taDOM* protocols are designed to provide lock-based approach to handle multiple access to XML databases. the notion of taDOM+ protocol is formalized and generalized and a formal model of taDOM+ lock manager that is pa...
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the proceedings contain 22 papers. the topics discussed include: equivalence-checking with infinite-state systems: techniques and results;database support for multisource multiresolution scientific data;semantic annot...
ISBN:
(纸本)354000145X
the proceedings contain 22 papers. the topics discussed include: equivalence-checking with infinite-state systems: techniques and results;database support for multisource multiresolution scientific data;semantic annotation and indexing of news and sports videos;multimedia presentations databases;interactive indexing and retrieval of multimedia content;a model-based approach to semantic-based retrieval of visual information;Hungarian speech synthesis using a phase exact HNM approach;modelling resource transitions in constraint-based scheduling;a specification framework for real-time scheduling;string transformation for N-dimensional image compression;validation and decomposition of partially occluded images;solving conflicts of agent knowledge states in multiagent systems;specification and verification of secure business transaction systems;and the reconstruction of some 3D convex polyominoes from orthogonal projections.
Programmers rely on programming idioms, design patterns, and workaround techniques to make up for missing programming language support. Evolving languages often address frequently encountered problems by adding langua...
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ISBN:
(纸本)9783642112652
Programmers rely on programming idioms, design patterns, and workaround techniques to make up for missing programming language support. Evolving languages often address frequently encountered problems by adding language and library support to subsequent releases. By using new features, programmers can express their intent more directly. As new concerns, such as parallelism or security, arise, early idioms and language facilities can become serious liabilities. Modern code sometimes benefits from optimization techniques not feasible for code that uses less expressive constructs. Manual source code migration is expensive, time-consuming, and prone to errors. In this paper, we present the notion of source code rejuvenation, the automated migration of legacy code and very briefly mention the tools we use to achieve that. While refactoring improves structurally inadequate source code, source code rejuvenation leverages enhanced program language and library facilities by finding and replacing coding patterns that can be expressed through higher-level software abstractions. Raising the level of abstraction benefits software maintainability, security, and performance.
To specify the set of tractable (practically solvable) computing problems is one of the few main research tasks of theoretical computerscience. Because of this the investigation of the possibility or the impossibilit...
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ISBN:
(纸本)354066694X
To specify the set of tractable (practically solvable) computing problems is one of the few main research tasks of theoretical computerscience. Because of this the investigation of the possibility or the impossibility to efficiently compute approximations of hard optimization problems becomes one of the central and most fruitful areas of recent algorithm and complexity theory. the current point of view is that optimization problems are considered to be tractable if there exist polynomial-time randomized approximation algorithms that solve them with a reasonable approximation ratio. If a optimization problem does not admit such a polynomial-time algorithm, then the problem is considered to be not tractable. the main goal of this paper is to relativize this specification of tractability. the main reason for this attempt is that we consider the requirement for the tractability to be strong because of the definition of the complexity as the "worst-case" complexity. this definition is also related to the approximation ratio of approximation algorithms and then an optimization problem is considered to be intractable because some subset of problem instances is hard. But in the practice we often have the situation that the hard problem instances do not occur. the general idea of this paper is to try to partition the set of all problem instances of a hard optimization problem into a (possibly infinite) spectrum of subclasses according to their polynomial-time approximability. Searching for a method enabling such a fine problem analysis (classification of problem instances) we introduce the concept of stability of approximation. To show that the application of this concept may lead to a "fine" characterisation of the hardness of particular problem instances we consider the traveling salesperson problem and the knapsack problem.
We survey recent results from different areas, studying how introducing per-instance a-priori information affects the solvability and complexity of given tasks. We mainly focus on distributed, and online computation, ...
