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In 1973, Tietäväinen proved [1] that any non-trivial perfect code over a prime-power alphabet has the parameters of a Hamming code or a Golay code. A perfect code may be interpreted as one in which the balls of Hamming radius t centered on codewords exactly fill out the space (t is the covering radius = packing radius). A quasi-perfect code ...
No-code tools are often designed with line of business users in mind as opposed to traditional IT.. The potential benefits of using a NCDP include: Agility - NCDPs typically provide some degree of templated user-interface and user experience functionality for common needs such as forms, workflows, and data display allowing creators to expedite parts of the app creation process.
It can also refer to the tendency to assume there is a perfect solution to a particular problem. A closely related concept is the "perfect solution fallacy". By creating a false dichotomy that presents one option which is obviously advantageous—while at the same time being completely unrealistic—a person using the nirvana fallacy can attack ...
But at certain dimensions, the packing uses all the space and these codes are the so-called "perfect" codes. The only nontrivial and useful perfect codes are the distance-3 Hamming codes with parameters satisfying (2 r – 1, 2 r – 1 – r, 3), and the [23,12,7] binary and [11,6,5] ternary Golay codes. [4] [5]
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It is unknown whether any odd perfect numbers exist, though various results have been obtained. In 1496, Jacques Lefèvre stated that Euclid's rule gives all perfect numbers, [17] thus implying that no odd perfect number exists, but Euler himself stated: "Whether ... there are any odd perfect numbers is a most difficult question". [18]
Robot in a wooden maze. A maze-solving algorithm is an automated method for solving a maze.The random mouse, wall follower, Pledge, and Trémaux's algorithms are designed to be used inside the maze by a traveler with no prior knowledge of the maze, whereas the dead-end filling and shortest path algorithms are designed to be used by a person or computer program that can see the whole maze at once.
Examples include biological or social networks, which contain hundreds, thousands and even billions of nodes in some cases (e.g. Facebook or LinkedIn). 1-planarity [1] 3-dimensional matching [2] [3]: SP1 Bandwidth problem [3]: GT40 Bipartite dimension [3]: GT18 Capacitated minimum spanning tree [3]: ND5