In the theory of formal languages, the pumping lemma for regular languages is a lemma that describes an essential property of all regular languages. Informally, it says that all sufficiently long strings in a regular language may be pumped—that is, have a middle section of the string repeated an arbitrary number of times—to produce a new string that is also part of the language. The pumping lemma is useful for proving that a specific language is not a regular language, by showing that the language does not have the property. Specifically, the pumping lemma says that for any regular language L {\displaystyle L} , there exists a constant p {\displaystyle p} such that any string w {\displaystyle w} in L {\displaystyle L} with length at least p {\displaystyle p} can be split into three substrings x {\displaystyle x} , y {\displaystyle y} and z {\displaystyle z} ( w = x y z {\displaystyle w=xyz} , with y {\displaystyle y} being non-empty), such that the strings x z , x y z , x y y z , x y y y z , . . . {\displaystyle xz,xyz,xyyz,xyyyz,...} are also in L {\displaystyle L} . The process of repeating y {\displaystyle y} zero or more times is known as "pumping". Moreover, the pumping lemma guarantees that the length of x y {\displaystyle xy} will be at most p {\displaystyle p} , thus giving a "small" substring x y {\displaystyle xy} that has the desired property. Languages with a finite number of strings vacuously satisfy the pumping lemma by having p {\displaystyle p} equal to the maximum string length in L {\displaystyle L} plus one. By doing so, no strings at all in L {\displaystyle L} have length at least p {\displaystyle p} . The pumping lemma was first proven by Michael Rabin and Dana Scott in 1959, and rediscovered shortly after by Yehoshua Bar-Hillel, Micha A. Perles, and Eli Shamir in 1961, as a simplification of their pumping lemma for context-free languages. == Formal statement == Let L {\displaystyle L} be a regular language. Then there exists an integer p ≥ 1 {\displaystyle p\geq 1} depending only on L {\displaystyle L} such that every string w {\displaystyle w} in L {\displaystyle L} of length at least p {\displaystyle p} ( p {\displaystyle p} is called the "pumping length") can be written as w = x y z {\displaystyle w=xyz} (i.e., w {\displaystyle w} can be divided into three substrings), satisfying the following conditions: | y | ≥ 1 {\displaystyle |y|\geq 1} | x y | ≤ p {\displaystyle |xy|\leq p} ( ∀ n ≥ 0 ) ( x y n z ∈ L ) {\displaystyle (\forall n\geq 0)(xy^{n}z\in L)} y {\displaystyle y} is the substring that can be pumped (removed or repeated any number of times, and the resulting string is always in L {\displaystyle L} ). (1) means the loop y {\displaystyle y} to be pumped must be of length at least one, that is, not an empty string; (2) means the loop must occur within the first p {\displaystyle p} characters. | x | {\displaystyle |x|} must be smaller than p {\displaystyle p} (conclusion of (1) and (2)), but apart from that, there is no restriction on x {\displaystyle x} and z {\displaystyle z} . In simple words, for any regular language L {\displaystyle L} , any sufficiently long string w {\displaystyle w} (in L {\displaystyle L} ) can be split into 3 parts, i.e. w = x y z {\displaystyle w=xyz} , such that all the strings x y n z {\displaystyle xy^{n}z} for n ≥ 0 {\displaystyle n\geq 0} are also in L {\displaystyle L} . Below is a formal expression of the pumping lemma. ∀ L ⊆ Σ ∗ , regular ( L ) ⟹ ∃ p ≥ 1 , ∀ w ∈ L , | w | ≥ p ⟹ ∃ x , y , z ∈ Σ ∗ , ( w = x y z ) ∧ ( | y | ≥ 1 ) ∧ ( | x y | ≤ p ) ∧ ( ∀ n ≥ 0 , x y n z ∈ L ) {\displaystyle {\begin{array}{l}\forall L\subseteq \Sigma ^{},{\mbox{regular}}(L)\implies \\\quad \exists p\geq 1,\forall w\in L,|w|\geq p\implies \\\qquad \exists x,y,z\in \Sigma ^{},(w=xyz)\land (|y|\geq 1)\land (|xy|\leq p)\land (\forall n\geq 0,xy^{n}z\in L)\end{array}}} == Use of the lemma to prove non-regularity == The pumping lemma is often used to prove that a particular language is non-regular: a proof by contradiction may consist of exhibiting a string (of the required length) in the language that lacks the property outlined in the pumping lemma. Example: The language L = { a n b n : n ≥ 0 } {\displaystyle L=\{a^{n}b^{n}:n\geq 0\}} over the alphabet Σ = { a , b } {\displaystyle \Sigma =\{a,b\}} can be shown to be non-regular as follows: Assume that some constant p ≥ 1 {\displaystyle p\geq 1} exists as required by the lemma. Let w {\displaystyle w} in L {\displaystyle L} be given by w = a p b p {\displaystyle w=a^{p}b^{p}} , which is a string longer than p {\displaystyle p} . By the pumping lemma, there must exist a decomposition w = x y z {\displaystyle w=xyz} with | x y | ≤ p {\displaystyle |xy|\leq p} and | y | ≥ 1 {\displaystyle |y|\geq 1} such that x y i z {\displaystyle xy^{i}z} in L {\displaystyle L} for every i ≥ 0 {\displaystyle i\geq 0} . Since | x y | ≤ p {\displaystyle |xy|\leq p} , the string y {\displaystyle y} only consists of instances of a {\displaystyle a} . Because | y | ≥ 1 {\displaystyle |y|\geq 1} , it contains at least one instance of the letter a {\displaystyle a} . Pumping y {\displaystyle y} to give x y 2 z {\displaystyle xy^{2}z} gives a word with more instances of the letter a {\displaystyle a} than the letter b {\displaystyle b} , since some instances of a {\displaystyle a} but none of b {\displaystyle b} were added. Therefore, x y 2 z {\displaystyle xy^{2}z} is not in L {\displaystyle L} which contradicts the pumping lemma. Therefore, L {\displaystyle L} cannot be regular. The proof that the language of balanced (i.e., properly nested) parentheses is not regular follows the same idea. Given p {\displaystyle p} , there is a string of balanced parentheses that begins with more than p {\displaystyle p} left parentheses, so that y {\displaystyle y} will consist entirely of left parentheses. By repeating y {\displaystyle y} , a string can be produced that does not contain the same number of left and right parentheses, and so they cannot be balanced. == Proof of the pumping lemma == For every regular language there is a finite-state automaton (FSA) that accepts the language. The number of states in such an FSA are counted and that count is used as the pumping length p {\displaystyle p} . For a string of length at least p {\displaystyle p} , let q 0 {\displaystyle q_{0}} be the start state and let q 1 , . . . , q p {\displaystyle q_{1},...,q_{p}} be the sequence of the next p {\displaystyle p} states visited as the string is emitted. Because the FSA has only p {\displaystyle p} states, within this sequence of p + 1 {\displaystyle p+1} visited states there must be at least one state that is repeated. Write q s {\displaystyle q_{s}} for such a state. The transitions that take the machine from the first encounter of state q s {\displaystyle q_{s}} to the second encounter of state q s {\displaystyle q_{s}} match some string. This string is called y {\displaystyle y} in the lemma, and since the machine will match a string without the y {\displaystyle y} portion, or with the string y {\displaystyle y} repeated any number of times, the conditions of the lemma are satisfied. For example, the following image shows an FSA. The FSA accepts the string: abcd. Since this string has a length at least as large as the number of states, which is four (so the total number of states that the machine passes through to scan abcd would be 5), the pigeonhole principle indicates that there must be at least one repeated state among the start state and the next four visited states. In this example, only q 1 {\displaystyle q_{1}} is a repeated state. Since the substring bc takes the machine through transitions that start at state q 1 {\displaystyle q_{1}} and end at state q 1 {\displaystyle q_{1}} , that portion could be repeated and the FSA would still accept, giving the string abcbcd. Alternatively, the bc portion could be removed and the FSA would still accept giving the string ad. In terms of the pumping lemma, the string abcd is broken into an x {\displaystyle x} portion a, a y {\displaystyle y} portion bc and a z {\displaystyle z} portion d. As a side remark, the problem of checking whether a given string can be accepted by a given nondeterministic finite automaton without visiting any state repeatedly, is NP hard. == General version of pumping lemma for regular languages == If a language L {\displaystyle L} is regular, then there exists a number p ≥ 1 {\displaystyle p\geq 1} (the pumping length) such that every string u w v {\displaystyle uwv} in L {\displaystyle L} with | w | ≥ p {\displaystyle |w|\geq p} can be written in the form u w v = u x y z v {\displaystyle uwv=uxyzv} with strings x {\displaystyle x} , y {\displaystyle y} and z {\displaystyle z} such that | x y | ≤ p {\displaystyle |xy|\leq p} , | y | ≥ 1 {\displaystyle |y|\geq 1} and u x y i z v {\displaystyle uxy^{i}zv} is in L {\displaystyle L} for every integer i ≥ 0 {\displaystyle i\geq 0} . From this, the above standard v
