Maximo is an IBM enterprise asset management for asset life-cycle and maintenance management. IBM Maximo® enterprise asset management solutions allow you to gain near real time visibility into asset usage, better govern assets, extend the useful life of capital equipment, improve return on assets and defer new purchases—while unifying processes for wide-ranging enterprising asset management functions across multiple sites.
Support enterprise asset management in key industries, including manufacturing, healthcare, life sciences, nuclear power, oil and gas, service providers, transportation and utilities.
Provide visibility and control over critical assets that affect compliance, risk and business performance.
Increase the useful life of physical assets with improved business processes for an increased return on assets and enhanced operational efficiency.
It has six major functions
Asset management – Achieve the control you need to more efficiently track and manage asset and location data throughout the asset lifecycle.
Work management – Manage both planned and unplanned work activities, from initial request through completion and recording of actuals.
Service management – Define service offerings, establish service level agreements (SLAs), more proactively monitor service level delivery and implement escalation procedures.
Contract management – Gain complete support for purchase, lease, rental, warranty, labor rate, software, master, blanket and user-defined contracts.
Inventory management – Know the details of asset-related inventory and its usage including what, when, where, how many and how valuable.
Procurement management – Support all phases of enterprise-wide procurement such as direct purchasing and inventory replenishment.
IBM MobileFirst Foundation, formerly known as IBM Worklight®, is a suite of software development products that allow developers to build and deliver mobile applications for the enterprise.
The MobileFirst Platform Foundation consists of:
MobileFirst Server – the middleware tier that provides a gateway between back-end systems and services and the mobile client applications.
MobileFirst API - both client and server-side APIs for developing and managing your enterprise mobile applications.
MobileFirst Studio - an optional all-inclusive development environment for developing enterprise apps on the MobileFirst platform. This is based on the Eclipse platform, and includes an integrated server, development environment, facilities to create and test all data adapters/services, a browser-based hybrid app simulator, and the ability to generate platform-specific applications for deployment.
MobileFirst Console – the console provides a dashboard and management portal for everything happening within your MobileFirst applications.
MobileFirst Application Center - a tool to make sharing mobile apps easier within an organization. Basically, it’s an app store for your enterprise.
BM talks about the MobileFirst Platform in two ways, based in its capabilities and also by its components. The capability areas are: Continuously Improve, Secure, Contextualize and Personalize, and Enrich with Data.
Continuously Improve - allows IT to manage application refresh cycles and collect in-app usage analytics. Secure - provides enterprise mobility management (EMM) capabilities. Contextualize and Personalize - allows developers to create mobile apps that are location- and context-aware. Enrich with Data - allows IT to join its mobile apps to internal and external data sources by connecting directly with IBM's Cloudant database as a service (DBaaS).
Nagare is a free and open-source web framework for developing web applications in Stackless Python. This allows web applications to be developed in much the same way as desktop applications, for rapid application development.
Nagare is a components based framework: a Nagare application is a composition of interacting components each one with its own state and workflow kept on the server.
Each component can have one or several views that are composed to generate the final web page. This enables the developers to reuse or write highly reusable components easily and quickly.
Nagare is also a continuation-based web framework which enables to code a web application like a desktop application, with no need to split its control flow in a multitude of controllers and with the automatic handling of the back, fork and refresh actions from the browser.
Its component model and use of the continuation come from the famous Seaside Smalltalk framework.
Furthermore, Nagare integrates the best tools and standard from the Python world. For example:
WSGI: binds the application to several possible publishers,
lxml: generates the DOM trees and brings to Nagare the full set of XML features (XSL, XPath, Schemas …),
setuptools: installs, deploys and extends the Nagare framework and the Nagare applications too,
Delphi is both an object oriented programming language (OOP) and an Integrated Development Environment (IDE). Published by the Embarcadero company (formerly CodeGear and more formerly Borland), Delphi is an alternative to language such as Visual Basic offering development with both rapidity and good quality.
Delphi includes the RunTime Library (RTL) that provides basic functionality across all the platforms. For Windows it provides the Visual Component Library (VCL), and for cross platform development it includes FireMonkey (FMX).
Delphi includes a code editor, a visual designer, an integrated debugger, a source code control component, and support for third-party plugins. The code editor features Code Insight (code completion), Error Insight (real-time error-checking), and refactoring.
The visual forms designer has traditionally used Visual Component Library (VCL) for native Windows development, but the FireMonkey (FMX) platform was later added for cross-platform development. Database support in Delphi is very strong. A Delphi project of a million lines to compile in a few seconds – one benchmark gave 170,000 lines per second.
It provides interfaces for the programmer to build an application using the Extensible Markup Language (XML), Extensible Stylesheet Language (XSL), Simple Object Access Protocol (SOAP), and Web Services Description Language (WSDL).
Trello is a collaboration tool that organizes your projects into boards. In one glance, Trello tells you what's being worked on, who's working on what, and where something is in a process.
Imagine a white board, filled with lists of sticky notes, with each note as a task for you and your team. Now imagine that each of those sticky notes has photos, attachments from other data sources like BitBucket or Salesforce, documents, and a place to comment and collaborate with your teammates. Now imagine that you can take that whiteboard anywhere you go on your smartphone, and can access it from any computer through the web. That's Trello!
Trello lets you work more collaboratively and get more done. Trello’s boards, lists, and cards enable you to organize and prioritize your projects in a fun, flexible and rewarding way.
Caffe is a deep learning framework made with expression, speed, and modularity in mind
Expression: models and optimizations are defined as plaintext schemas instead of code.
Speed: for research and industry alike speed is crucial for state-of-the-art models and massive data.
Modularity: new tasks and settings require flexibility and extension.
Openness: scientific and applied progress call for common code, reference models, and reproducibility.
Community: academic research, startup prototypes, and industrial applications all share strength by joint discussion and development in a BSD-2 project.
Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices.
Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models.
Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU*. That’s 1 ms/image for inference and 4 ms/image for learning and more recent library versions and hardware are faster still. We believe that Caffe is among the fastest convent implementations available.