Artificial Intelligence

AI making Rapid Strides

With its immense benefits becoming obvious, artificial intelligence (AI) is fast taking over various tasks in businesses across sectors. Typically, it is put to use to carry out functions that need accuracy but are repetitive in nature, like data analysis. At the other end of the spectrum, the technology is being honed and taken to a cutting-edge levels – unlocking its potential to perform cognitive functions of the kind the human mind performs such as perception, reasoning, problem solving, and even anticipating forthcoming situations, such as supply chain choking for instance, and be ready with solutions.
Other than the familiar data analysis, AI is currently used commonly in areas like Speech Recognition, Robotic Process Automation, Natural Language Generation, Bio-metrics et al. Likewise, the applications range from converting human speech into a format that a computer can understand and apply, use algorithms to device machine learning platforms (like the ones Amazon, Google, Microsoft etc. use), and Bio-metrics that recognise, measure and analyse human’s physical features and behaviour.

And while the potential of AI is limitless, businesses by and large are just beginning to harness that basic benefits of the technology. Even so, recent studies suggest that software for machine learning and deep learning segments of AI are expected to rake in a staggering $90 billion in revenue by 2025.
Companies are deploying the tech to achieve new levels of efficiency in data analysis to run functions and boost bottom lines. This in turn is driving research in the domain itself at a furious pace. Tech giants are pouring in enormous rerun sources into exploring the depth and scope of next-gen AI solutions. In fact, data scientists at internet giants as well as start-ups are teaming up with business managers to get machines to do number crunching that enables decision-making a low-risk affair so as to optimise revenue in businesses. Indeed, the next decade is likely to see seminal changes in both – extensive use of AI to run organisations as also the unleashing of the staggering breadth and scope of AI itself.
Top 15 AI technologies in currency today:
— Natural Language Generation
— Speech Recognition
— Machine Learning Platforms
— Virtual Agents
— Decision Managements
— Ai Optimized Hardware
— Deep Learning Platforms
— Robotic Process Automation
— Text Analytics and Natural Alnguage Processing (NLP)
— Bio-metrics
— Cyber Defence
— Content Creation
— Emotion Recognition
— Image Recognition
— Marketing Automation

Selenium

Selenium: Versatile Software Testing automation tool

Selenium is one of the most widely used open-source WebUI (User Interface) Automation Testing suite, originally developed in 2004. It has a portable framework which provides a playback tool for authoring functional tests without the need to learn a test scripting language. The testing tool provides a test domain-specific language to write test cases where the developer can use programming languages, including C#, Java, Perl, PHP, Python, Ruby, Scala, Groovy.

It’s a suite, not just one tool

Intrinsically, Selenium it is not a single tool, instead it is a product suite consisting of:

-- Selenium WebDriver

-- Selenium RC (Remote Control)

-- Selenium IDE

--Selenium-Grid

The Selenium IDE is the simplest framework in the suite and is the easiest one to learn. It is a Firefox plugin that testers can install on their PCs. However, because of its simplicity, Selenium IDE should only be used as a prototyping tool. For creating more advanced test cases, testers might have to use either Selenium RC or WebDriver.

Selenium can be used to automate functional tests and can be integrated with automation test tools such as Maven, Jenkins and Docker to achieve continuous testing. It can also be integrated with tools such as TestNG and JUnit for managing test cases and generating reports. Selenium-Grid is a feature that allows you to run test cases in different machines across different platforms. The control of triggering the test cases is on the local machine, and when the test cases are triggered, they are automatically executed by the remote machine.

Salient features

-- Ensures transparency, agility and transparency across the cross-functional teams of SDLC process (developers, quality assurance, operations, clients and the management).

-- Avoids waste of tester’s time in writing test scripts for each platform to be tested as it follows the principle of writing one test script and runs on any platform.

-- Fosters delivery integration efforts by automating the test process.

-- Offers great visibility in cases of end-to-end applications testing.

-- Reduces turnaround time by facilitating testing teams to automatically run multiple test cases parallelly on multi-browser platforms. This reduces the turnaround time by ensuring extreme testing quality.

-- Allows integration with other tools and jars like ExtentReports, Sikuli and Appium that extend its own functionalities too.

Why testers prefer it

Testers prefer Selenium over any other tool due to its ease of use, availability and simplicity. With the introduction of Selenium RC, testers can now circumvent the restrictions imposed by Same Origin policy prohibits JavaScript code from accessing elements from a domain that is different from where it was launched. Besides that, Selenium also encourages testers to write a script in one programming language and run (re-use) the same test scripts on multiple browser platforms.