Wumpus world
Wumpus world is a simple world use in artificial intelligence for which to represent knowledge and to reason. Wumpus world was introduced by Michael Genesereth, and is discussed in the Russell-Norvig Artificial Intelligence book Artificial Intelligence: A Modern Approach. Wumpus World is loosely inspired by the 1972 video game Hunt the Wumpus. == Problem description == In Artificial Intelligence: A Modern Approach, the wumpus world features a 4x4 grid, containing a monster called a wumpus, multiple bottomless pits and hidden gold. The agent starts at (1,1) and has to find the gold and return to the starting position. The agent loses 1 point for every move and gains 1000 points for bringing the gold to the starting position. The agent can sense pits by a breeze, stench indicates a wumpus, and sparkle indicates gold. The wumpus can be killed by an arrow but costs 10 points.
Framebuffer
A framebuffer (frame buffer, or sometimes framestore) is a portion of random-access memory (RAM) containing a bitmap that drives a video display. It is a memory buffer containing data representing all the pixels in a complete video frame. Modern video cards contain framebuffer circuitry in their cores. This circuitry converts an in-memory bitmap into a video signal that can be displayed on a computer monitor. In computing, a screen buffer is a part of computer memory used by a computer application for the representation of the content to be shown on the computer display. The screen buffer may also be called the video buffer, the regeneration buffer, or regen buffer for short. The phrase "screen buffer” refers to a logical function, while video memory refers to a hardware storage location. In particular, the screen buffer may be placed in the main RAM, the video memory, or some other hardware location. To reduce latency and avoid screen tearing, multiple frames can be buffered, and this technique is called multiple buffering. When this is so, at any time, only one frame would be visible, and the others would not be. The currently invisible frames are located in the off-screen buffer. The information in the buffer typically consists of color values for every pixel to be shown on the display. Color values are commonly stored in 1-bit binary (monochrome), 4-bit palettized, 8-bit palettized, 16-bit high color and 24-bit true color formats. An additional alpha channel is sometimes used to retain information about pixel transparency. The total amount of memory required for the framebuffer depends on the resolution of the output signal, and on the color depth or palette size. == History == Computer researchers had long discussed the theoretical advantages of a framebuffer but were unable to produce a machine with sufficient memory at an economically practicable cost. In 1947, the Manchester Baby computer used a Williams tube, later the Williams-Kilburn tube, to store 1024 bits on a cathode-ray tube (CRT) memory and displayed on a second CRT. Other research labs were exploring these techniques with MIT Lincoln Laboratory achieving a 4096 display in 1950. A color-scanned display was implemented in the late 1960s, called the Brookhaven RAster Display (BRAD), which used a drum memory and a television monitor. In 1969, A. Michael Noll of Bell Telephone Laboratories, Inc. implemented a scanned display with a frame buffer, using magnetic-core memory. A year or so later, the Bell Labs system was expanded to display an image with a color depth of three bits on a standard color TV monitor. The vector graphics used in the computer had to be converted for the scanned graphics of a TV display. In the early 1970s, the development of MOS memory (metal–oxide–semiconductor memory) integrated-circuit chips, particularly high-density DRAM (dynamic random-access memory) chips with at least 1 kb memory, made it practical to create, for the first time, a digital memory system with framebuffers capable of holding a standard video image. This led to the development of the SuperPaint system by Richard Shoup at Xerox PARC in 1972. Shoup was able to use the SuperPaint framebuffer to create an early digital video-capture system. By synchronizing the output signal to the input signal, Shoup was able to overwrite each pixel of data as it shifted in. Shoup also experimented with modifying the output signal using color tables. These color tables allowed the SuperPaint system to produce a wide