本発表では、の一つであるスプレー木の回転操作の方法について議論する。スプレー木の多くはボトムアップな回転を用いてスプレー操作を実現しているが、Afek達(2012)はより平衡のとれたの実現に向け、トップダウンな回転操作を提案している。本研究では既存の手法とAfek達の手法を実装し、両手法の性能について計算機実験に基づく比較を与える。

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演習などの授業で行われるメンタリングは学習者の学習行動に対し変容を与えるが，具体的にどのような効果を与えるか解明することは学習支援において重要である．本稿ではこのようなメンタリング内容を記録したメンタリングログを学生にフィードバックすることで，学習者の行動に与える影響を学習履歴とメンタリングログの分析から明らかにすることで，将来的な学習支援につなげることを目的としたシステムの構築と実際に得られたデータについて報告を行う．

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With the higher density of semiconductor devices, the yield prediction simulations such as the CAA (Critical Area Analysis) generally have to take a few days. Therefore, faster calculation is needed to reduce the elapsed time of the prediction. This study aims to propose a management structure of the design layout data which enable the elapsed time of CAA simulation to be considerably faster than the current one while still keeping the simulation accuracy unchanged. A management structure of the layout data using the range tree and interval tree and a prediction method of the query range size were developed to make the 2-dimensional range query in the CAA faster. The CAA calculation which is 10 times to 500 times faster than the current one was achieved.

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Highlly repetitive texts have been increasing still now. Examples are individual genomes, version controlled documents and repositries of source codes. Although grammar compression is an efficient for highly repetitive texts, the working space is still large for a data structure called reverse phrase dictionary. In this paper, we propose two methods for ruducing the space of reverse phrase dictionary. One is a space efficient dynamic 1-dimentional range search for reverse phrase dictionary, the other is a space reduction method of reverse phrase dictionary for a succinct represetation of grammar compression.

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The machine coordinate values that mechanical structure of 5-axis controlled machine tool causes interference are inherent in each machine tool, and can be estimated beforehand. In this report, the techniques for generating tool path of 5-axis controlled machining with consideration of the movable range of machine tool developed in the previous studies is enhanced. Comparing the machine coordinate values with the interference between mechanical structures calculated beforehand with the machine coordinate value corresponding to a tool attitude by using the technique of approximate nearest neighbor, the tool path without interference between mechanical structures could be generated.

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This paper deals with spatio-temporal indexing method for moving objects. In our research, we propose XAT (eXtended Adaptive Tree) structure, consisting of spatial trees and temporal trees, for fast search for spatio-temporal data. The searching process in XAT structure is divided into two steps. The first step roughly narrows down the potential solutions (moving objects) according to the given searching range. The last step fixes the real solution by checking the object’s moving track. We compare XAT structure and 3D structure, one of the conventional methods, by computer simulation. The result shows that XAT structure works faster than 3D structure when there is difference between the spatial search range and temporal search range and the objects’ moving areas are small.

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Since the emergence of the COVID-19 pandemic, disruptions in supply chains have significantly impacted both the global economy and asset markets. Despite a rising interest in supply-related data among policymakers, researchers, and financial market participants, existing indicators often wrestle with pervasive issues of low frequency and coarse granularity. In this carefully crafted paper, we ambitiously propose new, robust indices for the highfrequency nowcasting of disturbances specifically within the automotive supply chain. Firstly, by judiciously utilizing inter-factory transition data alongside time series anomaly detection methodologies, we have successfully created the Supply Chain Turbulence Index (SCTI). To further augment the SCTI, we introduce a novel, sophisticated technique, grounded on the principles of enhanced Variational Autoencoders, to diligently isolate supply factors contributing to bottlenecks in the supply chain, subsequently creating a nuanced subindex, dubbed SCTI-supply. The SCTI exhibits a strong correlation with existing statistics concerning supply chain delays and demonstrates the remarkable capability to detect micro-level production interruptions across various car manufacturers’ plants. On the other hand, SCTIsupply correlates effectively with low-frequency supply chain indicators we developed from established statistics and proves exceedingly effective in identifying supply shocks under rigorous event study analysis.

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本論文では，多相レコード計算のコンパイル方式を応用し軽量に実現可能な，型付き関数型言語の第一級オーバーロード方式を提案する．この方式の下では，オーバーロードされた関数は，オーバーロードされた型上のみを動く型変数で束縛された多相型を持つ第一級の関数として扱われる．本機能の実現に要求されるものは，型抽象におけるインスタンス変数の生成と，型適用におけるインスタンスの選択のみであり，これらは多相レコードコンパイルと同様の方式で達成できる．本方式はSML#コンパイラ上に実装され公開されている．

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The nearest neighbor algorithm has been one of the most basic class of techniques in the field of Pattern classification. It is also the most basic and important technique in the fields such as case-based reasoning (CBR), memory-based reasoning (MBR), and example-based natural language Processing (EBNLP). In the nearest neighbor algorithm, the computational cost of example retrieval is one of the most important issues, especially when the number of examples in the database becomes large. In the field of pattern classification, there exist several techniques for reducing the computational cost of the nearest neighbor algorithm, while in other fields such as CBR, MBR, and EBNLP, there has been no technique except for the one using massively parallel computers. This paper proposes a novel technique for optimizing the nearest neighbor algorithm, especially for the use in CBR, MBR, and EBNLP. The basic idea is to use similarity calculation template, a data structure that enumerates all the possible patterns of calculating similarity between two examples. In the method, the nearest neighbor retrieval process is optimized by generating retrieval queries from an input and similarity calculation templates in a certain order. Its major advantages are as follows : 1) it can be implemented without any expensive hardwave such as massively parallel computers, 2)it is easy to add new examples to the example database. Experimental results show that nearly constant time nearest neighbor retrieval is achieved, independently of the number of examples in the database.

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プログラミングにある程度習熟している学習者を対象にして,パーソナルコンピュータを使ってC言語のプログラミング演習を行っているときのキーの入力状況を記録し,プログラミング過程の分析を行った.記録したデータから得られる操作過程のプロトコルと再現された作成過程から,学生のプログラム構築方法を把握することができた.また,カテゴリー分析によって,各学生のシステム操作系列を明らかにした.そして,これらの分析結果からプログラミングスタイルが4タイプに分類できた.プログラム作成過程を分析すれば,学生のプログラム作成に関する知識や方略,苦手とする事項等を推測でき,演習内容の適切さの判断や学生へのきめの細かい指導に役立てられると考える.

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