states have different parity (P = +1 and P = −1, respectively). It was thought that the initial states should also have different parities, and hence be two distinct particles. However, with increasingly precise measurements, no difference was found between the masses and lifetimes of each, respectively, indicating that they are the same particle. This was known as the τ–θ puzzle. It was resolved only by the discovery of parity violation in weak interactions. Since the mesons decay through weak interactions, parity is not conserved, and the two decays are actually decays of the same particle, now called the K+.
Kaon
History
The discovery of hadrons with the internal quantum number "strangeness" marks the beginning of a most exciting epoch in particle physics that even now, fifty years later, has not yet found its conclusion ... by and large experiments have driven the development, and that major discoveries came unexpectedly or even against expectations expressed by theorists. — Bigi & Sanda (2016) While looking for the hypothetical nuclear meson, Louis Leprince-Ringuet found evidence for the existence of a positively charged heavier particle in 1944.In 1947, G.D. Rochester and C.C. Butler of the University of Manchester published two cloud chamber photographs of cosmic ray-induced events, one showing what appeared to be a neutral particle decaying into two charged pions, and one which appeared to be a charged particle decaying into a charged pion and something neutral. The estimated mass of the new particles was very rough, about half a proton's mass. More examples of these "V-particles" were slow in coming.
Kaon
History
In 1949, Rosemary Brown (later Rosemary Fowler), a research student in C.F. Powell's Bristol group, spotted her 'k' track, made by a particle of very similar mass that decayed to three pions.(p82) This led to the so-called 'Tau-Theta' problem: What seemed to be the same particles (now called K+) decayed in two different modes, Theta to two pions (parity +1), Tau to three pions (parity −1). The solution to this puzzle turned out to be that weak interactions do not conserve parity.
Kaon
History
The first breakthrough was obtained at Caltech, where a cloud chamber was taken up Mount Wilson, for greater cosmic ray exposure. In 1950, 30 charged and 4 neutral "V-particles" were reported. Inspired by this, numerous mountaintop observations were made over the next several years, and by 1953, the following terminology was being used: "L meson" for either a muon or charged pion; "K meson" meant a particle intermediate in mass between the pion and nucleon.
Kaon
History
Leprince-Rinquet coined the still-used term "hyperon" to mean any particle heavier than a nucleon. The Leprince-Ringuet particle turned out to be the K+ meson.The decays were extremely slow; typical lifetimes are of the order of 10−10 s. However, production in pion-proton reactions proceeds much faster, with a time scale of 10−23 s. The problem of this mismatch was solved by Abraham Pais who postulated the new quantum number called "strangeness" which is conserved in strong interactions but violated by the weak interactions. Strange particles appear copiously due to "associated production" of a strange and an antistrange particle together. It was soon shown that this could not be a multiplicative quantum number, because that would allow reactions which were never seen in the new synchrotrons which were commissioned in Brookhaven National Laboratory in 1953 and in the Lawrence Berkeley Laboratory in 1955.
Kaon
CP violation in neutral meson oscillations
Initially it was thought that although parity was violated, CP (charge parity) symmetry was conserved. In order to understand the discovery of CP violation, it is necessary to understand the mixing of neutral kaons; this phenomenon does not require CP violation, but it is the context in which CP violation was first observed.
Kaon
CP violation in neutral meson oscillations
Neutral kaon mixing Since neutral kaons carry strangeness, they cannot be their own antiparticles. There must be then two different neutral kaons, differing by two units of strangeness. The question was then how to establish the presence of these two mesons. The solution used a phenomenon called neutral particle oscillations, by which these two kinds of mesons can turn from one into another through the weak interactions, which cause them to decay into pions (see the adjacent figure).
Kaon
CP violation in neutral meson oscillations
These oscillations were first investigated by Murray Gell-Mann and Abraham Pais together. They considered the CP-invariant time evolution of states with opposite strangeness. In matrix notation one can write ψ(t)=U(t)ψ(0)=eiHt(ab),H=(MΔΔM), where ψ is a quantum state of the system specified by the amplitudes of being in each of the two basis states (which are a and b at time t = 0). The diagonal elements (M) of the Hamiltonian are due to strong interaction physics which conserves strangeness. The two diagonal elements must be equal, since the particle and antiparticle have equal masses in the absence of the weak interactions. The off-diagonal elements, which mix opposite strangeness particles, are due to weak interactions; CP symmetry requires them to be real.
Kaon
CP violation in neutral meson oscillations
The consequence of the matrix H being real is that the probabilities of the two states will forever oscillate back and forth. However, if any part of the matrix were imaginary, as is forbidden by CP symmetry, then part of the combination will diminish over time. The diminishing part can be either one component (a) or the other (b), or a mixture of the two.
Kaon
CP violation in neutral meson oscillations
Mixing The eigenstates are obtained by diagonalizing this matrix. This gives new eigenvectors, which we can call K1 which is the difference of the two states of opposite strangeness, and K2, which is the sum. The two are eigenstates of CP with opposite eigenvalues; K1 has CP = +1, and K2 has CP = -1 Since the two-pion final state also has CP = +1, only the K1 can decay this way. The K2 must decay into three pions. Since the mass of K2 is just a little larger than the sum of the masses of three pions, this decay proceeds very slowly, about 600 times slower than the decay of K1 into two pions. These two different modes of decay were observed by Leon Lederman and his coworkers in 1956, establishing the existence of the two weak eigenstates (states with definite lifetimes under decays via the weak force) of the neutral kaons.