variety of colors outside the range of the limited 8-bit data it contained. This scheme would later become commonplace in computer framebuffers. In 1974, Evans & Sutherland released the first commercial framebuffer, the Picture System, costing about $15,000. It was capable of producing resolutions of up to 512 by 512 pixels in 8-bit grayscale, and became a boon for graphics researchers who did not have the resources to build their own framebuffer. The New York Institute of Technology would later create the first 24-bit color system using three of the Evans & Sutherland framebuffers. Each framebuffer was connected to an RGB color output (one for red, one for green and one for blue), with a Digital Equipment Corporation PDP 11/04 minicomputer controlling the three devices as one. In 1975, the UK company Quantel produced the first commercial full-color broadcast framebuffer, the Quantel DFS 3000. It was first used in TV coverage of the 1976 Montreal Olympics to generate a picture-in-picture inset of the Olympic flaming torch while the rest of the picture featured the runner entering the stadium. The rapid improvement of integrated-circuit technology made it possible for many of the home computers of the late 1970s to contain low-color-depth framebuffers. Today, nearly all computers with graphical capabilities utilize a framebuffer for generating the video signal. Amiga computers, created in the 1980s, featured special design attention to graphics performance and included a unique Hold-And-Modify framebuffer capable of displaying 4096 colors. Framebuffers also became popular in high-end workstations and arcade system boards throughout the 1980s. SGI, Sun Microsystems, HP, DEC and IBM all released framebuffers for their workstation computers in this period. These framebuffers were usually of a much higher quality than could be found in most home computers, and were regularly used in television, printing, computer modeling and 3D graphics. Framebuffers were also used by Sega for its high-end arcade boards, which were also of a higher quality than on home computers. == Display modes == Framebuffers used in personal and home computing often had sets of defined modes under which the framebuffer can operate. These modes reconfigure the hardware to output different resolutions, color depths, memory layouts and refresh rate timings. In the world of Unix machines and operating systems, such conveniences were usually eschewed in favor of directly manipulating the hardware settings. This manipulation was far more flexible in that any resolution, color depth and refresh rate was attainable – limited only by the memory available to the framebuffer. An unfortunate side-effect of this method was that the display device could be driven beyond its capabilities. In some cases, this resulted in hardware damage to the display. More commonly, it simply produced garbled and unusable output. Modern CRT monitors fix this problem through the introduction of protection circuitry. When the display mode is changed, the monitor attempts to obtain a signal lock on the new refresh frequency. If the monitor is unable to obtain a signal lock or if the signal is outside the range of its design limitations, the monitor will ignore the framebuffer signal and possibly present the user with an error message. LCD monitors tend to contain similar protection circuitry, but for different reasons. Since the LCD must digitally sample the display signal (thereby emulating an electron beam), any signal that is out of range cannot be physically displayed on the monitor. == Color palette == Framebuffers have traditionally supported a wide variety of color modes. Due to the expense of memory, most early framebuffers used 1-bit (2 colors per pixel), 2-bit (4 colors), 4-bit (16 colors) or 8-bit (256 colors) color depths. The problem with such small color depths is that a full range of colors cannot be produced. The solution to this problem was indexed color, which adds a lookup table to the framebuffer. Each color stored in framebuffer memory acts as a color index. The lookup table serves as a palette with a limited number of different colors, while the rest is used as an index table. Here is a typical indexed 256-color image and its own palette (shown as a rectangle of swatches): In some designs, it was also possible to write data to the lookup table (or switch between existing palettes) on the fly, allowing dividing the picture into horizontal bars