Kento Sugiura

Control of nonmagnetic particles using a magnetic field

Abstract A force and/or torque are induced in a material under the imposition of a magnetic field. Their magnitudes are different from those acting on the surrounding materials because of the difference in their physical properties. Therefore, a magnetic field is a powerful tool for controlling a second phase in a mother phase such as particles suspended in a liquid. In this paper, we focus on two processes. The first one is a novel method of magnetic filtration in which schwertmannite particles in wastewater are controlled using a magnetic field. The second one is a refining process for a metallic alloy structure during solidification in which solid particles suspended in the liquid phase are controlled using the force excited by the simultaneous imposition of a magnetic field and alternating current.

Grouping Methods for Pattern Matching in Probabilistic Data Streams

In recent years, complex event processing has attracted considerable interest in research and industry.Pattern matching is used to find complex events in data streams. In probabilistic data streams, however, the system may find multiple matches in a given time interval. This may result in inappropriate matches, because multiple matches may correspond to a single event. We therefore propose grouping methods of matches for probabilistic data streams, and call such merged matches a group. We describe the definitions and generation methods of groups, propose an efficient approach for calculating an occurrence probability of a group, and compare the proposed approach with a naive one by experiment. The results demonstrate the properties and effectiveness of the proposed method.

Histogram Construction for Difference Analysis of Spatio-Temporal Data on Array DBMS

To analyze scientific data, there are frequent demands for comparing multiple datasets on the same subject to detect any differences between them. For instance, comparison of observation datasets in a certain spatial area at different times or comparison of spatial simulation datasets with different parameters are considered to be important. Therefore, this paper proposes a difference operator in spatio-temporal data warehouses, based on the notion of histograms in the database research area. We propose a difference histogram construction method and they are used for effective and efficient data visualization in difference analysis. In addition, we implement the proposed algorithms on an array DBMSs SciDB, which is appropriate to process and manage scientific data. Experiments are conducted using mass evacuation simulation data in tsunami disasters, and the effectiveness and efficiency of our methods are verified.

Top- k Pattern Matching Using an Information-Theoretic Criterion over Probabilistic Data Streams

As the development of data mining technologies for sensor data streams, more sophisticated methods for complex event processing are demanded. In the case of event recognition, since event recognition results may contain errors, we need to deal with the uncertainty of events. We therefore consider probabilistic event data streams with occurrence probabilities of events, and develop a pattern matching method based on regular expressions. In this paper, we first analyze the semantics of pattern matching over non-probabilistic data streams, and then propose the problem of top-k pattern matching over probabilistic data streams. We introduce the use of an information-theoretic criterion to select appropriate matches as the result of pattern matching. Then, we present an efficient algorithm to detect top-k matches, and evaluate the effectiveness of our approach using real and synthetic datasets.

Monitoring Query Processing in Mobile Robot Databases

In this paper, we propose methods for monitoring query processing in mobile robot databases. We assume that a mobile robot can move based on the specified movement plan and perform sensing (e.g., temperature measurements) at the specified points. The purpose of our query processing is to reduce the total travel and measurement time while ensuring the given sensing quality requirements. We develop a framework based on an existing approach in sensor databases. Since features of mobile robots are different from those of sensor networks, we extend the former approach considering our context. We propose four algorithms for planning robot movements and compare these methods in simulation-based experiments.