Kaon
CP violation in neutral meson oscillations
These two weak eigenstates are called the KL (K-long, τ) and KS (K-short, θ). CP symmetry, which was assumed at the time, implies that KS = K1 and KL = K2.
Kaon
CP violation in neutral meson oscillations
Oscillation An initially pure beam of K0 will turn into its antiparticle, K0, while propagating, which will turn back into the original particle, K0, and so on. This is called particle oscillation. On observing the weak decay into leptons, it was found that a K0 always decayed into a positron, whereas the antiparticle K0 decayed into the electron. The earlier analysis yielded a relation between the rate of electron and positron production from sources of pure K0 and its antiparticle K0. Analysis of the time dependence of this semileptonic decay showed the phenomenon of oscillation, and allowed the extraction of the mass splitting between the KS and KL. Since this is due to weak interactions it is very small, 10−15 times the mass of each state, namely ∆MK = M(KL) − M(KS) = 3.484(6)×10−12 MeV .
Kaon
CP violation in neutral meson oscillations
Regeneration A beam of neutral kaons decays in flight so that the short-lived KS disappears, leaving a beam of pure long-lived KL. If this beam is shot into matter, then the K0 and its antiparticle K0 interact differently with the nuclei. The K0 undergoes quasi-elastic scattering with nucleons, whereas its antiparticle can create hyperons. Due to the different interactions of the two components, quantum coherence between the two particles is lost. The emerging beam then contains different linear superpositions of the K0 and K0. Such a superposition is a mixture of KL and KS; the KS is regenerated by passing a neutral kaon beam through matter. Regeneration was observed by Oreste Piccioni and his collaborators at Lawrence Berkeley National Laboratory. Soon thereafter, Robert Adair and his coworkers reported excess KS regeneration, thus opening a new chapter in this history.
Kaon
CP violation in neutral meson oscillations
CP violation While trying to verify Adair's results, J. Christenson, James Cronin, Val Fitch and Rene Turlay of Princeton University found decays of KL into two pions (CP = +1) in an experiment performed in 1964 at the Alternating Gradient Synchrotron at the Brookhaven laboratory. As explained in an earlier section, this required the assumed initial and final states to have different values of CP, and hence immediately suggested CP violation. Alternative explanations such as nonlinear quantum mechanics and a new unobserved particle (hyperphoton) were soon ruled out, leaving CP violation as the only possibility. Cronin and Fitch received the Nobel Prize in Physics for this discovery in 1980.
Kaon
CP violation in neutral meson oscillations
It turns out that although the KL and KS are weak eigenstates (because they have definite lifetimes for decay by way of the weak force), they are not quite CP eigenstates. Instead, for small ε (and up to normalization), KL = K2 + εK1and similarly for KS. Thus occasionally the KL decays as a K1 with CP = +1, and likewise the KS can decay with CP = −1. This is known as indirect CP violation, CP violation due to mixing of K0 and its antiparticle. There is also a direct CP violation effect, in which the CP violation occurs during the decay itself. Both are present, because both mixing and decay arise from the same interaction with the W boson and thus have CP violation predicted by the CKM matrix. Direct CP violation was discovered in the kaon decays in the early 2000s by the NA48 and KTeV experiments at CERN and Fermilab.
Twist (cocktail garnish)
Twist (cocktail garnish)
A twist is a piece of citrus zest used as a cocktail garnish, generally for decoration and to add flavor when added to a mixed drink.
Twist (cocktail garnish)
Twist (cocktail garnish)
There are a variety of ways of making and using twists. Twists are typically cut from a whole fresh citrus fruit with a small kitchen knife immediately prior to serving, although a peeler, citrus zesters, or other utensil may be used. A curled shape may come from cutting the wedge into a spiral, winding it around a straw or other object, or as a byproduct of the cutting.
Twist (cocktail garnish)
Twist (cocktail garnish)
The name may refer to the shape of the garnish, which is typically curled or twisted longitudinally, or else to the act of twisting the garnish to release fruit oils that infuse the drink. Other techniques include running the twist along the rim of the glass, and "flaming" the twist.They are generally about 50 mm (2 inches) long (although length varies), and thin.Cocktails featuring a twist include Horse's Neck. A lemon twist is also an optional garnish for the martini, and an orange twist is traditional for the old fashioned.
Registered user
Registered user
A registered user is a user of a website, program, or other systems who has previously registered. Registered users normally provide some sort of credentials (such as a username or e-mail address, and a password) to the system in order to prove their identity: this is known as logging in. Systems intended for use by the general public often allow any user to register simply by selecting a register or sign up function and providing these credentials for the first time. Registered users may be granted privileges beyond those granted to unregistered users.
Registered user
Rationale
User registration and login enables a system to personalize itself. For example, a website might display a welcome banner with the user's name and change its appearance or behavior according to preferences indicated by the user. The system may also allow a logged-in user to send and receive messages, and to view and modify personal files or other information.
Registered user
Criticism
Privacy concerns Registration necessarily provides more personal information to a system than it would otherwise have. Even if the credentials used are otherwise meaningless, the system can distinguish a logged-in user from other users and might use this property to store a history of users' actions or activity, possibly without their knowledge or consent. While many systems have privacy policies, depending on the nature of the system, a user might not have any way of knowing for certain exactly what information is stored, how it is used, and with whom, if anyone, it is shared.
