The end of polling : why and how to transform a REST API into a Data Streamin...Audrey Neveu
We know interactivity is the key to keep our user's interest alive but we can't reduce animation to UI anymore. Twitter, Waze, Slack... users are used to have real-time data in applications they love.
But how can you turn your static API into a stream of data? By pulling? Pushing? Webhook-ing? When talking about data streaming, we often think about WebSockets. But have you ever heard of Server-Sent Events?
In this talk, we will compare those technologies to understand which one you should opt for depending on your usecase and I'll show you how we have been even further by reducing the amount of data to transfer with JSON-Patch.
And because real-time data is not only needed by web (and because it's much more fun), I'll show you how we can make drone dance on streamed APIs.
The end of polling : why and how to transform a REST API into a Data Streamin...Audrey Neveu
We know interactivity is the key to keep our user's interest alive but we can't reduce animation to UI anymore. Twitter, Waze, Slack... users are used to have real-time data in applications they love.
But how can you turn your static API into a stream of data? By pulling? Pushing? Webhook-ing? When talking about data streaming, we often think about WebSockets. But have you ever heard of Server-Sent Events?
In this talk, we will compare those technologies to understand which one you should opt for depending on your usecase and I'll show you how we have been even further by reducing the amount of data to transfer with JSON-Patch.
And because real-time data is not only needed by web (and because it's much more fun), I'll show you how we can make drone dance on streamed APIs.
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Storing such huge event streams into HDFS or a NoSQL datastore is feasible and not such a challenge anymore. But if you want to be able to react fast, with minimal latency, you can not afford to first store the data and doing the analysis/analytics later. You have to be able to include part of your analytics right after you consume the event streams. Products for doing event processing, such as Oracle Event Processing or Esper, are avaialble for quite a long time and also used to be called Complex Event Processing (CEP). In the last 3 years, another family of products appeared, mostly out of the Big Data Technology space, called Stream Processing or Streaming Analytics. These are mostly open source products/frameworks such as Apache Storm, Spark Streaming, Apache Samza as well as supporting infrastructures such as Apache Kafka. In this talk I will present the theoretical foundations for Event and Stream Processing and present what differences you might find between the more traditional CEP and the more modern Stream Processing solutions and show that a combination will bring the most value.
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)Apache Apex
This presentation will introduce usage of Apache Apex for Time Series & Data Ingestion Service by General Electric Internet of things Predix platform. Apache Apex is a native Hadoop data in motion platform that is being used by customers for both streaming as well as batch processing. Common use cases include ingestion into Hadoop, streaming analytics, ETL, database off-loads, alerts and monitoring, machine model scoring, etc.
Abstract: Predix is an General Electric platform for Internet of Things. It helps users develop applications that connect industrial machines with people through data and analytics for better business outcomes. Predix offers a catalog of services that provide core capabilities required by industrial internet applications. We will deep dive into Predix Time Series and Data Ingestion services leveraging fast, scalable, highly performant, and fault tolerant capabilities of Apache Apex.
Speakers:
- Venkatesh Sivasubramanian, Sr Staff Software Engineer, GE Predix & Committer of Apache Apex
- Pramod Immaneni, PPMC member of Apache Apex, and DataTorrent Architect
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。
1. Data API 2.0
MTDDC Meetup Tokyo 2014
2014.11.29 (Sat)
Yuji Takayama@Six Apart
2. My Social
icon
YUJI TAKAYAMA
Six Apart, Ltd.
Senior Product Manager
Movable Type Lead Engineer
Twitter: @yuji
Facebook: Yuji Takayama
Github: yuji
Mail: ytakayama@sixapart.com
3. Today’s Agenda
Movable Type Data API Overview
Movable Type Data API とはなにか?
Why Movable Type offers API?
なぜ、Movable Type は API を提供しているのか?