with their own palette and thus rendering an image that had a far wider palette. For example, viewing an outdoor shot photograph, the picture could be divided into four bars: the top one with emphasis on sky tones, the next with foliage tones, the next with skin and clothing tones, and the bottom one with ground colors. This required each palette to have overlapping colors, but, carefully done, allowed great flexibility. == Memory access == While framebuffers are commonly accessed via a memory mapping directly to the CPU memory space, this is not the only method by which they may be accessed. Framebuffers have varied widely in the methods used to access memory. Some of the most common are: Mapping the entire framebuffer to a given memory range. Port commands to set each pixel, range of pixels or palette entry. Mapping a memory range smaller than the framebuffer memory, then bank switching as necessary. The framebuffer organization may be packed pixel or planar. The framebuffer may be all
Quantum robotics
Quantum robotics is an interdisciplinary field that investigates the intersection of robotics and quantum mechanics. This field, in particular, explores the applications of quantum phenomena such as quantum entanglement within the realm of robotics. Examples of its applications include quantum communication in multi-agent cooperative robotic scenarios, the use of quantum algorithms in performing robotics tasks, and the integration of quantum devices (e.g., quantum detectors) in robotic systems. == Introduction == The free-space quantum communication between mobile platforms was proposed for reconfigurable quantum key distribution (QKD) applications using unmanned aerial vehicle (UAVs, a.k.a. drones) in 2017. This technology was later advanced in various aspects in mobile drone and vehicle platforms in several configurations such as drone-to-drone, drone-to-moving vehicle, and vehicle-to-vehicle systems. Some research has contributed to low-size, low-weight, and low-power quantum key distribution systems for small-form UAVs, the characterization of a polarization-based receiver for mobile free-space optical QKD, and optical-relayed entanglement distribution using drones as mobile nodes. The topic of free-space quantum communication between mobile platforms, initially developed to meet the need for free-space QKD and entanglement distribution using mobile nodes, was brought into the robotics domain as an emerging interdisciplinary mechatronics topic to investigate the interface between quantum technologies and the robotic systems domain. The main advantage of such integrated technology is the guaranteed security in communication between multi-agent and cooperative autonomous systems. Other advances are anticipated. == Quantum entanglement == According to quantum mechanics, entanglement occurs when more than one particle become connected. If the state of one particle changes then it will instantly change the state of other particles regardless of their distance. Entangled sensors do the same kind of work and achieve strong sensitivity. A group of quantum robots can measure magnetic fields, gravitational fields and other physical properties using entangled sensors with high rate of accuracy. Again the connection of one robot to other is increased (become strong) by quantum entanglement. == Quantum teleportation == Quantum teleportation is the transfer of quantum information (not physical objects). This is used in case of multi robot process. One robot is programmed with a complex quantum update. Then that robot can teleport that complex quantum information (the update) to other robots. This teleportation or communication is very secure because all the work is done in quantum state. == Kinematics == Quantum computing has been proposed as being optimal for calculating inverse kinematics values. == Alice and Bob robots == In the realm of quantum mechanics, the names Alice and Bob are frequently employed to illustrate various phenomena, protocols, and applications. These include their roles in QKD, quantum cryptography, entanglement, and teleportation. The terms "Alice Robot" and "Bob Robot" serve as analogous expressions that merge the concepts of Alice and Bob from quantum mechanics with mechatronic mobile platforms (such as robots, drones, and autonomous vehicles). For example, the Alice Robot functions as a transmitter platform that communicates with the Bob Robot, housing the receiving detectors.
