9540989
Word Graphs: The Third Set
This is the third paper in a series of natural language processing in term of knowledge graphs. A word is a basic unit in natural language processing. This is why we study word graphs. Word graphs were already built for prepositions and adwords (including adjectives, adverbs and Chinese quantity words) in two other papers [2], [3]. In this paper, we propose the concept of the logic word and classify logic words into groups in terms of semantics and the way they are used in describing reasoning processes.
7182796
Logic and Model Checking for Hidden Markov Models
The branching-time temporal logic PCTL* has been intro- duced to specify quantitative properties over probability systems, such as discrete-time Markov chains. Until now, however, no logics have been defined to specify properties over hidden Markov models (HMMs). In HMMs the states are hidden, and the hidden processes produce a se- quence of observations. In this paper we extend the logic PCTL* to POCTL*. With our logic one can state properties such as “there is at least a 90 percent probability that the model produces a given sequence of observations” over HMMs. Subsequently, we give model checking algorithms for POCTL* over HMMs.
1125168
Flow Faster: Efficient Decision Algorithms for Probabilistic Simulations
Strong and weak simulation relations have been proposed for Markov chains,
while strong simulation and strong probabilistic simulation relations have been
proposed for probabilistic automata. However, decision algorithms for strong
and weak simulation over Markov chains, and for strong simulation over
probabilistic automata are not efficient, which makes it as yet unclear whether
they can be used as effectively as their non-probabilistic counterparts. This
paper presents drastically improved algorithms to decide whether some
(discrete- or continuous-time) Markov chain strongly or weakly simulates
another, or whether a probabilistic automaton strongly simulates another. The
key innovation is the use of parametric maximum flow techniques to amortize
computations. We also present a novel algorithm for deciding strong
probabilistic simulation preorders on probabilistic automata, which has
polynomial complexity via a reduction to an LP problem. When extending the
algorithms for probabilistic automata to their continuous-time counterpart, we
retain the same complexity for both strong and strong probabilistic
simulations.
36054855
MQML-Message Queuing Markup Language
Message Queuing allows applications to use components that communicate with one another using queued messages. In this paper, we propose a Message Queuing Markup Language (MQML), which is an XML based markup language designed to describe e-business applications and enterprise integration. The MQML language is extensible. The detailed description of the MQML is presented in this paper. An research prototype is given to validate the effectiveness and value of our proposed MQML for enterprise integration.
7466807
Mitosis in Computational Complexity
This expository paper describes some of the results of two recent research papers [GOP+05, GPSZ05]. The first of these papers proves that every NP-complete set is many-one autoreducible. The second paper proves that every many-one autoreducible set is many-one mitotic. It follows immediately that every NP-complete set is many-one mitotic. Hence, we have the compelling result that every NP-complete set A splits into two NP-complete sets A1 and A2.
12649565
Optical nonlinear effects on the performance of IP traffic over GMPLS-based DWDM networks
With the introduction of Generalized multiprotocol label switching in the common control plane for optical crossconnects and electrical switching devices, the integration of IP and dense wavelength division multiplexing can be efficiently achieved. When IP traffic flows are directly mapped to optical channels without SDH inter-layer, the bursty nature of IP traffic may have significant effect on the performance of the optical channel. On the other hand, the nonlinear effects of the optical channel may also have significant effect on the performance at IP level. This paper focuses on the effect of fiber nonlinearities on the performance of IP traffic. Numerical results including IP packet error probability and high-order distribution functions of IP packet error are presented in terms of IP traffic load, input light signal power and the frequency space between the optical wavelengths. It is demonstrated that when IP traffic load is light in such systems, the effect of either four-wave mixing (FWM) or stimulated Raman scattering (SRS) is much less serious than the worst-case assumption, and the limitation on allowable power of input light is also relaxed. The obtained numerical results demonstrated that FWM and SRS are both sensitive to power level of input light and frequency spacing, but each in a unique way. Effort must be taken in system design to avoid improving the performance of one effect at the expense of deteriorating the other.
15561253
An experimental comparison of four test suite reduction techniques
As a test suite usually contains redundancy, a subset of the test suite (representative set) may still satisfy all the test objectives. As the redundancy increases the cost of executing the test suite, many test suite reduction techniques have been brought out in spite of the NP-completeness of the general problem of finding the optimal representative set of the test suite. In the literature, some experimental studies of test suite reduction techniques have already been reported, but there are still shortcomings of the studies of these techniques. This paper presents an experimental comparison of the four typical test suite reduction techniques: heuristic H, heuristic GRE, genetic algorithm-based approach and ILP-based approach. The aim of the study is to provide a guideline for choosing the appropriate test suite reduction techniques.
7255987
Relationship between support vector set and kernel functions in SVM
Based on a constructive learning approach, covering algorithms, we investigate the relationship between support vector sets and kernel functions in support vector machines (SVM). An interesting result is obtained. That is, in the linearly non-separable case, any sample of a given sample setK can become a support vector under a certain kernel function. The result shows that when the sample setK is linearly non-separable, although the chosen kernel function satisfies Mercer’s condition its corresponding support vector set is not necessarily the subset ofK that plays a crucial role in classifyingK. For a given sample set, what is the subset that plays the crucial role in classification? In order to explore the problem, a new concept, boundary or boundary points, is defined and its properties are discussed. Given a sample setK, we show that the decision functions for classifying the boundary points ofK are the same as that for classifying theK itself. And the boundary points ofK only depend onK and the structure of the space at whichK is located and independent of the chosen approach for finding the boundary. Therefore, the boundary point set may become the subset ofK that plays a crucial role in classification. These results are of importance to understand the principle of the support vector machine (SVM) and to develop new learning algorithms.