Registered user
Criticism
A system could even sell information it has gathered on its users to third parties for advertising or other purposes. The subject of systems' transparency in this regard is one of ongoing debate.
Registered user
Criticism
User inconvenience Registration may be seen as an annoyance or hindrance, especially if it is not inherently necessary or important (for example, in the context of a search engine) or if the system repeatedly prompts users to register. A system's registration process might also be time-consuming or require that the user provide the information they might be reluctant to, such as a home address or social security number.
Parabolic antenna
Parabolic antenna
A parabolic antenna is an antenna that uses a parabolic reflector, a curved surface with the cross-sectional shape of a parabola, to direct the radio waves. The most common form is shaped like a dish and is popularly called a dish antenna or parabolic dish. The main advantage of a parabolic antenna is that it has high directivity. It functions similarly to a searchlight or flashlight reflector to direct radio waves in a narrow beam, or receive radio waves from one particular direction only. Parabolic antennas have some of the highest gains, meaning that they can produce the narrowest beamwidths, of any antenna type. In order to achieve narrow beamwidths, the parabolic reflector must be much larger than the wavelength of the radio waves used, so parabolic antennas are used in the high frequency part of the radio spectrum, at UHF and microwave (SHF) frequencies, at which the wavelengths are small enough that conveniently-sized reflectors can be used.
Parabolic antenna
Parabolic antenna
Parabolic antennas are used as high-gain antennas for point-to-point communications, in applications such as microwave relay links that carry telephone and television signals between nearby cities, wireless WAN/LAN links for data communications, satellite communications, and spacecraft communication antennas. They are also used in radio telescopes.
Parabolic antenna
Parabolic antenna
The other large use of parabolic antennas is for radar antennas, which need to transmit a narrow beam of radio waves to locate objects like ships, airplanes, and guided missiles. They are also often used for weather detection. With the advent of home satellite television receivers, parabolic antennas have become a common feature of the landscapes of modern countries.The parabolic antenna was invented by German physicist Heinrich Hertz during his discovery of radio waves in 1887. He used cylindrical parabolic reflectors with spark-excited dipole antennas at their foci for both transmitting and receiving during his historic experiments.
Parabolic antenna
Design
The operating principle of a parabolic antenna is that a point source of radio waves at the focal point in front of a paraboloidal reflector of conductive material will be reflected into a collimated plane wave beam along the axis of the reflector. Conversely, an incoming plane wave parallel to the axis will be focused to a point at the focal point.
Parabolic antenna
Design
A typical parabolic antenna consists of a metal parabolic reflector with a small feed antenna suspended in front of the reflector at its focus, pointed back toward the reflector. The reflector is a metallic surface formed into a paraboloid of revolution and usually truncated in a circular rim that forms the diameter of the antenna. In a transmitting antenna, radio frequency current from a transmitter is supplied through a transmission line cable to the feed antenna, which converts it into radio waves. The radio waves are emitted back toward the dish by the feed antenna and reflect off the dish into a parallel beam. In a receiving antenna the incoming radio waves bounce off the dish and are focused to a point at the feed antenna, which converts them into electric currents which travel through a transmission line to the radio receiver.
Parabolic antenna
Design
Parabolic reflector The reflector can be constructed from sheet metal, a metal screen, or a wire grill, and can be either a circular dish or various other shapes to create different beam shapes. A metal screen reflects radio waves as effectively as a solid metal surface if its holes are smaller than one-tenth of a wavelength, so screen reflectors are often used to reduce weight and wind loads on the dish. To achieve the maximum gain, the shape of the dish needs to be accurate within a small fraction of a wavelength, to ensure the waves from different parts of the antenna arrive at the focus in phase. Large dishes often require a supporting truss structure behind them to provide the required stiffness.
Parabolic antenna
Design
A reflector made of a grill of parallel wires or bars oriented in one direction acts as a polarizing filter as well as a reflector. It only reflects linearly polarized radio waves, with the electric field parallel to the grill elements. This type is often used in radar antennas. Combined with a linearly polarized feed horn, it helps filter out noise in the receiver and reduces false returns.
Parabolic antenna
Design
A shiny metal parabolic reflector can also focus the sun's rays. Since most dishes could concentrate enough solar energy on the feed structure to severely overheat it if they happened to be pointed at the sun, solid reflectors are always given a coat of flat paint.
Parabolic antenna
Design
Feed antenna The feed antenna at the reflector's focus is typically a low-gain type, such as a half-wave dipole or (more often) a small horn antenna called a feed horn. In more complex designs, such as the Cassegrain and Gregorian, a secondary reflector is used to direct the energy into the parabolic reflector from a feed antenna located away from the primary focal point. The feed antenna is connected to the associated radio-frequency (RF) transmitting or receiving equipment by means of a coaxial cable transmission line or waveguide.
Parabolic antenna
Design
At the microwave frequencies used in many parabolic antennas, waveguide is required to conduct the microwaves between the feed antenna and transmitter or receiver. Because of the high cost of waveguide runs, in many parabolic antennas the RF front end electronics of the receiver is located at the feed antenna, and the received signal is converted to a lower intermediate frequency (IF) so it can be conducted to the receiver through cheaper coaxial cable. This is called a low-noise block downconverter. Similarly, in transmitting dishes, the microwave transmitter may be located at the feed point.
