| 安見 嘉人 | D, 中間発表 | ディペンダブルシステム学 | 井上 美智子, | 笠原 正治, | 大下 福仁, | 新谷 道広 |
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title: Population Protocols for Some Fundamental Problems
abstract: In recent years, autonomous distributed systems using low-performance devices have attracted attention. With such low-performance devices, existing algorithms of distributed systems cannot be applied because functions of devices are greatly limited. Hence, in this research, we use a population protocol model that is a model for such low-performance devices, and consider the space complexity to solve basic tasks in the model. In particular, we focus on the uniform k-partition problem and graph class identification problems in the population protocol model. The goal of the uniform k-partition problem is to divide a population into k groups of the same size (k is a positive integer). An application of the uniform k-partition problem is to execute multiple tasks simultaneously by assigning different tasks to each group. The goal of graph class identification problems is to decide whether a given communication graph is in the desired class (e.g. whether the given communication graph is a ring graph). An application of the graph class identification problems is to understand properties of the communication graph in order to design efficient algorithms. As a results, in both problems, we clarify the upper and lower bounds with respect to the number of states for each agent on various assumptions. | ||||||
| 花房 亮太 | M, 2回目発表 | ネットワークシステム学 | 岡田 実, | 別所 康全 | ||
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title:A Feature Measurement for Rainfall Nowcast Using GNSS
abstract:In recent years, natural disaster caused by localized downpour of short duration have been on the increase. The lifetime of a cumulonimbus cloud, which brings heavy rainfall, is known to take about one hour from its generation to disappearance. So the time resolution of the current numerical prediction is not sufficient for nowcasting heavy rainfall. And satellite-based meteorological measurement is not suitable for observing water vapor at the low-layer troposphere. This study employs a GNSS (Global Navigation Satellite System) receiver as a sensing tool for observe the amount of water vapor with high frequency. Tropospheric delay can be obtained in the calculation process of GNSS precise positioning. Since the tropospheric delay varies with the amount of water vapor, it can be used as a feature quantity for rainfall nowcast. However, significant number of undesired false alarms are reported. This study proposes a feature measurement method using preprocessing for observed GNSS and meteorological data, and aims to quantitatively evaluate improvement in precision. language of the presentation: Japanese 発表題目: GNSSを利用した短時間降雨予測のための特徴量の抽出 発表概要: 近年、ゲリラ豪雨による自然災害が増加傾向にある。 豪雨の発生要因である積乱雲は発生から消滅までが約１時間とされており、数値予報による時間分解能では 不十分である。また、気象衛星を用いた観測では対流圏の低層の水蒸気量観測には適していない。 そこで本研究では、高頻度に対流圏内の水蒸気量を観測可能なツールとしてGNSS (Global Navigation Satellite System)を用いる。 GNSSの精密測位の計算過程で得られる対流圏遅延量が水蒸気量によって変化するため、短時間の降雨予測の 特徴量として利用できるが、判定誤りが多いことが報告されている。 本研究では、GNSSや気象センサから得られた観測値や特徴量に適切な前処理を施すことで、 判定精度の改善に寄与するかを定量的に評価することを目的とする。 | ||||||