Search

Your search keyword '"Takahashi, Wataru"' showing total 1,765 results
Start Over Author "Takahashi, Wataru"
1,765 results on '"Takahashi, Wataru"'

1. Time for aCTIon: Automated Analysis of Cyber Threat Intelligence in the Wild

Author

Siracusano, Giuseppe, Sanvito, Davide, Gonzalez, Roberto, Srinivasan, Manikantan, Kamatchi, Sivakaman, Takahashi, Wataru, Kawakita, Masaru, Kakumaru, Takahiro, and Bifulco, Roberto

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

Cyber Threat Intelligence (CTI) plays a crucial role in assessing risks and enhancing security for organizations. However, the process of extracting relevant information from unstructured text sources can be expensive and time-consuming. Our empirical experience shows that existing tools for automated structured CTI extraction have performance limitations. Furthermore, the community lacks a common benchmark to quantitatively assess their performance. We fill these gaps providing a new large open benchmark dataset and aCTIon, a structured CTI information extraction tool. The dataset includes 204 real-world publicly available reports and their corresponding structured CTI information in STIX format. Our team curated the dataset involving three independent groups of CTI analysts working over the course of several months. To the best of our knowledge, this dataset is two orders of magnitude larger than previously released open source datasets. We then design aCTIon, leveraging recently introduced large language models (GPT3.5) in the context of two custom information extraction pipelines. We compare our method with 10 solutions presented in previous work, for which we develop our own implementations when open-source implementations were lacking. Our results show that aCTIon outperforms previous work for structured CTI extraction with an improvement of the F1-score from 10%points to 50%points across all tasks.

Published
2023

7. Real-time markerless tumour tracking with patient-specific deep learning using a personalized data generation strategy: Proof of concept by phantom study

Author

Takahashi, Wataru, Oshikawa, Shota, and Mori, Shinichiro

Subjects
Physics - Medical Physics
Abstract

Objective: For real-time markerless tumour tracking in stereotactic lung radiotherapy, we propose a different approach which uses patient-specific deep learning (DL) using a personalized data generation strategy, avoiding the need for collection of a large patient data set. We validated our strategy with digital phantom simulation and epoxy phantom studies. Methods: We developed lung tumour tracking for radiotherapy using a convolutional neural network trained for each phantom's lesion by using multiple digitally reconstructed radiographs (DRRs) generated from each phantom's treatment planning 4D-CT. We trained tumour-bone differentiation using large numbers of training DRRs generated with various projection geometries to simulate tumour motion. We solved the problem of using DRRs for training and X-ray images for tracking by using the training DRRs with random contrast transformation and random noise addition. Results: We defined adequate tracking accuracy as the % frames satisfying < 1 mm tracking error of the isocentre. In the simulation study, we achieved 100% tracking accuracy in 3-cm spherical and 1.5 x 2.25 x 3-cm ovoid masses. In the phantom study, we achieved 100% and 94.7% tracking accuracy in 3- and 2-cm spherical masses, respectively. This required 32.5 ms/frame (30.8 fps) real-time processing. Conclusions: We proved the potential feasibility of a real-time markerless tumour tracking framework for stereotactic lung radiotherapy based on patient-specific DL with personalized data generation with digital phantom and epoxy phantom studies. Advances in Knowledge: Using DL with personalized data generation is an efficient strategy for real-time lung tumour tracking., Comment: 10 pages, 11 figures, 2 tables, accepted for publication in The British Journal of Radiology

Published
2020
Full Text
View/download PDF

12. Development of Philadelphia chromosome-negative acute myeloid leukemia with IDH2 and NPM1 mutations in a patient with chronic myeloid leukemia who showed a major molecular response to tyrosine kinase inhibitor therapy

Author

Nakamura, Fumi, Arai, Honoka, Nannya, Yasuhito, Ichikawa, Motoshi, Furuichi, Shiho, Nagasawa, Fusako, Takahashi, Wataru, Handa, Tomoyuki, Nakamura, Yuko, Tanaka, Hiroko, Nakamura, Yuka, Sasaki, Ko, Miyano, Satoru, Ogawa, Seishi, and Mitani, Kinuko

Published
2021
Full Text
View/download PDF

25. Introduction of Internal Circulation-Based Cooling Methods and Green Coolants in Milling via Cutting Tool and Tooling Design.

Author

Radchenko, Ilia, Takahashi, Wataru, Takahashi, Hidebumi, Abe, Taro, and Sasahara, Hiroyuki

Subjects
COOLANTS, CUTTING tools, MILLING cutters, COOLING, CUTTING force, SAFETY factor in engineering, MINERAL oils, MECHANICAL alloying, SUSTAINABLE architecture
Abstract

Featured Application: The results of the following design investigation can be used in the field of machining, particularly when developing new types of cutting tools and tooling. This paper describes the process of the design and verification of a milling tool and tooling that may contribute to the renouncement of the flood cooling method when mineral oils and oil-in-water emulsions are used as coolants. The proposed solutions are based on the idea of coolant supply in internal channels created inside of a cutting tool. As an alternative to the aforementioned mineral oil-based coolants, liquids with higher cooling efficiency and environmental friendliness (green coolants) were considered. Given coolants' possible lack of lubricating properties and negative (corrosive, etc.) influence on a machine tool's units, tooling delivers these coolants to the cutting tool and bypasses the standard machine tool's supply system. The geometry of the milling tool (a cutting insert with an internal channel) was tested in the framework of a stress simulation. To perform it, cutting force components F z , F y , and F x were determined empirically and then applied to the simulated area of contact between the tool and the workpiece. Based on the obtained principal stress values P 1 , P 2 , and P 3 , the factor of safety was calculated with the Mohr–Coulomb, P 1   m a x , and P 3   m i n failure criteria. The proposed milling tool, equipped with a novel type of labyrinth seal with no friction between its components, was experimentally tested to confirm its ability to maintain leak-tightness at different values of spindle speed (200~2000 rpm) and coolant supply volume (1.0~10.0 L/min). Based on the results of the stress simulation and the leak-tightness experiment, conclusions were drawn about further modernization and utilization prospects of the proposed milling tool and tooling design. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

50. Strong Convergence Theorems under Hybrid Methods for Two Nonlinear Mappings in Banach Spaces (Study on Nonlinear Analysis and Convex Analysis)

Author

Takahashi, Wataru

Subjects
47H09, 47H05, skew-generalized nonspreading mapping /hybrid method, Fixed point, shrinking projection method
Abstract

In this article, using the hybrid method defined by Nakajo and Takahashi [17], we first obtain a strong convergence theorem for two noncommutative nonlinear mappings in a Banach space. Next, using the shrinking projection method defined by Takahashi, Takeuchi and Kubota [25], we prove another strong convergence theorem for the mappings in a Banach space. Using these results, we get well-known and new strong convergence theorems by the hybrid method and the shrinking projection method in a Hilbert space and a Banach space.

Published
2021

Catalog

Books, media, physical & digital resources
See catalog results