Haskins Laboratories
Haskins Laboratories, Inc. is an independent research laboratory, founded in 1935 and located in New Haven, Connecticut since 1970. Many current Haskins researchers are affiliated with Yale University's Child Study Center and/or the University of Connecticut. Haskins is a multidisciplinary and international community of researchers who conduct basic research on spoken and written language and global literacy. A guiding perspective of their research has been to view speech and language as emerging from biological processes, including those of adaptation, response to stimuli, and conspecific interaction. Haskins Laboratories has a long history of technological and theoretical innovation, from creating systems of rules for speech synthesis and development of an early working prototype of a reading machine for the blind to developing the landmark concept of phonemic awareness as the critical preparation for learning to read an alphabetic writing system. == Research tools and facilities == Haskins Laboratories is equipped, in-house, with a comprehensive suite of tools and capabilities to advance its mission of research into language and literacy. As of 2014, these included: Anechoic chamber Electroencephalography BioSemi 264 electrode, 24 bit Active Two System EGI 128 electrode, Geodesic EEG System 300 Electromagnetic articulography (EMMA) Carstens AG501 NDI WAVE Eye tracking: HL is equipped with 3 SR Research eye-trackers. 2 Model Eyelink 1000 systems. 1 Model Eyelink 1000plus system. Magnetic resonance imaging: Haskins has access to MRI scanners through agreements with the University of Connecticut and the Yale School of Medicine. On-site, HL has a Linux computer cluster dedicated to analysis of MRI data. Motion capture: HL is equipped with a Vicon motion capture system with one Basler high-speed digital camera, six Vicon MX T-20 cameras and a Vicon MX Giganet for synching camera data and connecting cameras to the data capture computer. Near infrared spectroscopy: HL has a TechEn CW6 8x8 system (four emitters; eight detectors). Ultrasound sonogram == History == Many researchers have contributed to scientific breakthroughs at Haskins Laboratories since its founding. All of them are indebted to the pioneering work and leadership of Caryl Parker Haskins, Franklin S. Cooper, Alvin Liberman, Seymour Hutner and Luigi Provasoli. The history presented here focuses on the research program of the division of Haskins Laboratories that, since the 1940s, has been most well known for its work in the areas of speech, language, and reading. === 1930s === Caryl Haskins and Franklin S. Cooper established Haskins Laboratories in 1935. It was originally affiliated with Harvard University, MIT, and Union College in Schenectady, NY. Caryl Haskins conducted research in microbiology, radiation physics, and other fields in Cambridge, MA and Schenectady. In 1939 Haskins Laboratories moved its center to New York City. Seymour Hutner joined the staff to set up a research program in microbiology, genetics, and nutrition. The descendant of the division led by Hutner program eventually became a department of Pace University in New York. The two identically named organizations are no longer formally affiliated. === 1940s === The U. S. Office of Scientific Research and Development, under Vannevar Bush asked Haskins Laboratories to evaluate and develop technologies for assisting blinded World War II veterans. Experimental psychologist Alvin Liberman joined Haskins Laboratories to assist in developing a "sound alphabet" to represent the letters in a text for use in a reading machine for the blind. Luigi Provasoli joined Haskins Laboratories to set up a research program in marine biology. The program in marine biology moved to Yale University in 1970 and disbanded with Provasoli's retirement in 1978. === 1950s === Franklin S. Cooper invented the pattern playback, a machine that converts pictures of the acoustic patterns of speech back into sound. With this device, Alvin Liberman, Cooper, and Pierre Delattre (and later joined by Katherine Safford Harris, Leigh Lisker, Arthur Abramson, and others), discovered the acoustic cues for the perception of phonetic segments (consonants and vowels). Liberman and colleagues proposed a motor theory of speech perception to resolve the acoustic complexity: they hypothesized that we perceive speech by tapping into a biological specialization, a speech module, that contains knowledge of the acoustic consequences of articulation. Liberman, aided by Frances Ingemann and others, organized the results of the work on speech cues into a groundbreaking set of rules for speech synthesis by the Pattern Playback. === 1960s === Franklin S. Cooper and Katherine Safford Harris, working with Peter MacNeilage, were the first researchers in the U.S. to use electromyographic techniques, pioneered at the University of Tokyo, to study the neuromuscular organization of speech. Leigh Lisker and Arthur Abramson looked for simplification at the level of articulatory action in the voicing of certain contrasting consonants. They showed that many acoustic properties of voicing contrasts arise from variations in voice onset time, the relative phasing of the onset of vocal cord vibration and the end of a consonant. Their work has been widely replicated and elaborated, here and abroad, over the following decades. Donald Shankweiler