Measurement of eGovernment user satisfaction and impactsvdpeijl
Presentation held at the eGovMonet meeting in Hungary on 26 March 2009. Presenting the results of the study conducted by Deloitte and Indigove for the European Commission on \'Measurement of eGovernment user satisfaction and impact\'. See also: http://www.epractice.eu/en/library/288705
Measurement of eGovernment user satisfaction and impactsvdpeijl
Presentation held at the eGovMonet meeting in Hungary on 26 March 2009. Presenting the results of the study conducted by Deloitte and Indigove for the European Commission on \'Measurement of eGovernment user satisfaction and impact\'. See also: http://www.epractice.eu/en/library/288705
Con l'occasione del 1* Universitary Crossfit Contest organizzato da CrossFit RedWall Cusferrara si terrà un master su:
PALEODIET E CROSSFIT
-consigli pratici per un alimentazione funzionale e migliorativa della performance
-come combinare all'allenamento la dieta alimentare per riduzione della massa grassa e aumento della tonicita' muscolare.
Relatore: Jacopo Zuffi
R&S GJAV
Get Your Business Found on Google! (Bahasa Indonesia)jkairupan
This is a deck I presented to Indonesian SMB owners in various local conferences in 2014.
The product has since been upgraded and optimized, now called "Google My Business"
Jacopo Zuffi, responsabile commerciale presenta il format di GJAV in occasione del PMIcamp svoltosi a Siena presso l'universtà di comunicazione e marketing.
This ppt. demonstrates the technology that is being used in schools to help students learn. As technology continues to evolve, teachers need to learn how to utilize these instructional tools for the benefit of the 21st Century learner!
Ethically-donated fresh, functional human tissues can be used to better predict the likely effect of drugs during clinical trials. As the closest possible model of drug function in patients, fresh human tissues are playing an increasingly important role in de-risking the drug discovery process, helping pharmaceutical and biotechnology companies to make earlier go/no-go decisions based on human data.
5 SEO Mistakes that are Costing you Millions (Travel Edition)Powered by Search
February 25, 2015 Powered by Search participated in a Masterclassing event to promote the millions of dollars companies are loosing by not implementing best practise SEO techniques.
Oversea Maker Faire Meetup 2016 Tokyo Report
https://medium.com/@tks/oversea-maker-faire-meetup-2016-tokyo-b8518e2a3248#.8tt1nz9ee
We MakerFaire Organizer from 7 citiys meet at 5/Aug 2016 at Tokyo, present day of Maker Faire Tokyo.
Bangkok/Hongkong/Seoul/Shanghai/Singapore/Shenzhen/Trondheim!
I got slide by bunnie (@bunniestudios)
Why I Like Hardware Hacking (and if you haven't tried it, here's a few tips on getting started!) bunnie
video
https://youtu.be/RVI77LwkeM0
https://togetter.com/li/1329842
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。