グリッド間の電力融通を考慮したレジリエントな電力網分割

Open House, ISM in Tachikawa, 2015.6.19統計数理研究所オープンハウス（立川）、H27.6.19ポスター発

Core Challenge 2023: Solver and Graph Descriptions

This paper collects all descriptions of solvers and ISR instances submitted to CoRe Challenge 2023.Comment: arXiv admin note: text overlap with arXiv:2208.02495, arXiv:2207.1395

Sapporo: A workflow execution service that encourages the reuse of workflows in various languages in bioinformatics [version 2; peer review: 1 approved, 2 approved with reservations]

The increased demand for efficient computation in data analysis encourages researchers in biomedical science to use workflow systems. Workflow systems, or so-called workflow languages, are used for the description and execution of a set of data analysis steps. Workflow systems increase the productivity of researchers, specifically in fields that use high-throughput DNA sequencing applications, where scalable computation is required. As systems have improved the portability of data analysis workflows, research communities are able to share workflows to reduce the cost of building ordinary analysis procedures. However, having multiple workflow systems in a research field has resulted in the distribution of efforts across different workflow system communities. As each workflow system has its unique characteristics, it is not feasible to learn every single system in order to use publicly shared workflows. Thus, we developed Sapporo, an application to provide a unified layer of workflow execution upon the differences of various workflow systems. Sapporo has two components: an application programming interface (API) that receives the request of a workflow run and a browser-based client for the API. The API follows the Workflow Execution Service API standard proposed by the Global Alliance for Genomics and Health. The current implementation supports the execution of workflows in four languages: Common Workflow Language, Workflow Description Language, Snakemake, and Nextflow. With its extensible and scalable design, Sapporo can support the research community in utilizing valuable resources for data analysis

CoRe Challenge 2022/2023: Empirical Evaluations for Independent Set Reconfiguration Problems (Extended Abstract)

In this extended abstract, we describe CoRe Challenge 2022/2023, an international competition series aiming to construct the technical foundation of practical research for Combinatorial Reconfiguration. This competition series targets one of the most well-studied reconfiguration problems, called the independent set reconfiguration problem under the token jumping model, which asks a step-by-step transformation between two given independent sets in a graph. Theoretically, the problem is PSPACE-complete, which implies that there exist instances such that even a shortest transformation requires super-polynomial steps with respect to the input size under the assumption of $NP \neq PSPACE$. The competition series consists of four tracks: three tracks take two independent sets of a graph as input, and ask the existence of a transformation, a shortest transformation, a longest transformation between them; and the last track takes only a number of vertices as input, and asks for an instance of the specified number of vertices that needs a longer shortest transformation steps. We describe the background of the competition series and highlight the results of the solver and graph tracks

sapporo-wes/sapporo-service: 1.5.0

<h2>What's Changed</h2> <ul> <li>Introduce workflow run crate by @inutano in https://github.com/sapporo-wes/sapporo-service/pull/32</li> </ul> <p><strong>Full Changelog</strong>: https://github.com/sapporo-wes/sapporo-service/compare/1.4.9...1.5.0</p&gt

Electricity Self-Sufficient Community Clustering for Energy Resilience

Local electricity generation and sharing has been given considerable attention recently for its disaster resilience and other reasons. However, the process of designing local sharing communities (or local grids) is still unclear. Thus, this study empirically compares algorithms for electricity sharing community clustering in terms of self-sufficiency, sharing cost, and stability. The comparison is performed for all 12 months of a typical year in Yokohama, Japan. The analysis results indicate that, while each individual algorithm has some advantages, an exhaustive algorithm provides clusters that are highly self-sufficient. The exhaustive algorithm further demonstrates that a clustering result optimized for one month is available across many months without losing self-sufficiency. In fact, the clusters achieve complete self-sufficiency for five months in spring and autumn, when electricity demands are lower