Introduce Data API v2.0
Movable Type Data API v2.0 のご紹介。v1.0 との違いについても
5. Movable Type
Data API
REST/JSON API for every websites and applications
Released with Movable Type 6.0 on Oct 17, 2013
6. Data API Features
REST / JSON API
特殊な処理を必要としない URL ベースの呼び出しと、結果は扱いやすい JSON 形式をサポート
MT Authentication and Role based permission
Movable Type が提供するロールベースのユーザー管理機能を利用した認証機能を提供
Pluggable / Extensible
Movable Type らしく拡張性も重視。プラグイン (Perl) によるエンドポイントの拡張、
コールバックを利用したフィルター処理、JSON 以外の出力形式を追加することも
JavaScript library available
JavaScript 用の開発ライブラリを標準提供。ブラウザの差異も吸収
7. Data API Show Case 1
Six Apart のごはんレシピ
• 新着一覧に表示するレシピを Data API で無限スクロール
• ページ遷移が必要ない
• 【利用者目線】気になるレシピを探しやすく
• 【制作者目線】ページ分割のための再構築が不要 = 負荷が低減
http://makanai.sixapart.jp/
8. Data API Show Case 2
ワンダードライビング
• Google Analytics と連携し、アクセス数の多い記事をランキング表示
• ほぼリアルタイムにページを更新
• 独自開発したサムネイル作成用エンドポイント
http://wonderdriving.com/
9. Data API Show Case 3
Loupe
• サイトのアクセス数を取得してグラフ表示
• 撮影した写真をすばやくアップロード
• 記事へのコメントにすばやく返信
• デバイスに最適化されたページ
• 必要なデータだけを送受信することで通信コストの低減
10. Data API Show Case 4
Movable Type Writer (仮)
• Movable Type の管理画面を使わずに記事を投稿
• Movable Type の管理画面を改造せずに、ニーズに併せる
• Google Chrome App
• おもいついた時にパッと書ける
• コンテンツに合わせた、適切なラベルと適切な配置で独自アプリに
12. Build web pages
Responsive Web Design
Templates
<html>
Content
13. The web of Things
“The Web of Things (WoT) is a set of software architectural styles and programming patterns that
allow real-world objects to be part of the World Wide Web. Similarly to what the Web
(Application Layer) is to the Internet (Network Layer), the Web of Things provides an Application
Layer that simplifies the creation of Internet of Things applications.
Rather than re-inventing completely new standards, the Web of Things reuses existing and well-known
Web standards used in the programmable Web (e.g, REST, HTTP, JSON), semantic Web
(e.g., JSON-LD, Microdata, etc.), the real-time Web (e.g, Websockets) and the social Web (e.g.,
oauth or social networks).”
— Wikipedia http://en.wikipedia.org/wiki/Web_of_Things —
14. Build web pages
Web Browser
Digital Car fridge
Signage
Mobile Applications
Templates
TV Watch
Data API
<html>
Content
Data API
Any Devices
15. Why Movable Type offers API? Because…
The Web of Things
PCやスマホだけにとどまらず、広がっていくウェブの世界
Mobile First, Content First
モバイル端末での閲覧に最適化。コンテンツを配信することで通信を最適化
Dynamic Site
リッチな表現は必要に応じてフロント側で実現
19. Data API v2.0 Features
Create/read/update/delete every objects
ほぼすべてのオブジェクトについて、CRUDのエンドポイントをサポート
Assign categories to an entry, save categories order
記事へのカテゴリの割り当てはもとより、カテゴリの順序を保存することも
Restrict Data API access for each site
各サイト単位で Data API のアクセスを禁止することが可能に
Search entries across the each site
サイトを横断して記事の検索が可能に
20. Data API v2.0 Features
Make a thumbnail for an asset
任意のサイズのサムネイル画像を作成可能に
Make a log from a front side
フロントエンドで発生したイベントもログに書き込み可能に
Build index/archive template
インデックス・テンプレート、アーカイブテンプレートの再構築を実行可能に
Run backup/restore
バックアップの生成はもとより、バックアップファイルを指定した復元も
24. Mobile Application x Data API x Website
Mobile Applications
Available at Data API v1.0 Available at Data API v2.0
Web Browser
Upload via Data API
Make thumbnail via
Rebuild main index via Data API
Data API
28. Get thumbnail
.done(function( data ) {
var url = “http://path/to/mt-data-api.cgi/v2/sites/1/assets/" +
data.id + "/thumbnail?width=200&square=1"
$.ajax({
url: url,
type: "GET",
dataType: 'json'
})
.done(function( data ) {
$('#result').append('<img src="' + data.url + '" width="200">');
});
});
29. Rebuild main index file
var url = “http://path/to/mt-data-api.cgi/v2/sites/1/templates/35/publish”;
$.ajax({
url: url,
type: "POST",
headers: {
'X-MT-Authorization': t
}
})
.done(function( data ) {
alert('Done!');
});
Template ID of
Main Index
Authentication
required
30. Data API 2.0 will be available in
Movable Type 6.1 (early 2015)