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Kurihara, Momo*; Yasutaka, Tetsuo*; Aono, Tatsuo*; Ashikawa, Nobuo*; Ebina, Hiroyuki*; Iijima, Takeshi*; Ishimaru, Kei*; Kanai, Ramon*; Karube, Jinichi*; Konnai, Yae*; et al.
Journal of Radioanalytical and Nuclear Chemistry, 322(2), p.477 - 485, 2019/11
Times Cited Count：2 Percentile：21.58(Chemistry, Analytical)We assessed the repeatability and reproducibility of methods for determining low dissolved radiocesium concentrations in freshwater in Fukushima. Twenty-one laboratories pre-concentrated three of 10 L samples by five different pre-concentration methods (prussian-blue-impregnated filter cartridges, coprecipitation with ammonium phosphomolybdate, evaporation, solid-phase extraction disks, and ion-exchange resin columns), and activity of radiocesium was measured. The z-scores for all of the 
Cs results were within 
2, indicating that the methods were accurate. The relative standard deviations (RSDs) indicating the variability in the results from different laboratories were larger than the RSDs indicating the variability in the results from each separate laboratory.
Miyamura, Hiroko; Ozahata, Satoshi*; Shinano, Yuji*; Miyashiro, Ryuhei*
Proceedings of 8th International Joint Conference on Computer Science and Software Engineering (JCSSE-2011), p.187 - 192, 2011/00
This paper proposes an adaptive visualization technique for representing a large-scale hierarchical dataset within a limited display space. A hierarchical dataset has nodes and links that reveal the parent-child relationship between the nodes. These nodes and links are described using graphics primitives. When the number of these primitives is large, it is difficult to recognize the structure of the hierarchical data because several primitives overlap within a display space. In order To overcome this difficulty, we propose an adaptive visualization technique for hierarchical datasets. The proposed technique selects an appropriate graph style according to the nodal density in each area.
Miyamura, Hiroko; Shinano, Yuji*; Ozahata, Satoshi*
Kashika Joho Gakkai-Shi, 30(Suppl.1), p.273 - 276, 2010/07
We propose an adaptive visualization technique for representing a large-scale hierarchical dataset within limited display space. A hierarchical dataset has nodes and links showing the parent-child relationship between the nodes. These nodes and links are described using graphics primitives. When the number of these primitives is large, it is difficult to recognize the structure of the hierarchical data because many primitives are overlapped within a limited region. To overcome this difficulty, we propose an adaptive visualization technique for hierarchical datasets. The proposed technique selects an appropriate graph style according to the nodal density in each area.
Miyamura, Hiroko; Shinano, Yuji*; Miyashiro, Ryuhei*; Saito, Takafumi*
Joho Shori Gakkai Rombunshi; Suri Moderuka To Oyo (Internet), 2(2), p.103 - 112, 2009/03
In branch-and-bound algorithms for integer programming, runtime behavior of the algorithms depends much on branching strategy. However, from a huge computation log of a large program, it is difficult to explore a key factor for effective branching. To analyze which factor of branching strategy is essential, we develop a system for visualization of growing process of a large branch-and-bound tree. The proposed system provides intuitive understanding how branching strategy affects branch-and-bound process.
