665 research outputs found

    決定グラフを用いた暗黙的グラフ列挙に関する研究

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    京都大学新制・課程博士博士(情報学)甲第23548号情博第778号新制||情||132(附属図書館)京都大学大学院情報学研究科通信情報システム専攻(主査)教授 湊 真一, 教授 山本 章博, 准教授 川原 純学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA

    Evaluation of a Home Biomonitoring Autonomous Mobile Robot

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    Increasing population age demands more services in healthcare domain. It has been shown that mobile robots could be a potential solution to home biomonitoring for the elderly. Through our previous studies, a mobile robot system that is able to track a subject and identify his daily living activities has been developed. However, the system has not been tested in any home living scenarios. In this study we did a series of experiments to investigate the accuracy of activity recognition of the mobile robot in a home living scenario. The daily activities tested in the evaluation experiment include watching TV and sleeping. A dataset recorded by a distributed distance-measuring sensor network was used as a reference to the activity recognition results. It was shown that the accuracy is not consistent for all the activities; that is,mobile robot could achieve a high success rate in some activities but a poor success rate in others. It was found that the observation position of the mobile robot and subject surroundings have high impact on the accuracy of the activity recognition, due to the variability of the home living daily activities and their transitional process. The possibility of improvement of recognition accuracy has been shown too

    Enumerating Graph Partitions Without Too Small Connected Components Using Zero-suppressed Binary and Ternary Decision Diagrams

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    Partitioning a graph into balanced components is important for several applications. For multi-objective problems, it is useful not only to find one solution but also to enumerate all the solutions with good values of objectives. However, there are a vast number of graph partitions in a graph, and thus it is difficult to enumerate desired graph partitions efficiently. In this paper, an algorithm to enumerate all the graph partitions such that all the weights of the connected components are at least a specified value is proposed. To deal with a large search space, we use zero-suppressed binary decision diagrams (ZDDs) to represent sets of graph partitions and we design a new algorithm based on frontier-based search, which is a framework to directly construct a ZDD. Our algorithm utilizes not only ZDDs but also ternary decision diagrams (TDDs) and realizes an operation which seems difficult to be designed only by ZDDs. Experimental results show that the proposed algorithm runs up to tens of times faster than an existing state-of-the-art algorithm

    Enumerating All Subgraphs Under Given Constraints Using Zero-Suppressed Sentential Decision Diagrams

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    Subgraph enumeration is a fundamental task in computer science. Since the number of subgraphs can be large, some enumeration algorithms exploit compressed representations for efficiency. One such representation is the Zero-suppressed Binary Decision Diagram (ZDD). ZDDs can represent the set of subgraphs compactly and support several poly-time queries, such as counting and random sampling. Researchers have proposed efficient algorithms to construct ZDDs representing the set of subgraphs under several constraints, which yield fruitful results in many applications. Recently, Zero-suppressed Sentential Decision Diagrams (ZSDDs) have been proposed as variants of ZDDs. ZSDDs can be smaller than ZDDs when representing the same set of subgraphs. However, efficient algorithms to construct ZSDDs are known only for specific types of subgraphs: matchings and paths. We propose a novel framework to construct ZSDDs representing sets of subgraphs under given constraints. Using our framework, we can construct ZSDDs representing several sets of subgraphs such as matchings, paths, cycles, and spanning trees. We show the bound of sizes of constructed ZSDDs by the branch-width of the input graph, which is smaller than that of ZDDs by the path-width. Experiments show that our methods can construct ZSDDs faster than ZDDs and that the constructed ZSDDs are smaller than ZDDs when representing the same set of subgraphs

    Experimental study of the atmospheric neutrino backgrounds for proton decay to positron and neutral pion searches in water Cherenkov detectors

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    The atmospheric neutrino background for proton decay to positron and neutral pion in ring imaging water Cherenkov detectors is studied with an artificial accelerator neutrino beam for the first time. In total, about 314,000 neutrino events corresponding to about 10 megaton-years of atmospheric neutrino interactions were collected by a 1,000 ton water Cherenkov detector (KT). The KT charged-current single neutral pion production data are well reproduced by simulation programs of neutrino and secondary hadronic interactions used in the Super-Kamiokande (SK) proton decay search. The obtained proton to positron and neutral pion background rate by the KT data for SK from the atmospheric neutrinos whose energies are below 3 GeV is about two per megaton-year. This result is also relevant to possible future, megaton-scale water Cherenkov detectors.Comment: 13 pages, 16 figure

    Measurements of neutrino oscillation in appearance and disappearance channels by the T2K experiment with 6.6 x 10(20) protons on target

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    111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee comments111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee comments111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee commentsWe thank the J-PARC staff for superb accelerator performance and the CERN NA61/SHINE Collaboration for providing valuable particle production data. We acknowledge the support of MEXT, Japan; NSERC, NRC, and CFI, Canada; CEA and CNRS/IN2P3, France; DFG, Germany; INFN, Italy; National Science Centre (NCN), Poland; RSF, RFBR and MES, Russia; MINECO and ERDF funds, Spain; SNSF and SER, Switzerland; STFC, UK; and the U. S. Deparment of Energy, USA. We also thank CERN for the UA1/NOMAD magnet, DESY for the HERA-B magnet mover system, NII for SINET4, the WestGrid and SciNet consortia in Compute Canada, GridPP, UK, and the Emerald High Performance Computing facility in the Centre for Innovation, UK. In addition, participation of individual researchers and institutions has been further supported by funds from ERC (FP7), EU; JSPS, Japan; Royal Society, UK; and DOE Early Career program, USA
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