SAML, developed by the Security Services Technical Committee of the Organization for the Advancement of Structured Information Standards (OASIS), is an XML-based framework for communicating user authentication, entitlement, and attribute information. As its name suggests, SAML allows business entities to make assertions regarding the identity, attributes, and entitlements of a subject (an entity that is often a human user) to other entities, such as a partner company or another enterprise application.
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Mobile communication is the basis for one of the fastest growing business areas at the beginning of the 21 st century. With IMT-2000 (International Mobile Telecommunications 2000), high-speed communication is possible anywhere, at any time, to any communication partner, with almost any device. As IMT-2000 comprises a set of different networking technologies, it provides a communication framework in which a subscriber may freely roam without having to be concerned about which network to use [1]. Hand-over procedures seamlessly integrate in-house networks, campus-based networks, metropolitan and wide area networks.
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This short history identifies 32 major classes of software methods that have emerged over the last 50 years. There are many variations of each major class of software method, which renders the number of software methods in the hundreds. This short history contains a brief synopsis of each of the 32 major classes of software methods, identifying the decade and year they appeared, their purpose, their major tenets, their strengths, and their weaknesses. The year each software method appeared corresponds to the seminal work that introduced the method based on extensive bibliographic research and the strengths and weaknesses were based on scholarly and empirical works to provide an objective capstone for each method.
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In October of 1976 I observed that a certain algorithm – parallel reduction – was associated with monoids: collections of elements with an associative operation. That observation led me to believe that it is possible to associate every useful algorithm with a mathematical theory and that such association allows for both widest possible use and meaningful taxonomy. As mathematicians learned to lift theorems into their most general settings, so I wanted to lift algorithms and data structures. One seldom needs to know the exact type of data on which an algorithm works since most algorithms work on many similar types. In order to write an algorithm one needs only to know the properties of operations on data. I call a collection of types with similar properties on which an algorithm makes sense the underlying concept of the algorithm. Also, in order to pick an efficient algorithm one needs to know the complexity of these operations. In other words, complexity is an essential part of the interface to a concept.
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The history of computers starts out about 2000 years ago, at the birth of the abacus, a wooden rack holding two horizontal wires with beads strung on them. When these beads are moved around, according to programming rules memorized by the user, all regular arithmetic problems can be done. Another important invention around the same time was the Astrolabe, used for navigation. Blaise Pascal is usually credited for building the first digital computer in 1642. It added numbers entered with dials and was made to help his father, a tax collector. In 1671, Gottfried Wilhelm von Leibniz invented a computer that was built in 1694. It could add, and, after changing some things around, multiply. Leibniz invented a special stepped gear mechanism for introducing the addend digits, and this is still being used.
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A decision is a deliberative process that results in the commitment to a categorical proposition. An apt analogy is a judge or jury that must take time to weigh evidence for alternative interpretations and/or possible ramifications before settling on a verdict. Here we evaluate progress in understanding how this process is implemented in the brain. Our scope is somewhat narrow: We consider primarily studies that relate behavior on simple sensory-motor tasks to activity measured in the brain because of the ability to precisely control sensory input, quantify motor output, and target relevant brain regions for measurement and analysis. Nevertheless, our intent is broad: We hope to identify principles that seem likely to contribute to the kinds of flexible and nuanced decisions that are a hallmark of higher cognition. SDT: signal detection theory SA: sequential analysis
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Decision making is one of people’s usual activities since situations that require making decisions constantly arise in their everyday life. Very often, however, the dimensionality and complexity of decision problems reach far beyond human’s capabilities while the cost of a poor decision may be rather high. Therefore, there is a need in software support to the decision making process, and, in response, a wide variety of software tools, from tools for building graphs and charts to expert systems and intelligent agents, are offered as decision support systems. The reason for this variety is the compound, multi-faceted nature of the decision making process.
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Once upon a time, the Internet was a wholly virtual environment, moored only loosely to the physical world. It was where information went to become free, where censorship was routed around, where communities could leap barriers of distance and culture in a single bound . . . and where no one knew you were a dog. The kicker was that these aspects were built into the fabric of the Net, thanks to its origins in military communications research. You couldn’t tie the Net to the real world if you wanted to.
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