ViewMonitor can measure view positions with accuracy. This library is to check design sheet from native app.
detail:
https://github.com/daisuke0131/ViewMonitor
Guilty Couch Potato: The role of negative emotions in recovery through media useAllison Eden
Individuals with depleted self-control may be particularly prone to engage in negative
appraisals of media use. These appraisals may lessen the potentially restorative effects of media. Results from an online survey support this relationship, suggesting that “guilty couch potatoes” are least likely to experience restorative benefits of entertaining media use
ViewMonitor can measure view positions with accuracy. This library is to check design sheet from native app.
detail:
https://github.com/daisuke0131/ViewMonitor
Guilty Couch Potato: The role of negative emotions in recovery through media useAllison Eden
Individuals with depleted self-control may be particularly prone to engage in negative
appraisals of media use. These appraisals may lessen the potentially restorative effects of media. Results from an online survey support this relationship, suggesting that “guilty couch potatoes” are least likely to experience restorative benefits of entertaining media use
T21.Fujitsu World Tour India 2016-Education, Research and DesignFujitsu India
Find out how Fujitsu has helped hundreds of customers in India redefine their High Performance computing environment - and streamlined processes to enhance throughput.
Carrenza at Government ICT 2016 / The advantages of highly automated cloudsCarrenza
The Carrenza team held host to an hour interactive seminar be on the topic of ‘The advantages of highly automated clouds’.
Taking advantage of cloud computing for development purposes, and the running of production systems has become a de facto approach for most organisations, government sector departments and small businesses alike. Being able to manage this in a fully automated and secure manner however can still prove challenging, and even more so now that many are working and managing a multi-cloud environment spanning across a number of different providers. Join us to explore our findings having worked with many public sector organisations and enterprises alike.
Learning points;
The benefits of cloud Automation & Dev-Ops and what it looks like
How to manage a Multi-Cloud infrastructure
Using opensource tools for application delivery
Compliant as standard
Speakers:
Matthew McGrory, Managing Director, Carrenza
Jason Reid, CTO, R3 Labs
Material de apoio para a disciplina de Ética e Legislação em Comunicação do curso de Publicidade e Propaganda da Faculdade Cásper Líbero - São Paulo (SP).
セル生産方式におけるロボットの活用には様々な問題があるが,その一つとして 3 体以上の物体の組み立てが挙げられる.一般に,複数物体を同時に組み立てる際は,対象の部品をそれぞれロボットアームまたは治具でそれぞれ独立に保持することで組み立てを遂行すると考えられる.ただし,この方法ではロボットアームや治具を部品数と同じ数だけ必要とし,部品数が多いほどコスト面や設置スペースの関係で無駄が多くなる.この課題に対して音𣷓らは組み立て対象物に働く接触力等の解析により,治具等で固定されていない対象物が組み立て作業中に運動しにくい状態となる条件を求めた.すなわち,環境中の非把持対象物のロバスト性を考慮して,組み立て作業条件を検討している.本研究ではこの方策に基づいて,複数物体の組み立て作業を単腕マニピュレータで実行することを目的とする.このとき,対象物のロバスト性を考慮することで,仮組状態の複数物体を同時に扱う手法を提案する.作業対象としてパイプジョイントの組み立てを挙げ,簡易な道具を用いることで単腕マニピュレータで複数物体を同時に把持できることを示す.さらに,作業成功率の向上のために RGB-D カメラを用いた物体の位置検出に基づくロボット制御及び動作計画を実装する.
This paper discusses assembly operations using a single manipulator and a parallel gripper to simultaneously
grasp multiple objects and hold the group of temporarily assembled objects. Multiple robots and jigs generally operate
assembly tasks by constraining the target objects mechanically or geometrically to prevent them from moving. It is
necessary to analyze the physical interaction between the objects for such constraints to achieve the tasks with a single
gripper. In this paper, we focus on assembling pipe joints as an example and discuss constraining the motion of the
objects. Our demonstration shows that a simple tool can facilitate holding multiple objects with a single gripper.
【DLゼミ】XFeat: Accelerated Features for Lightweight Image Matchingharmonylab
公開URL:https://arxiv.org/pdf/2404.19174
出典:Guilherme Potje, Felipe Cadar, Andre Araujo, Renato Martins, Erickson R. ascimento: XFeat: Accelerated Features for Lightweight Image Matching, Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
概要:リソース効率に優れた特徴点マッチングのための軽量なアーキテクチャ「XFeat(Accelerated Features)」を提案します。手法は、局所的な特徴点の検出、抽出、マッチングのための畳み込みニューラルネットワークの基本的な設計を再検討します。特に、リソースが限られたデバイス向けに迅速かつ堅牢なアルゴリズムが必要とされるため、解像度を可能な限り高く保ちながら、ネットワークのチャネル数を制限します。さらに、スパース下でのマッチングを選択できる設計となっており、ナビゲーションやARなどのアプリケーションに適しています。XFeatは、高速かつ同等以上の精度を実現し、一般的なラップトップのCPU上でリアルタイムで動作します。