Parabolic antenna
Design
An advantage of parabolic antennas is that most of the structure of the antenna (all of it except the feed antenna) is nonresonant, so it can function over a wide range of frequencies (i.e. a wide bandwidth). All that is necessary to change the frequency of operation is to replace the feed antenna with one that operates at the desired frequency. Some parabolic antennas transmit or receive at multiple frequencies by having several feed antennas mounted at the focal point, close together.
Parabolic antenna
Types
Parabolic antennas are distinguished by their shapes: Paraboloidal or dish – The reflector is shaped like a paraboloid truncated with a circular rim. This is the most common type. It radiates a narrow pencil-shaped beam along the axis of the dish.
Parabolic antenna
Types
Shrouded dish – Sometimes a cylindrical metal shield is attached to the rim of the dish. The shroud shields the antenna from radiation from angles outside the main beam axis, reducing the sidelobes. It is sometimes used to prevent interference in terrestrial microwave links, where several antennas using the same frequency are located close together. The shroud is coated inside with microwave absorbent material. Shrouds can reduce back lobe radiation by 10 dB.
Parabolic antenna
Types
Cylindrical – The reflector is curved in only one direction and flat in the other. The radio waves come to a focus not at a point but along a line. The feed is sometimes a dipole antenna located along the focal line. Cylindrical parabolic antennas radiate a fan-shaped beam, narrow in the curved dimension, and wide in the uncurved dimension. The curved ends of the reflector are sometimes capped by flat plates, to prevent radiation out the ends, and this is called a pillbox antenna.
Parabolic antenna
Types
Shaped-beam antennas – Modern reflector antennas can be designed to produce a beam or beams of a particular shape, rather than just the narrow "pencil" or "fan" beams of the simple dish and cylindrical antennas mentioned above. Two techniques are used, often in combination, to control the shape of the beam: Shaped reflectors – The parabolic reflector can be given a noncircular shape, or different curvatures in the horizontal and vertical directions, to alter the shape of the beam. This is often used in radar antennas. As a general principle, the wider the antenna is in a given transverse direction, the narrower the radiation pattern will be in that direction.
Parabolic antenna
Types
"Orange peel" antenna – Used in search radars, this is a long narrow antenna shaped like the letter "C". It radiates a narrow vertical fan-shaped beam.Arrays of feeds – In order to produce an arbitrary shaped beam, instead of one feed horn, an array of feed horns clustered around the focal point can be used. Array-fed antennas are often used on communication satellites, particularly direct broadcast satellites, to create a downlink radiation pattern to cover a particular continent or coverage area. They are often used with secondary reflector antennas such as the Cassegrain.Parabolic antennas are also classified by the type of feed, that is, how the radio waves are supplied to the antenna: Axial, prime focus, or front feed – This is the most common type of feed, with the feed antenna located in front of the dish at the focus, on the beam axis, pointed back toward the dish. A disadvantage of this type is that the feed and its supports block some of the beam, which limits the aperture efficiency to only 55–60%.
Parabolic antenna
Types
Off-axis or offset feed – The reflector is an asymmetrical segment of a paraboloid, so the focus, and the feed antenna, are located to one side of the dish. The purpose of this design is to move the feed structure out of the beam path, so it does not block the beam. It is widely used in home satellite television dishes, which are small enough that the feed structure would otherwise block a significant percentage of the signal. Offset feed can also be used in multiple reflector designs such as the Cassegrain and Gregorian, below.
Parabolic antenna
Types
Cassegrain – In a Cassegrain antenna, the feed is located on or behind the dish, and radiates forward, illuminating a convex hyperboloidal secondary reflector at the focus of the dish. The radio waves from the feed reflect off the secondary reflector to the dish, which reflects them forward again, forming the outgoing beam. An advantage of this configuration is that the feed, with its waveguides and "front end" electronics does not have to be suspended in front of the dish, so it is used for antennas with complicated or bulky feeds, such as large satellite communication antennas and radio telescopes. Aperture efficiency is on the order of 65–70%.
Parabolic antenna
Types
Gregorian – Similar to the Cassegrain design except that the secondary reflector is concave (ellipsoidal) in shape. Aperture efficiency over 70% can be achieved.
Parabolic antenna
Feed pattern
The radiation pattern of the feed antenna has to be tailored to the shape of the dish, because it has a strong influence on the aperture efficiency, which determines the antenna gain (see Gain section below). Radiation from the feed that falls outside the edge of the dish is called spillover and is wasted, reducing the gain and increasing the backlobes, possibly causing interference or (in receiving antennas) increasing susceptibility to ground noise. However, maximum gain is only achieved when the dish is uniformly "illuminated" with a constant field strength to its edges. Therefore, the ideal radiation pattern of a feed antenna would be a constant field strength throughout the solid angle of the dish, dropping abruptly to zero at the edges. However, practical feed antennas have radiation patterns that drop off gradually at the edges, so the feed antenna is a compromise between acceptably low spillover and adequate illumination. For most front feed horns, optimum illumination is achieved when the power radiated by the feed horn is 10 dB less at the dish edge than its maximum value at the center of the dish.
Parabolic antenna
Feed pattern
Polarization The pattern of electric and magnetic fields at the mouth of a parabolic antenna is simply a scaled-up image of the fields radiated by the feed antenna, so the polarization is determined by the feed antenna. In order to achieve maximum gain, both feed antennas (transmitting and receiving) must have the same polarization. For example, a vertical dipole feed antenna will radiate a beam of radio waves with their electric field vertical, called vertical polarization. The receiving feed antenna must also have vertical polarization to receive them; if the feed is horizontal (horizontal polarization) the antenna will suffer a severe loss of gain.
