13197 research outputs found
Sort by
シュウハスウ シフトガタ ＷｉＦｉ バックスキャッター タグ オ モチイタ タクナイ コウドウ ニンシキ システム ト ソノ ヒョウカ
Get PDF奈良先端科学技術大学院大学修士(工学)master thesi
Exploring the Impact of the COVID-19 Pandemic on Twitter in Japan: Qualitative Analysis of Disrupted Plans and Consequences
No full textBackground:
Despite being a pandemic, the impact of the spread of COVID-19 extends beyond public health, influencing areas such as the economy, education, work style, and social relationships. Research studies that document public opinions and estimate the long-term potential impact after the pandemic can be of value to the field.
Objective:
This study aims to uncover and track concerns in Japan throughout the COVID-19 pandemic by analyzing Japanese individuals’ self-disclosure of disruptions to their life plans on social media. This approach offers alternative evidence for identifying concerns that may require further attention for individuals living in Japan.
Methods:
We extracted 300,778 tweets using the query phrase Corona-no-sei (“due to COVID-19,” “because of COVID-19,” or “considering COVID-19”), enabling us to identify the activities and life plans disrupted by the pandemic. The correlation between the number of tweets and COVID-19 cases was analyzed, along with an examination of frequently co-occurring words.
Results:
The top 20 nouns, verbs, and noun plus verb pairs co-occurring with Corona no-sei were extracted. The top 5 keywords were graduation ceremony, cancel, school, work, and event. The top 5 verbs were disappear, go, rest, can go, and end. Our findings indicate that education emerged as the top concern when the Japanese government announced the first state of emergency. We also observed a sudden surge in anxiety about material shortages such as toilet paper. As the pandemic persisted and more states of emergency were declared, we noticed a shift toward long-term concerns, including careers, social relationships, and education.
Conclusions:
Our study incorporated machine learning techniques for disease monitoring through the use of tweet data, allowing the identification of underlying concerns (eg, disrupted education and work conditions) throughout the 3 stages of Japanese government emergency announcements. The comparison with COVID-19 case numbers provides valuable insights into the short- and long-term societal impacts, emphasizing the importance of considering citizens’ perspectives in policy-making and supporting those affected by the pandemic, particularly in the context of Japanese government decision-making.journal articl
Enhanced Pedestrian Detection Model Transfer-Trained on YOLOv8 Using DenseFused RGB and FIR Images
No full textThere are broad benefits to developing pedestrian spaces in terms of environment, culture, and economy. Given this context, accurately measuring pedestrian traffic is considered a critical indicator of sidewalk usage. Currently, the mainstream method for detecting pedestrians utilizes RGB camera footage installed along sidewalks. However, especially during nighttime and adverse weather conditions, insufficient lighting hampers detection accuracy. In contrast, Far-Infrared(FIR) imaging does not require a light source as it measures radiated heat. This study proposes a pedestrian detection and tracking model that integrates the strengths of both RGB and FIR cameras through image fusion processing. Specifically, pedestrians are detected from fused images using a pedestrian detector and then tracked using a tracking system to measure pedestrian counts. Additionally, a version of the pedestrian detector trained on the fused images through transfer learning is developed, and its detection results are compared with those from a non-transfer learning model. The experimental results demonstrate that using fused images for detection and tracking is effective in specific data scenarios, confirming the utility of the image fusion model under varied conditions.conference pape
DNA double-strand breaks enhance brassinosteroid signaling to activate quiescent center cell division in Arabidopsis
Get PDFIn Arabidopsis roots, the quiescent center (QC), a group of slowly dividing cells located at the center of the stem cell niche, functions as an organizing center to maintain the stemness of neighboring cells. Recent studies have shown that they also act as a reservoir for backup cells, which replenish DNA-damaged stem cells by activating cell division. The latter function is essential for maintaining stem cells under stressful conditions, thereby guaranteeing post-embryonic root development in fluctuating environments. In this study, we show that one of the brassinosteroid receptors in Arabidopsis, BRASSINOSTEROID INSENSITIVE1-LIKE3 (BRL3), plays a major role in activating QC division in response to DNA double-strand breaks. SUPPRESSOR OF GAMMA RESPONSE 1, a master transcription factor governing DNA damage response, directly induces BRL3. DNA damage-induced QC division was completely suppressed in brl3 mutants, whereas QC-specific overexpression of BRL3 activated QC division. Our data also showed that BRL3 is required to induce the AP2-type transcription factor ETHYLENE RESPONSE FACTOR 115, which triggers regenerative cell division. We propose that BRL3-dependent brassinosteroid signaling plays a unique role in activating QC division and replenishing dead stem cells, thereby enabling roots to restart growing after recovery from genotoxic stress.journal articl
ジョウホウ インフラ ノ クライ ミライ AI/BC ト ショクリョウ ニタク ナラ ドウスル
No full textvideo/mp4AIの機能的な負の側面に関しては、様々なメディアが取り上げています。しかし、環境負荷に関する報道はほとんどありません。本講演では、AIやブロックチェインなどの計算処理に、なぜ大量の電力を消費するのか、解決方法を提案し具体化できる人材が、なぜ居ないのか。居たとして、電力を削減するには、どう考えるのかについて概観します。講演日: 2024年10月5日講演場所: 生駒市生涯学習施設 たけまるホール（大ホール）講演者所属: 情報科学領域vide
Assessing Authenticity and Anonymity of Synthetic User-generated Content in the Medical Domain
No full textSince medical text cannot be shared easily due to privacy concerns, synthetic data bears much potential for natural language processing applications. In the context of social media and user-generated messages about drug intake and adverse drug effects, this work presents different methods to examine the authenticity of synthetic text. We conclude that the generated tweets are untraceable and show enough authenticity from the medical point of view to be used as a replacement for a real Twitter corpus. However, original data might still be the preferred choice as they contain much more diversity.conference pape