Selenium’s WebDriver is of late becoming standard for all browsers, which in turn will automatically support it. The interesting aspect of WebDriver is it leverages testers in testing UI modules, offers a large set of options to test, compare results and finally check if they are in accordance to the expected application behaviour.

Nutanix @ Attuneww

Nutanix: Leader in Hyperconvergence space

The concept

Nutanix is an Enterprise Cloud OS based on hyperconvergened technology which serves as a building block for private clouds. Its solutions are based on the industry’s most popular hyperconverged infrastructure (HCI) technology i.e. a completely software-defined stack that integrates compute, virtualisation, storage, networking and security to run any application at any scale. Nutanix essentially offers a solution to data center complexities, scalability and flexibility issues with its hyperconverged technology and equipment.

The benefits

With Nutanix, client businesses obtain a software or operating system that has the ability to reap the functionality of multiple clouds all at the same time, and consequently produce a management system that is scalable, simple and yet workload-oriented. From the users’ point of view, this technology is tuned to scale up a business easily on a shared-nothing architecture with no single point of failure, and no data and meta-data redundancy. It is built to deliver a software-defined enterprise cloud that can run applications at any scale.

Low cost, high yield:

-- Lower costs: 40-60% reduction in overall CapEx and OpEx.

-- Limitless Scalability: Scale infrastructure predictably and linearly, without limits.

-- Fastest time-to-value: Eight-times faster time-to-value in buying, deploying and managing.

-- Smallest footprint: Up to 90% reduction in power, cooling and space, with a 2U form factor.

-- Spares time for IT innovation: Frees up IT resources to focus on important initiatives and innovation.

How it works

All solutions featured by Nutanix are software defined and hyperconverged, meaning they operate on a virtualized and integrated infrastructure of computing, storage, and networking that are available as a full stack. It delivers a web-scale, hyperconverged infrastructure solution purpose-built for virtualization and cloud environments. This solution brings the scale, resilience, and economic benefits of web-scale architecture to companies through the Nutanix Enterprise Cloud Platform, which combines three product families -- Nutanix Acropolis, Nutanix Prism and Nutanix Calm.

The attributes

As an Enterprise Cloud OS, Nutanix is optimized for storage and compute resources. It employs machine learning to plan for and adapt to changing conditions automatically, and is self-healing to tolerate and adjust to component failures.

Features at a glance:

 -- API-based automation and rich analytics.

 -- Simplified one-click upgrade.

-- Native file services for user and application data.

-- Native backup and disaster recovery solutions.

-- Powerful and feature-rich virtualization.

-- Flexible software-defined networking for visualization, automation, and security.

-- Cloud automation and life cycle management.

Azure: Microsoft’s popular Cloud Service Platform

It is no secret that cloud computing, with its vast applications for business continuity, collaboration etc, is rapidly becoming an agent of change in how businesses operate worldwide. Its game-changing nature of securely hosting and saving files online has brought about vastly increased competitiveness in businesses through cost reduction, greater flexibility and optimal resource utilization. Cloud technology has gained immense popularity among mid-size and small business, thanks to its ability to allow access to application software over high-speed internet connection without the need for investing in computer software and hardware. The leading tech giant in the cloud computing industry today are Amazon, Google, Microsoft, IBM and Oracle, among others. Of these, Microsoft has been at the forefront of cloud technology world for quite a few years now.

Cloud service categories

Azure cloud services fall into three main categories: IaaS (Infrastructure as a Service), PaaS (Platform as a Service) and SaaS (Software as a Service). All three options provide secure, reliable access to cloud hosted data built on Microsoft’s stable architecture. Here, IaaS is the most all-encompassing offering which gives you a server in the cloud. It allows the user to be in full control over the virtual machine, while the company is responsible for managing everything from the operating system up to the application that are running. PaaS and SaaS are the other services where applications are built and hosted through third-party vendors that usually charge for a certain amount of service.

Azure gained the edge

The rising popularity of Microsoft Azure is attributed of the comprehensive set of features and capabilities it offers. The company invested lavishly in its Azure infrastructure which provides hybrid computing tasks -- (i.e. running jobs on both the Azure Public Cloud and on the data center of the customer). Hybrid computing is useful to save on investment costs because the cloud is scalable, and a business can use Infrastructure as a Service only for specific tasks while still keeping its data center for more applicable (or less intricate) computing jobs.

Services Azure provides

Microsoft has been expanding its Azure services with time. Among these are Virtual Machines, SQL databases, Application services etc. The products it provides include AI + Machine Learning, Analytics, Blockchain, Compute, Containers, Databases, Developer Tools, DevOps, Identity, Integration, Internet of Things, Management and Governance, Media, Migration, Mobile, among others.