Parabolic antenna
Feed pattern
To increase the data rate, some parabolic antennas transmit two separate radio channels on the same frequency with orthogonal polarizations, using separate feed antennas; this is called a dual polarization antenna. For example, satellite television signals are transmitted from the satellite on two separate channels at the same frequency using right and left circular polarization. In a home satellite dish, these are received by two small monopole antennas in the feed horn, oriented at right angles. Each antenna is connected to a separate receiver.
Parabolic antenna
Feed pattern
If the signal from one polarization channel is received by the oppositely polarized antenna, it will cause crosstalk that degrades the signal-to-noise ratio. The ability of an antenna to keep these orthogonal channels separate is measured by a parameter called cross polarization discrimination (XPD). In a transmitting antenna, XPD is the fraction of power from an antenna of one polarization radiated in the other polarization. For example, due to minor imperfections a dish with a vertically polarized feed antenna will radiate a small amount of its power in horizontal polarization; this fraction is the XPD. In a receiving antenna, the XPD is the ratio of signal power received of the opposite polarization to power received in the same antenna of the correct polarization, when the antenna is illuminated by two orthogonally polarized radio waves of equal power. If the antenna system has inadequate XPD, cross polarization interference cancelling (XPIC) digital signal processing algorithms can often be used to decrease crosstalk.
Parabolic antenna
Feed pattern
Dual reflector shaping In the Cassegrain and Gregorian antennas, the presence of two reflecting surfaces in the signal path offers additional possibilities for improving performance. When the highest performance is required, a technique called dual reflector shaping may be used. This involves changing the shape of the sub-reflector to direct more signal power to outer areas of the dish, to map the known pattern of the feed into a uniform illumination of the primary, to maximize the gain. However, this results in a secondary that is no longer precisely hyperbolic (though it is still very close), so the constant phase property is lost. This phase error, however, can be compensated for by slightly tweaking the shape of the primary mirror. The result is a higher gain, or gain/spillover ratio, at the cost of surfaces that are trickier to fabricate and test. Other dish illumination patterns can also be synthesized, such as patterns with high taper at the dish edge for ultra-low spillover sidelobes, and patterns with a central "hole" to reduce feed shadowing.
Parabolic antenna
Gain
The directive qualities of an antenna are measured by a dimensionless parameter called its gain, which is the ratio of the power received by the antenna from a source along its beam axis to the power received by a hypothetical isotropic antenna. The gain of a parabolic antenna is: G=4πAλ2eA=(πdλ)2eA where: A is the area of the antenna aperture, that is, the mouth of the parabolic reflector. For a circular dish antenna, A=πd2/4 , giving the second formula above.
Parabolic antenna
Gain
d is the diameter of the parabolic reflector, if it is circular. λ is the wavelength of the radio waves.
Parabolic antenna
Gain
eA is a dimensionless parameter between 0 and 1 called the aperture efficiency. The aperture efficiency of typical parabolic antennas is 0.55 to 0.70.It can be seen that, as with any aperture antenna, the larger the aperture is, compared to the wavelength, the higher the gain. The gain increases with the square of the ratio of aperture width to wavelength, so large parabolic antennas, such as those used for spacecraft communication and radio telescopes, can have extremely high gain. Applying the above formula to the 25-meter-diameter antennas often used in radio telescope arrays and satellite ground antennas at a wavelength of 21 cm (1.42 GHz, a common radio astronomy frequency), yields an approximate maximum gain of 140,000 times or about 52 dBi (decibels above the isotropic level). The largest parabolic dish antenna in the world is the Five-hundred-meter Aperture Spherical radio Telescope in southwest China, which has an effective aperture of about 300 meters. The gain of this dish at 3 GHz is roughly 90 million, or 80 dBi.
Parabolic antenna
Gain
Aperture efficiency eA is a catchall variable which accounts for various losses that reduce the gain of the antenna from the maximum that could be achieved with the given aperture. The major factors reducing the aperture efficiency in parabolic antennas are: Feed spillover – Some of the radiation from the feed antenna falls outside the edge of the dish and so does not contribute to the main beam.
Parabolic antenna
Gain
Feed illumination taper – The maximum gain for any aperture antenna is only achieved when the intensity of the radiated beam is constant across the entire aperture area. However, the radiation pattern from the feed antenna usually tapers off toward the outer part of the dish, so the outer parts of the dish are "illuminated" with a lower intensity of radiation. Even if the feed provided constant illumination across the angle subtended by the dish, the outer parts of the dish are farther away from the feed antenna than the inner parts, so the intensity would drop off with distance from the center. Hence, the intensity of the beam radiated by a parabolic antenna is maximum at the center of the dish and falls off with distance from the axis, reducing the efficiency.
Parabolic antenna
Gain
Aperture blockage – In front-fed parabolic dishes where the feed antenna is located in front of the dish in the beam path (and in Cassegrain and Gregorian designs as well), the feed structure and its supports block some of the beam. In small dishes such as home satellite dishes, where the size of the feed structure is comparable with the size of the dish, this can seriously reduce the antenna gain. To prevent this problem these types of antennas often use an offset feed, where the feed antenna is located to one side, outside the beam area. The aperture efficiency for these types of antennas can reach 0.7 to 0.8.
