The Experts below are selected from a list of 70002 Experts worldwide ranked by ideXlab platform
Venkat Venkatasubramanian - One of the best experts on this subject based on the ideXlab platform.
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a signed Directed Graph and qualitative trend analysis based framework for incipient fault diagnosis
Chemical Engineering Research & Design, 2007Co-Authors: Mano Ram Maurya, Raghunathan Rengaswamy, Venkat VenkatasubramanianAbstract:In this article a combined signed Directed Graph (SDG) and qualitative trend analysis (QTA) framework for incipient fault diagnosis has been proposed. The SDG is the first level in this framework and provides a possible candidate set of faults based on the incipient response of the process. The search for the actual fault is performed based on a QTA (level 2), which uses the temporal evolution of the sensors for further resolution. Thus, this framework combines the completeness property of SDG with the high diagnostic resolution property of QTA. Methods to address the problem of incorrect diagnosis arising due to incorrect measurement of initial response have also been presented. The proposed approach is tested on the Tennessee Eastman (TE) case study. Correct fault diagnosis is performed in all possible single fault scenarios. It is shown that this framework provides fast, reliable and accurate incipient fault diagnosis.
Jinyi Cai - One of the best experts on this subject based on the ideXlab platform.
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a decidable dichotomy theorem on Directed Graph homomorphisms with non negative weights
Computational Complexity, 2019Co-Authors: Jinyi Cai, Xi ChenAbstract:The complexity of Graph homomorphism problems has been the subject of intense study for some years. In this paper, we prove a decidable complexity dichotomy theorem for the partition function of Directed Graph homomorphisms. Our theorem applies to all non-negative weighted forms of the problem: given any fixed matrix A with non-negative algebraic entries, the partition function ZA(G) of Directed Graph homomorphisms from any Directed Graph G is either tractable in polynomial time or #P-hard, depending on the matrix A. The proof of the dichotomy theorem is combinatorial, but involves the definition of an infinite family of Graph homomorphism problems. The proof of its decidability on the other hand is algebraic and based on properties of polynomials.
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a decidable dichotomy theorem on Directed Graph homomorphisms with non negative weights
arXiv: Computational Complexity, 2010Co-Authors: Jinyi Cai, Xi ChenAbstract:The complexity of Graph homomorphism problems has been the subject of intense study. It is a long standing open problem to give a (decidable) complexity dichotomy theorem for the partition function of Directed Graph homomorphisms. In this paper, we prove a decidable complexity dichotomy theorem for this problem and our theorem applies to all non-negative weighted form of the problem: given any fixed matrix A with non-negative algebraic entries, the partition function Z_A(G) of Directed Graph homomorphisms from any Directed Graph G is either tractable in polynomial time or #P-hard, depending on the matrix A. The proof of the dichotomy theorem is combinatorial, but involves the definition of an infinite family of Graph homomorphism problems. The proof of its decidability is algebraic using properties of polynomials.
Mano Ram Maurya - One of the best experts on this subject based on the ideXlab platform.
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a signed Directed Graph and qualitative trend analysis based framework for incipient fault diagnosis
Chemical Engineering Research & Design, 2007Co-Authors: Mano Ram Maurya, Raghunathan Rengaswamy, Venkat VenkatasubramanianAbstract:In this article a combined signed Directed Graph (SDG) and qualitative trend analysis (QTA) framework for incipient fault diagnosis has been proposed. The SDG is the first level in this framework and provides a possible candidate set of faults based on the incipient response of the process. The search for the actual fault is performed based on a QTA (level 2), which uses the temporal evolution of the sensors for further resolution. Thus, this framework combines the completeness property of SDG with the high diagnostic resolution property of QTA. Methods to address the problem of incorrect diagnosis arising due to incorrect measurement of initial response have also been presented. The proposed approach is tested on the Tennessee Eastman (TE) case study. Correct fault diagnosis is performed in all possible single fault scenarios. It is shown that this framework provides fast, reliable and accurate incipient fault diagnosis.
Xi Chen - One of the best experts on this subject based on the ideXlab platform.