How businesses benefit

Azure comes in handy to companies that need additional computer capacity for existing applications, but don’t want to add more servers to their own data centers. It allows easy migration of workloads to the cloud without having to modify network configurations while still being able to connect the virtual machines to your on-premises corporate networks. Microsoft Azure has a worldwide network of data centers for its cloud platform, spread over 55 regions in 140 different countries. These form the backbone of facilities like building, deploying, and managing services and applications, anywhere.

-- Azure helps businesses be future-ready -- thanks to continuous innovation from Microsoft.

-- Helps companies build infrastructure on their terms, with a commitment to open source and support for all languages and frameworks, build how you want and deploy where you want to.

-- Enables operations of hybrid cloud seamlessly by integrating and managing environments with services designed for hybrid cloud.

-- It is ensures high security from the ground up, backed by a team of experts and proactive compliance trusted by enterprises, governments and startups.

Azure is the future

Intelligent Cloud and Intelligent Edge with Artificial Intelligence running across all systems is the next big thing. Azure platform is ready to provide an agile and secure experience in these.

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ModelListener Hook in Liferay DXP 7.1

Model Listeners are used for listening to the Liferay Model Events.Model Listeners implement the ModelListener interface. They are used to listen for persistence events on models and perform actions based on requirement either before or after creation of event.

Model listeners were designed to perform lightweight actions in response to a create, remove, or update attempt on an entity’s database table or a mapping table.

For example, if one wants to perform a specific action after deleting a user, this can be implemented using a model listener.

Requirements:Liferay 7 Dxp and knowledge of creating liferay hooks

You can create a model listener in a module by doing two simple things:

●     Implement ModelListener

●     Register the service in Liferay’s OSGi runtime

Step 1: Create a model Listener class that extends BaseModelListener to override listener methods from parent class. Here in CustomEntity you can define any entity of liferay as well as custom entity also. Here I have used User as an entity.

Step 2: Register the Model Listener Service

Register the service with Liferay’s OSGi runtime. If using Declarative Services, set service= ModelListener.class and immediate=true in the Component.

Step 3: Now implement listener methods and write your custom logic to perform actions. Here I have used onAfterRemove() and onBeforeRemove().

There are multiple methods of model listener used to perform action on model.

Listening for Persistence Events:

onAfterAddAssociation	onBeforeAddAssociation
onAfterCreate	onBeforeCreate
onAfterUpdate	onBeforeUpdate
onAfterRemove	onBeforeRemove
onAfterRemoveAssociation	onBeforeRemoveAssociation

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Learn Use of Hook in Liferay with examples

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OpenCV: Solving Computer Vision issues in real-time

OpenCV is a library of programming functions designed to solve Computer Vision problems in real-time. It is a cross-platform and free for use, which allows businesses to utilize and modify the code. OpenCV supports the deep learning frameworks like TensorFlow, Torch/PyTorch and Caffe. It is written in C++ and supports Windows, Linux, Android and Mac OS.

Its features

The OpenCV library has more than 2,500 optimized algorithms, which includes a vast set of both classic and state-of-the-art Computer Vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has a large user community and an estimated number of downloads exceeding 18 million. The library is used extensively in companies, research groups and by governmental bodies.

Languages and OS supported

OpenCV supports programming languages C++, Android SDK, Java, Python, Matlab/Octave and C. On the other hand, it can be run on Linux, Windows, Android,  Mac-OS, FreeBSD, NetBSD and OpenBSD operating systems.

The library has more than 2,500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms.

Widely used

The OpenCV library is used by private companies, startups and government organisations. Its deployed uses range from stitching together street-view images, detecting intrusions in surveillance video, helping robots navigate and pick up objects, detection of swimming pool drowning accidents, running interactive art, inspecting labels on products in factories, among others.

OpenCV applications

    • 2D and 3D feature toolkits

    • Egomotion estimation

    • Facial recognition system

    • Gesture recognition

    • Human–computer interaction (HCI)

    • Mobile robotics

    • Motion understanding

    • Object identification

    • Segmentation and recognition

    • Stereopsis stereo vision: depth perception from 2 cameras

    • Structure from motion (SFM)

    • Motion tracking

    • Augmented reality

To support some of the above areas, OpenCV includes a statistical machine learning library that contains Boosting, Decision tree learning, Gradient boosting trees, Expectation-maximization algorithm, k-nearest neighbor algorithm, Naive Bayes classifier, Artificial neural networks, Random forest, Support vector machine (SVM) and Deep neural networks (DNN).

Attune World Wide is a one-stop Technology and IT Infrastructure Solutions provider. We support our clients with the complete Open-source Technology Consultation, Integration, Development, Training and Migration services.

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