Parabolic antenna
Gain
Shape errors – Random surface errors in the shape of the reflector reduce efficiency. This loss is approximated by Ruze's Equation.For theoretical considerations of mutual interference (at frequencies between 2 and approximately 30 GHz; typically in the Fixed Satellite Service) where specific antenna performance has not been defined, a reference antenna based on Recommendation ITU-R S.465 is used to calculate the interference, which will include the likely sidelobes for off-axis effects.
Parabolic antenna
Radiation pattern
In parabolic antennas, virtually all the power radiated is concentrated in a narrow main lobe along the antenna's axis. The residual power is radiated in sidelobes, usually much smaller, in other directions. Since the reflector aperture of parabolic antennas is much larger than the wavelength, diffraction usually causes many narrow sidelobes, so the sidelobe pattern is complex. There is also usually a backlobe, in the opposite direction to the main lobe, due to the spillover radiation from the feed antenna that misses the reflector.
Parabolic antenna
Radiation pattern
Beamwidth The angular width of the beam radiated by high-gain antennas is measured by the half-power beam width (HPBW), which is the angular separation between the points on the antenna radiation pattern at which the power drops to one-half (-3 dB) its maximum value. For parabolic antennas, the HPBW θ is given by: θ=kλ/d where k is a factor which varies slightly depending on the shape of the reflector and the feed illumination pattern. For an ideal uniformly illuminated parabolic reflector and θ in degrees, k would be 57.3 (the number of degrees in a radian). For a typical parabolic antenna, k is approximately 70.For a typical 2 meter satellite dish operating on C band (4 GHz), this formula gives a beamwidth of about 2.6°. For the Arecibo antenna at 2.4 GHz, the beamwidth is 0.028°. Since parabolic antennas can produce very narrow beams, aiming them can be a problem. Some parabolic dishes are equipped with a boresight so they can be aimed accurately at the other antenna.
Parabolic antenna
Radiation pattern
There is an inverse relation between gain and beam width. By combining the beamwidth equation with the gain equation, the relation is: G=(πkθ)2eA Radiation pattern formula The radiation from a large paraboloid with uniform illuminated aperture is essentially equivalent to that from a circular aperture of the same diameter D in an infinite metal plate with a uniform plane wave incident on the plate.The radiation-field pattern can be calculated by applying Huygens' principle in a similar way to a rectangular aperture. The electric field pattern can be found by evaluating the Fraunhofer diffraction integral over the circular aperture. It can also be determined through Fresnel zone equations.
Parabolic antenna
Radiation pattern
E=∫∫Ar1ej(ωt−βr1)dS=∫∫e2πi(lx+my)/λdS where β=ω/c=2π/λ . Using polar coordinates, cos ⁡θ and sin ⁡θ . Taking account of symmetry, cos ⁡θl/λρdρ and using first-order Bessel function gives the electric field pattern E(θ) where D is the diameter of the antenna's aperture in meters, λ is the wavelength in meters, θ is the angle in radians from the antenna's symmetry axis as shown in the figure, and J1 is the first-order Bessel function. Determining the first nulls of the radiation pattern gives the beamwidth θ0 . The term J1(x)=0 whenever 3.83 . Thus, arcsin 3.83 arcsin 1.22 λD When the aperture is large, the angle θ0 is very small, so arcsin ⁡(x) is approximately equal to x . This gives the common beamwidth formulas,
Parabolic antenna
History
The idea of using parabolic reflectors for radio antennas was taken from optics, where the power of a parabolic mirror to focus light into a beam has been known since classical antiquity. The designs of some specific types of parabolic antenna, such as the Cassegrain and Gregorian, come from similarly named analogous types of reflecting telescope, which were invented by astronomers during the 15th century.German physicist Heinrich Hertz constructed the world's first parabolic reflector antenna in 1888. The antenna was a cylindrical parabolic reflector made of zinc sheet metal supported by a wooden frame, and had a spark-gap excited 26 cm dipole as a feed antenna along the focal line. Its aperture was 2 meters high by 1.2 meters wide, with a focal length of 0.12 meters, and was used at an operating frequency of about 450 MHz. With two such antennas, one used for transmitting and the other for receiving, Hertz demonstrated the existence of radio waves which had been predicted by James Clerk Maxwell some 22 years earlier. However, the early development of radio was limited to lower frequencies at which parabolic antennas were unsuitable, and they were not widely used until after World War II, when microwave frequencies began to be employed.
Parabolic antenna
History
Italian radio pioneer Guglielmo Marconi used a parabolic reflector during the 1930s in investigations of UHF transmission from his boat in the Mediterranean. In 1931, a 1.7 GHz microwave relay telephone link across the English Channel was demonstrated using 3.0-meter (10 ft) diameter dishes. The first large parabolic antenna, a 9 m dish, was built in 1937 by pioneering radio astronomer Grote Reber in his backyard, and the sky survey he did with it was one of the events that founded the field of radio astronomy.The development of radar during World War II provided a great impetus to parabolic antenna research. This led to the evolution of shaped-beam antennas, in which the curve of the reflector is different in the vertical and horizontal directions, tailored to produce a beam with a particular shape. After the war, very large parabolic dishes were built as radio telescopes. The 100-meter Green Bank Radio Telescope at Green Bank, West Virginia—the first version of which was completed in 1962—is currently the world's largest fully steerable parabolic dish.