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ISBN:
(纸本)9783319042978;9783319042985
We survey recent results from different areas, studying how introducing per-instance a-priori information affects the solvability and complexity of given tasks. We mainly focus on distributed, and online computation, where some sort of hidden information plays a crucial role: in the distributed computing, typically nodes have no or only limited information about the global state of the network;in online problems, the algorithm lacks the information about the future input. the traditional approach in both areas is to study how the properties of the problem change if some partial information is available (e. g., nodes of a distributed system have sense of direction, the online algorithm has the promise that the input requests come in some specified order etc.). Recently, attempts have been made to study this information from a quantitative point of view: there is an oracle that delivers (per-instance) best-case information of a limited size, and the relationship between the amount of the additional information, and the benefit it can provide to the algorithm, is investigated. We show cases where this relationship has a form of a trade-off, and others where one or more thresholds can be identified.
the traditional client/server architecture for web service delivery fails to naturally scale. this results in growing costs to the service provider for powerful hardware or extensive use of Content Distribution Networ...
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Unmanned surface vehicle(USV) is a kind of important marine autonomous robots,which has been studied and applied to practice *** the study,the far-field collision conflict scope and marine traffic rules for USV are ...
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ISBN:
(纸本)9781509009107
Unmanned surface vehicle(USV) is a kind of important marine autonomous robots,which has been studied and applied to practice *** the study,the far-field collision conflict scope and marine traffic rules for USV are defined.A novel far-field region collision detection method is proposed for the collision conflict *** constraints from marine traffic rules and collision conflict are denoted by feasible candidate direction angle *** the base of sparse A,a dynamic replanning algorithm of local trajectory is proposed for dynamic obstacles avoidance of USV in the far-field *** the simulation,the validity of the algorithm is demonstrated in the experiments by different types of scenarios.
the shortest common superstring problem (SCS) is one of the fundamental optimization problems in the. area of data compression and DNA sequencing. the SCS is known to be APX-hard [1]. this paper focuses on the analysi...
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ISBN:
(纸本)3540413480
the shortest common superstring problem (SCS) is one of the fundamental optimization problems in the. area of data compression and DNA sequencing. the SCS is known to be APX-hard [1]. this paper focuses on the analysis of the approximation ratio of two greedy-based approximation algorithms for it, namely the naive Greedy algorithm and the Group-Merge algorithm. the main results of this paper are: (i) We disprove the claim that the input instances of Jiang and Li (4) prove that the Group-Merge algorithm does not provide any constant approximation for the SCS. We even prove that the Group-Merge algorithm always finds optimal solutions for these instances. (ii) We show that the Greedy algorithm and the Group-Merge algorithm are incomparable according to the approximation ratio. (iii) We attack the main problem whether the Group-Merge algorithm has a constant approximation ratio by showing that this is the case for a slightly modified algorithm denoted as Group-Merge-1 if all strings have approximately the same length and the compression is limited by a constant fraction of the trivial solution.
In this paper, we investigate how to quantitatively evaluate the performance of state estimation in a discrete event system. We adopt stochastic automaton to quantitatively describe a discrete event system. Withthe s...
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ISBN:
(纸本)9781509009107
In this paper, we investigate how to quantitatively evaluate the performance of state estimation in a discrete event system. We adopt stochastic automaton to quantitatively describe a discrete event system. Withthe stochastic automaton, we can calculate the probability of occurrence of any event sequence. We say that an event sequence(with sufficient length) is detectable if we can determine the current state and subsequent states of the system after the occurrence of the sequence. We then define the sum of probabilities of all detectable event sequences as a quantitative state estimation indicator. this indicator is the limit when the length of sequence goes to infinite. In order to calculate the limit, we augment the discrete event system into a larger automaton which includes the information of the discrete event system and all its state estimates. the augmented automaton is also a stochastic automaton and can be converted into a Markov Chain by removing all the event labels. the calculation of the limit is then translated into the calculation of the sum of probabilities of some states in the Markov Chain, which can be done efficiently.
Lazy clause generation is a powerful approach to reducing search in constraint programming. For use in a lazy clause generation solver, global constraints must be extended to explain themselves. Alternatively they can...
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