Keiichi Kaneko

Bio: Keiichi Kaneko is an academic researcher from Tokyo University of Agriculture and Technology. The author has contributed to research in topics: Disjoint sets & Hypercube. The author has an hindex of 14, co-authored 170 publications receiving 732 citations. Previous affiliations of Keiichi Kaneko include Tokyo Gakugei University & Tokyo University of Agriculture.

An Algorithm for Node-Disjoint Paths in Pancake Graphs

Abstract: SUMMARY For any pair of distinct nodes in an n-pancake graph, we give an algorithm for construction of n � 1 internally disjoint paths connecting the nodes in the time complexity of polynomial order of n. The length of each path obtained and the time complexity of the algorithm are estimated theoretically and verified by computer simulation.

Node-to-set disjoint paths problem in pancake graphs

Abstract: In this paper, we give an algorithm for the nodeto-set disjoint paths problem in pancake graphs with its evaluation results. The algorithm is of polynomial order of n for an n-pancake graph. It is based on recursion and divided into two cases according to the distribution of destination nodes in classes into which all the nodes in a pancake graph are categorized. The sum of lengths of paths obtained and the time complexity of the algorithm are estimated and the average performance is evaluated based on computer simulation. key words: interconnection networks, graph algorithms, pancake graph, node-to-set disjoint paths, parallel computing

An Algorithm for Node-to-Set Disjoint Paths Problem in Burnt Pancake Graphs

Abstract: A burnt pancake graph is a variant of Cayley graphs and its topology is suitable for massively parallel systems. However, for a burnt pancake graph, there is much room for further research. Hence, in this study, we focus on n-burnt pancake graphs and propose an algorithm to obtain n disjoint paths from a source node to n destination nodes in polynomial order time of n, n being the degree of the graph. In addition, we estimate the time complexity of the algorithm and the sum of path lengths. We also give a proof of correctness of the algorithm. Moreover, we report the results of computer simulation to evaluate the average performance of the algorithm. key words: burnt pancake graph, disjoint paths, polynomial algorithm, fault tolerance, routing algorithm

An Algorithm for Node-to-Set Disjoint Paths Problem in Bi-Rotator Graphs

Abstract: An algorithm is described for solving the node-to-set disjoint paths problem in bi-rotator graphs, which are obtained by making each edge of a rotator graph bi-directional. The algorithm is of polynomial order of n for an n-bi-rotator graph. It is based on recursion and divided into three cases according to the distribution of destination nodes in the classes into which the nodes in a bi-rotator graph are categorized. We estimated that it obtains 2n - 3 disjoint paths with a time complexity of O(n5), that the sum of the path lengths is O(n3), and that the length of the maximum path is O(n2). Computer experiment showed that the average execution time was O(n3.9) and, the average sum of the path lengths was O(n3.0).

Node-to-Set Disjoint-Path Routing in Hierarchical Cubic Networks

Abstract: Hypercubes are a simple topology frequently used as interconnection network of parallel systems. However, hypercubes connecting a significant number of nodes also have an impractically high number of edges. To address this issue, Ghose and Desai introduced a new topology, hierarchical cubic networks, containing almost half many edges than a hypercube of the same size. In this paper, we describe a node-to-set disjoint-path routing algorithm in a hierarchical cubic network HCN(n) finding node-disjoint paths between one source node and k (k≤n+1) destination nodes in O(knlog k) time complexity. Generated paths have lengths of at most 3n+k+3.

詞彙:描述、習得與教學=Vocabulary : description, acquisition and pedagogy

Abstract: 1. Word frequency and vocabulary size Paul Nation and Rob Waring 2. Variation in spoken and written language Michael McCarthy and Ron Carter 3. Vocabulary connections Rosamund Moon 4. Vocabulary and context William Nagy 5. Productive vs. receptive aspects of vocabulary Francine Melka 6. Models of lexical acquisition Paul Meara 7. Cognitive constraints on vocabulary acquisition Nick Ellis 8. Intralexical factors affecting the difficulty of vocabulary acquisition Batia Laufer 9. L1 influences on L2 vocabulary acquisition 10. Acquisition of the formal aspects of vocabulary Michael Swan 11. Vocabulary learning strategies Ann Ryan 12. Vocabulary and the syllabus Norbert Schmitt 13. Teaching vocabulary: most recent trends Felicity O'Dell 14. Vocabulary and testing John Read 15. Dictionaries, thesauruses, lexical resources Phil Schofield.

Computer supported collaborative learning

Abstract: 1 Peer Learning with Computers.- Collaborative problem solving with HyperCard: The influence of peer interaction on planning and information handling strategies.- Small group collaborative discovery learning from hypertext.- Peer interaction and writing: The process of revision.- Computer support for the collaborative learning of physics concepts.- The construction of shared knowledge in collaborative problem solving.- 2 Computer Support for Distance Learning.- Learning network design: Coordinating group interactions in formal learning environments over time and distance.- Computer-supported collaborative learning in a multi-media distance education environment.- Distance learning and computer-mediated communication: Interactive, quasiinteractive or monologue?.- 3 The Social and Organisational Context.- Educational practice within two local computer networks.- Technology's role in restructuring for collaborative learning.- 4 Models of Collaboration.- The negotiation of dialogue focus: An investigation of dialogue processes in joint planning in a computer based task.- Computational modelling of constructive interaction: Relaxing the mutuality hypothesis.- Designing human-computer collaborative learning.- 5 Design Issues.- Issues in computer supported collaborative learning.- Designing computer support for collaborative learning.