and Michael Studdert-Kennedy used a dichotic listening technique (presenting different nonsense syllables simultaneously to opposite ears) to demonstrate the dissociation of phonetic (speech) and auditory (nonspeech) perception by finding that phonetic structure devoid of meaning is an integral part of language, typically processed in the left cerebral hemisphere. Liberman, Cooper, Shankweiler, and Studdert-Kennedy summarized and interpreted fifteen years of research in "Perception of the Speech Code", still among the most cited papers in the speech literature. It set the agenda for many years of research at Haskins and elsewhere by describing speech as a code in which speakers overlap (or coarticulate) segments to form syllables. Researchers at Haskins connected their first computer to a speech synthesizer designed by Haskins Laboratories' engineers. Ignatius Mattingly, with British collaborators, John N. Holmes and J.N. Shearme, adapted the Pattern playback rules to write the first computer program for synthesizing continuous speech from a phonetically spelled input. A further step toward a reading machine for the blind combined Mattingly's program with an automatic look-up procedure for converting alphabetic text into strings of phonetic symbols. === 1970s === In 1970, Haskins Laboratories moved to New Haven, Connecticut, and entered into affiliation agreements with Yale University and the University of Connecticut; Haskins remains fully independent of both Yale and UConn, administratively and financially. The lab's original location in New Haven, at 270 Crown Street (from 1970 to 2005), was leased from Yale University. Isabelle Liberman, Donald Shankweiler, and Alvin Liberman teamed up with Ignatius Mattingly to study the relationship between speech perception and reading, a topic implicit in Haskins Laboratories' research program since its inception. They developed the concept of phonemic awareness, the knowledge that would-be readers must be aware of the phonemic structure of their language in order to be able to read. Leonard Katz related the work to contemporary cognitive theory and provided expertise in experimental design and data analysis. Under the broad rubric of the "alphabetic principle", this is the core of the lab's present program of reading pedagogy. Patrick Nye joined Haskins Laboratories to lead a team working on the reading machine for the blind. The project culminated when the addition of an optical character recognizer allowed investigators to assemble the first automatic text-to-speech reading machine. By the end of the decade this technology had advanced to the point where commercial concerns assumed the task of designing and manufacturing reading machines for the blind. In 1973, Franklin S. Cooper was selected to form a panel of six experts charged with investigating the famous 18-minute gap in the White House office tapes of President Richard Nixon related to the Watergate scandal. Building on earlier work, Philip Rubin developed the sinewave synthesis program, which was then used by Robert Remez, Rubin, and colleagues to show that listeners can perceive continuous speech without traditional speech cues from a pattern of sinewaves that track the changing resonances of the vocal tract. This paved the way for a view of speech as a dynamic pattern of trajectories through articulatory-acoustic space. Philip Rubin and colleagues developed Paul Mermelstein's anatomically simplified vocal tract model, originally worked on at Bell Laboratories, into the first articulatory synthesizer that can be controlled in a phy
Semantic analysis (machine learning)
In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents. Semantic analysis strategies include: Metalanguages based on first-order logic, which can analyze the speech of humans. Understanding the semantics of a text is symbol grounding: if language is grounded, it is equal to recognizing a machine-readable meaning. For the restricted domain of spatial analysis, a computer-based language understanding system was demonstrated. Latent semantic analysis (LSA), a class of techniques where documents are represented as vectors in a term space. A prominent example is probabilistic latent semantic analysis (PLSA). Latent Dirichlet allocation, which involves attributing document terms to topics. n-grams and hidden Markov models, which work by representing the term stream as a Markov chain, in which each term is derived from preceding terms. == Stochastic semantic analysis ==
Microsoft To Do
Microsoft To Do (previously styled as Microsoft To-Do) is a cloud-based task management application. It allows users to manage their tasks from a smartphone, tablet and computer. The technology is produced by the team behind Wunderlist, which was acquired by Microsoft, and the stand-alone apps feed into the existing Tasks feature of the Outlook product range. == History == Microsoft To Do was first launched as a preview with basic features in April 2017. Later more features were added including Task list sharing in June 2018. In September 2019, a major update to the app was unveiled, adopting a new user interface with a closer resemblance to Wunderlist. The name was also slightly updated by removing the hyphen from To-Do. In May 2020, Microsoft officially closed the doors on Wunderlist, ending its active service in favor of improving and expanding Microsoft To Do.