Term

Microelectronics Commons

Overview

最終更新: 2026年7月9日

CHIPS法に基づき、米国内での半導体プロトタイピングや製造能力の強化、人材育成を目的とした国防総省主導のネットワークおよび支援プログラム。

Mentioned Articles

2 件

Research Papers

5 件
  • Intermetallic Bonding for High-Temperature Microelectronics and Microsystems: Solid-Liquid Interdiffusion Bonding

    K. Aasmundtveit, T. Luu, Hoang-Vu Nguyen, AndreasLarsson, T. A. Tollefsen

    201811 件引用Semantic Scholar

    This chapter is distributed under the terms of the Creative which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited Commons Attribution Licens.

  • Licensed Under Creative Commons Attribution CC BY-NC Nanoelectronics : A Primer

    M. Sadiku, Yogita P. Akhare, S. Musa, R. Perry

    20190 件引用Semantic Scholar
  • Digital Commons @ University of Digital Commons @ University of South Florida South Florida
    0 件引用Semantic Scholar
  • ODU Digital Commons ODU Digital Commons

    M. Ojha, A. A. Elmustafa

    0 件引用Semantic Scholar
  • A Curated Spanish-Language Dataset for Detecting LGBTQIA-Phobic Language in Digital Environments

    C. Martínez-Araneda, Mariella Gutiérrez Valenzuela, P. Gómez-Meneses, Diego Maldonado Montiel, A. Navarrete, C. Vidal-Castro, Elías Pérez Álvarez

    20260 件引用Semantic Scholar

    This article presents the LGBTQIA phobia dataset (augmented and balanced), a curated Spanish-language corpus designed to support research on the automated detection of discriminatory and hateful language targeting LGBTQIA+ communities in digital environments. The dataset comprises 1,000 short textual phrases collected from publicly available content on the web, X/Twitter, Instagram, TikTok, and YouTube comments. Each instance was manually annotated by three independent raters using a binary labeling scheme (1 is LGBTQIA phobic; 0 is non-LGBTQIA phobic). To improve robustness and reproducibility, text augmentation and class balancing via under sampling were applied. The final dataset is evenly distributed across classes and released under a Creative Commons Attribution 4.0 International license through Zenodo. This resource aims to bridge the gap in Spanish-language datasets for hate speech detection, aiding future research in content moderation, bias analysis, and the creation of inclusive artificial intelligence systems.

External Mentions

5 件