Parabolic antenna
History
During the 1960s, dish antennas became widely used in terrestrial microwave relay communication networks, which carried telephone calls and television programs across continents. The first parabolic antenna used for satellite communications was constructed in 1962 at Goonhilly in Cornwall, England, to communicate with the Telstar satellite. The Cassegrain antenna was developed in Japan in 1963 by NTT, KDDI, and Mitsubishi Electric. The advent of computer design tools in the 1970s—such as NEC, capable of calculating the radiation pattern of parabolic antennas—has led to the development of sophisticated asymmetric, multi-reflector and multi-feed designs in recent years.
Learning engineering
Learning engineering
Learning Engineering is the systematic application of evidence-based principles and methods from educational technology and the learning sciences to create engaging and effective learning experiences, support the difficulties and challenges of learners as they learn, and come to better understand learners and learning. It emphasizes the use of a human-centered design approach in conjunction with analyses of rich data sets to iteratively develop and improve those designs to address specific learning needs, opportunities, and problems, often with the help of technology. Working with subject-matter and other experts, the Learning Engineer deftly combines knowledge, tools, and techniques from a variety of technical, pedagogical, empirical, and design-based disciplines to create effective and engaging learning experiences and environments and to evaluate the resulting outcomes. While doing so, the Learning Engineer strives to generate processes and theories that afford generalization of best practices, along with new tools and infrastructures that empower others to create their own learning designs based on those best practices.
Learning engineering
Learning engineering
Supporting learners as they learn is complex, and design of learning experiences and support for learners usually requires interdisciplinary teams. Learning engineers themselves might specialize in designing learning experiences that unfold over time, engage the population of learners, and support their learning; automated data collection and analysis; design of learning technologies; design of learning platforms; improve environments or conditions that support learning; or some combination. The products of learning engineering teams include on-line courses (e.g., a particular MOOC), software platforms for offering online courses, learning technologies (e.g., ranging from physical manipulatives to electronically-enhanced physical manipulatives to technologies for simulation or modeling to technologies for allowing immersion), after-school programs, community learning experiences, formal curricula, and more. Learning engineering teams require expertise associated with the content that learners will learn, the targeted learners themselves, the venues in which learning is expected to happen, educational practice, software engineering, and sometimes even more.
Learning engineering
Learning engineering
Learning engineering teams employ an iterative design process for supporting and improving learning. Initial designs are informed by findings from the learning sciences. Refinements are informed by analysis of data collected as designs are carried out in the world. Methods from learning analytics, design-based research, and rapid large-scale experimentation are used to evaluate designs, inform refinements, and keep track of iterations. According to the IEEE Standards Association's IC Industry Consortium on Learning Engineering, "Learning Engineering is a process and practice that applies the learning sciences using human-centered engineering design methodologies and data-informed decision making to support learners and their development."
Learning engineering
History
Herbert Simon, a cognitive psychologist and economist, first coined the term learning engineering in 1967. However, associations between the two terms learning and engineering began emerging earlier, in the 1940s and as early as the 1920s. Simon argued that the social sciences, including the field of education, should be approached with the same kind of mathematical principles as other fields like physics and engineering.Simon’s ideas about learning engineering continued to reverberate at Carnegie Mellon University, but the term did not catch on until businessman Bror Saxberg began marketing it in 2014 after visiting Carnegie Mellon University and the Pittsburgh Science of Learning Center, or LearnLab for short. Bror Saxberg brought his team from the for-profit education company, Kaplan, to visit CMU. The team went back to Kaplan with what we now call learning engineering to enhance, optimize, test, and sell their educational products. Bror Saxberg would later co-write with Frederick Hess, founder of the American Enterprise Institute's Conservative Education Reform Network, the 2014 book using the term learning engineering.
Learning engineering
Overview
Learning Engineering is aimed at addressing a deficit in the application of science and engineering methodologies to education and training. Its advocates emphasize the need to connect computing technology and generated data with the overall goal of optimizing learning environments.Learning Engineering initiatives aim to improve educational outcomes by leveraging computing to dramatically increase the applications and effectiveness of learning science as a discipline. Digital learning platforms have generated large amounts of data which can reveal immediately actionable insights.The Learning Engineering field has the further potential to communicate educational insights automatically available to educators. For example, learning engineering techniques have been applied to the issue of drop-out or high failure rates. Traditionally, educators and administrators have to wait until students actually withdraw from school or nearly fail their courses to accurately predict when the drop out will occur. Learning engineers are now able to use data on off-task behavior or wheel spinning to better understand student engagement and predict whether individual students are likely to fail.
Learning engineering
Overview
This data enables educators to spot struggling students weeks or months prior to being in danger of dropping out. Proponents of Learning Engineering posit that data analytics will contribute to higher success rates and lower drop-out rates.Learning Engineering can also assist students by providing automatic and individualized feedback. Carnegie Learning’s tool LiveLab, for instance, employs big data to create a learning experience for each student user by, in part, identifying the causes of student mistakes. Research insights gleaned from LiveLab analyses allow teachers to see student progress in real-time.