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a decidable dichotomy theorem on Directed Graph homomorphisms with non negative weights
Computational Complexity, 2019Co-Authors: Jinyi Cai, Xi ChenAbstract:The complexity of Graph homomorphism problems has been the subject of intense study for some years. In this paper, we prove a decidable complexity dichotomy theorem for the partition function of Directed Graph homomorphisms. Our theorem applies to all non-negative weighted forms of the problem: given any fixed matrix A with non-negative algebraic entries, the partition function ZA(G) of Directed Graph homomorphisms from any Directed Graph G is either tractable in polynomial time or #P-hard, depending on the matrix A. The proof of the dichotomy theorem is combinatorial, but involves the definition of an infinite family of Graph homomorphism problems. The proof of its decidability on the other hand is algebraic and based on properties of polynomials.
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a decidable dichotomy theorem on Directed Graph homomorphisms with non negative weights
arXiv: Computational Complexity, 2010Co-Authors: Jinyi Cai, Xi ChenAbstract:The complexity of Graph homomorphism problems has been the subject of intense study. It is a long standing open problem to give a (decidable) complexity dichotomy theorem for the partition function of Directed Graph homomorphisms. In this paper, we prove a decidable complexity dichotomy theorem for this problem and our theorem applies to all non-negative weighted form of the problem: given any fixed matrix A with non-negative algebraic entries, the partition function Z_A(G) of Directed Graph homomorphisms from any Directed Graph G is either tractable in polynomial time or #P-hard, depending on the matrix A. The proof of the dichotomy theorem is combinatorial, but involves the definition of an infinite family of Graph homomorphism problems. The proof of its decidability is algebraic using properties of polynomials.
Hai Jin - One of the best experts on this subject based on the ideXlab platform.
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An efficient incremental strongly connected components algorithm for evolving Directed Graphs
SCIENTIA SINICA Informationis, 2019Co-Authors: Liao Xiaofei, Yu Zhang, Hai Jin, Yicheng Chen, Haikun Liu, Jin ZhaoAbstract:The strongly connected components (SCC) algorithm can contract a Directed Graph into a Directed acyclic Graph and is widely used in Directed Graph analysis applications, such as reachability queries. A variety of SCC algorithms for static Directed Graphs have been proposed but such algorithms require non-negligible runtime overheads to repeatedly perform computations on an entire Graph in response to the frequent changes in the evolving Directed Graphs that are ubiquitous in the real world. In general, evolving Directed Graphs are often evolving with minor changes (less than 5%).It allows us to compute SCC in an evolving Directed Graph on the basis of incremental computations in order to reduce the response time. This paper proposes Inc-SCC, an efficient incremental SCC algorithm for evolving Directed Graphs, reducing the data access and computation overhead of the algorithm by eliminating unnecessary computations, and using the disjoint feature of SCC for parallel processing to improve the performance of the SCC algorithm. We propose a heuristic optimization method to further speed up the convergence of Inc-SCC. Experiments show that Inc-SCC can be used to enhance the timeliness for evolving Directed Graphs. When the number of the changed edges of the entire Directed Graph is 5%, the speedup of Inc-SCC over the existing algorithm is from 2.8 to 12 times. When the number of thechanged edges of an entire Directed Graph is 0.5%, the speedup of Inc-SCC over the existing algorithm is from 2.9 to 12 times.
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efficient disk based Directed Graph processing a strongly connected component approach
IEEE Transactions on Parallel and Distributed Systems, 2018Co-Authors: Yu Zhang, Xiaofei Liao, Xiang Shi, Hai JinAbstract:Recently, there have been many disk-based systems proposed for iterative Graph processing. In the popular vertex/edge-centric systems, an iterative Directed Graph algorithm needs to reprocess many partitions so as to update their vertices’ states according to other non-convergent vertices for the unawareness of their dependencies. As a result, it induces high data access cost and a long time to converge. To tackle this problem, we propose a novel system for iterative Directed Graph processing with taking advantage of the strongly connected component (SCC) structure. It stores a Directed Graph into a Directed acyclic Graph (DAG) sketch, with each node representing a SCC in the original data Graph. During execution, the SCCs are loaded into memory for processing in a parallel way according to the topological order of the DAG sketch, and the vertices in each SCC are tried to be handled along the Directed paths. In this way, each SCC is able to reach convergence in order and needs to be loaded into the main memory for exactly once, getting much lower data access cost and faster convergence. Besides, the vertices of each SCC need fewer updates for convergence. We further develop a lightweight approach to maintain the DAG sketch and handle SCCs in an incremental way for evolving Graphs. Compared with the state-of-the-art methods, experimental results show that our approach achieves a performance improvements of 1.46-8.37 times for static Graphs, and can reduce the execution time by 61.4-72.7 percent for evolving Graphs.
