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Wilmington, North Carolina once had a thriving Black middle class and an elected interracial government. In 1898 white supremacists used violence to overthrow that government, kill Black residents and drive many others from the city.
MORE →Reflects the personal views, recollections, and perspective of the author, Mike Davis.
This is a personal recollection on the Move fire on May 13, 1985
In computer science, a linear bounded automaton (abbreviated LBA) is a restricted form of Turing machine that functions as a more accurate model of a real-world computer, as its definition does not assume an unlimited tape.
Formally, it satisfies the following three conditions:
In other words: instead of having potentially infinite tape on which to compute, computation is restricted to the portion of the tape containing the input plus the two tape squares holding the endmarkers.
An alternative, less restrictive definition is as follows:
The strong and the weaker definition lead to the same computational abilities of the respective automaton classes,[1]: 225 by the same argument used to prove the linear speedup theorem.
Linear bounded automata are acceptors for the class of context-sensitive languages.[1]: 225–226 The only restriction placed on grammars for such languages is that no production maps a string to a shorter string. Thus no derivation of a string in a context-sensitive language can contain a sentential form longer than the string itself. Since there is a one-to-one correspondence between linear-bounded automata and such grammars, no more tape than that occupied by the original string is necessary for the string to be recognized by the automaton.
In 1960, John Myhill introduced an automaton model today known as deterministic linear bounded automaton.[2] In 1963, Peter Landweber proved that the languages accepted by deterministic LBAs are context-sensitive.[3] In 1964, S.-Y. Kuroda introduced the more general model of (nondeterministic) linear bounded automata, and adapted Landweber's proof to show that the languages accepted by nondeterministic linear bounded automata are precisely the context-sensitive languages.[4][5]
In his seminal paper, Kuroda also stated two research challenges, which subsequently became famously known as the "LBA problems": The first LBA problem is whether the class of languages accepted by LBA is equal to the class of languages accepted by deterministic LBA. This problem can be phrased succinctly in the language of computational complexity theory as:
The second LBA problem is whether the class of languages accepted by LBA is closed under complement.
As observed already by Kuroda, a negative answer to the second LBA problem would imply a negative answer to the first problem. But the second LBA problem has an affirmative answer, which is implied by the Immerman–Szelepcsényi theorem proved 20 years after the problem was raised.[6][7] As of today, the first LBA problem still remains open. Savitch's theorem provides an initial insight, that NSPACE(O(n)) ⊆ DSPACE(O(n2)).[8]
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In computer science, a linear bounded automaton (abbreviated LBA) is a restricted form of Turing machine that functions as a more accurate model of a real-world computer, as its definition does not assume an unlimited tape. Formally, it satisfies the following three conditions: Its input alphabet includes two special symbols, serving as left and right endmarkers. Its transitions may not print other symbols over the endmarkers. Its transitions may neither move to the left of the left endmarker nor to the right of the right endmarker. In other words: instead of having potentially infinite tape on which to compute, computation is restricted to the portion of the tape containing the input plus the two tape squares holding the endmarkers. An alternative, less restrictive definition is as follows: Like a Turing machine, an LBA possesses a tape made up of cells that can contain symbols from a finite alphabet, a head that can read from or write to one cell on the tape at a time and can be moved, and a finite number of states. An LBA differs from a Turing machine in that while the tape is initially considered to have unbounded length, only a finite contiguous portion of the tape, whose length is a linear function of the length of the initial input, can be accessed by the read/write head; hence the name linear bounded automaton. The strong and the weaker definition lead to the same computational abilities of the respective automaton classes, by the same argument used to prove the linear speedup theorem.
A context-sensitive grammar (CSG) is a formal grammar in which the left-hand sides and right-hand sides of any production rules may be surrounded by a context of terminal and nonterminal symbols. Context-sensitive grammars are more general than context-free grammars, in the sense that there are languages that can be described by a CSG but not by a context-free grammar. Context-sensitive grammars are less general (in the same sense) than unrestricted grammars. Thus, CSGs are positioned between context-free and unrestricted grammars in the Chomsky hierarchy. A formal language that can be described by a context-sensitive grammar, or, equivalently, by a noncontracting grammar or a linear bounded automaton, is called a context-sensitive language. Some textbooks actually define CSGs as non-contracting, although this is not how Noam Chomsky defined them in 1959. This choice of definition makes no difference in terms of the languages generated (i.e. the two definitions are weakly equivalent), but it does make a difference in terms of what grammars are structurally considered context-sensitive; the latter issue was analyzed by Chomsky in 1963. Chomsky introduced context-sensitive grammars as a way to describe the syntax of natural language where it is often the case that a word may or may not be appropriate in a certain place depending on the context. Walter Savitch has criticized the terminology "context-sensitive" as misleading and proposed "non-erasing" as better explaining the distinction between a CSG and an unrestricted grammar. Although it is well known that certain features of languages (e.g. cross-serial dependency) are not context-free, it is an open question how much of CSGs' expressive power is needed to capture the context sensitivity found in natural languages. Subsequent research in this area has focused on the more computationally tractable mildly context-sensitive languages. The syntaxes of some visual programming languages can be described by context-sensitive graph grammars.
Lazy linear hybrid automata model the discrete time behavior of control systems containing finite-precision sensors and actuators interacting with their environment under bounded inertial delays. The model permits only linear flow constraints but the invariants and guards can be any computable function. This computational model was proposed by Manindra Agrawal and P. S. Thiagarajan. This model is more realistic and also computationally amenable than the currently popular modeling paradigm of linear hybrid automaton.
In the study of graph algorithms, Courcelle's theorem is the statement that every graph property definable in the monadic second-order logic of graphs can be decided in linear time on graphs of bounded treewidth. The result was first proved by Bruno Courcelle in 1990 and independently rediscovered by Borie, Parker & Tovey (1992). It is considered the archetype of algorithmic meta-theorems.
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
MORE →Madam C.J. Walker