Learning engineering
Common approaches
A/B Testing A/B testing compares two versions of a given program and allows researchers to determine which approach is most effective. In the context of Learning Engineering, platforms like TeacherASSIST and Coursera use A/B testing to determine which type of feedback is the most effective for learning outcomes.Neil Heffernan’s work with TeacherASSIST includes hint messages from teachers that guide students toward correct answers. Heffernan’s lab runs A/B tests between teachers to determine which type of hints result in the best learning for future questions.UpGrade is an open-source platform for A/B testing in education. It allows EdTech companies to run experiments within their own software. ETRIALS leverages ASSISTments and give scientists freedom to run experiments in authentic learning environments. Terracotta is a research platform that supports teachers' and researchers' abilities to easily run experiments in live classes.
Learning engineering
Common approaches
Educational Data Mining Educational Data Mining involves analyzing data from student use of educational software to understand how software can improve learning for all students. Researchers in the field, such as Ryan Baker at the University of Pennsylvania, have developed models of student learning, engagement, and affect to relate them to learning outcomes. Platform Instrumentation Education tech platforms link educators and students with resources to improve learning outcomes. Dataset Generation Datasets provide the raw material that researchers use to formulate educational insights. For example, Carnegie Mellon University hosts a large volume of learning interaction data in LearnLab's DataShop. Their datasets range from sources like Intelligent Writing Tutors to Chinese tone studies to data from Carnegie Learning’s MATHia platform. Kaggle, a hub for programmers and open source data, regularly hosts machine learning competitions. In 2019, PBS partnered with Kaggle to create the 2019 Data Science Bowl. The DataScience Bowl sought machine learning insights from researchers and developers, specifically into how digital media can better facilitate early-childhood STEM learning outcomes. Datasets, like those hosted by Kaggle PBS and Carnegie Learning, allow researchers to gather information and derive conclusions about student outcomes. These insights help predict student performance in courses and exams.
Learning engineering
Common approaches
Learning Engineering in Practice Combining education theory with data analytics has contributed to the development of tools that differentiate between when a student is wheel spinning (i.e., not mastering a skill within a set timeframe) and when they are persisting productively. Tools like ASSISTments alert teachers when students consistently fail to answer a given problem, which keeps students from tackling insurmountable obstacles, promotes effective feedback and educator intervention, and increases student engagement.
Learning engineering
Common approaches
Studies have found that Learning Engineering may help students and educators to plan their studies before courses begin. For example, UC Berkeley Professor Zach Pardos uses Learning Engineering to help reduce stress for community college students matriculating into four-year institutions. Their predictive model analyzes course descriptions and offers recommendations regarding transfer credits and courses that would align with previous directions of study.Similarly, researchers Kelli Bird and Benjamin Castlemen’s work focuses on creating an algorithm to provide automatic, personalized guidance for transfer students. The algorithm is a response to the finding that while 80 percent of community college students intend to transfer to a four-year institution, only roughly 30 percent actually do so. Such research could lead to a higher pass/fail rate and help educators know when to intervene to prevent student failure or drop out.
Learning engineering
Criticisms of Learning Engineering
Researchers and educational technology commentators have published critiques of learning engineering. The criticisms raised include that learning engineering misrepresents the field of learning sciences and that despite stating it is based on cognitive science, it actually resembles a return to behaviorism. Others have also commented that learning engineering exists as a form of surveillance capitalism. Other fields, such as instructional systems design, have criticized that learning engineering rebrands the work of their own field.
Learning engineering
Criticisms of Learning Engineering
Still others have commented critically on learning engineering's use of metaphors and figurative language. Often a term or metaphor carries a different meaning for professionals or academics from different domains. At times a term that is used positively in one domain carries a strong negative perception in another domain.
Learning engineering
Challenges for Learning Engineering Teams
The multidisciplinary nature of learning engineering creates challenges. The problems that learning engineering attempts to solve often require expertise in diverse fields such as software engineering, instructional design, domain knowledge, pedagogy/andragogy, psychometrics, learning sciences, data science, and systems engineering. In some cases, an individual Learning Engineer with expertise in multiple disciplines might be sufficient. However, learning engineering problems often exceed any one person’s ability to solve. A 2021 convening of thirty learning engineers produced recommendations that key challenges and opportunities for the future of the field involve enhancing R&D infrastructure, supporting domain-based education research, developing components for reuse across learning systems, enhancing human-computer systems, better engineering implementation in schools, improving advising, optimizing for the long-term instead of short-term, supporting 21st-century skills, improved support for learner engagement, and designing algorithms for equity.
Middle reliever
Middle reliever
In baseball, a middle reliever or middle relief pitcher, is a relief pitcher who typically pitches during the fifth, sixth, and seventh innings of a standard baseball game. In leagues with no designated hitter, such as in the National League prior to 2022 and the Japanese Central League, a middle reliever often comes in after the starting pitcher has been pulled in favor of a pinch hitter. Middle relief pitchers are usually tasked to pitch one or two innings where they are then replaced in later innings by a left-handed specialist, setup pitcher, or closer due to deprivation of stamina and effectiveness, but middle relievers may sometimes pitch in these innings as well, especially during games which are close, tied or in extra innings.
Nested transaction
Nested transaction
A nested transaction is a database transaction that is started by an instruction within the scope of an already started transaction. Nested transactions are implemented differently in different databases. However, they have in common that the changes are not made visible to any unrelated transactions until the outermost transaction has committed. This means that a commit in an inner transaction does not necessarily persist updates to the system. In some databases, changes made by the nested transaction are not seen by the 'host' transaction until the nested transaction is committed. According to some, this follows from the isolation property of transactions.

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