This document provides an overview and introduction to reactive robotics and the Internet of Things (IoT). It discusses several key concepts including reactive programming, functional reactive programming, and high-performance reactive Java. It also covers topics like concurrency, parallelism, queues, and the LMAX Disruptor design pattern. Code examples are provided to demonstrate reactive programming concepts using tools like RxJava. The document aims to explain reactive approaches that can help address complexity in robotics and IoT systems.
This document provides a disclaimer and overview of a presentation on reactive Java, robotics, and IoT using technologies like Reactor, RxJava, Angular 2, and Raspberry Pi. It discusses key concepts like reactive programming, reactive streams, functional reactive programming, and achieving high performance. The presentation will include tales about robotics complexity, domain-driven design, imperative vs reactive programming, and code demonstrations.
IPT presentation @ jProfessionals 2016 on Java and JavaScipt Reactive Robotics and IoT including: Domain Driven Design (DDD), high-performance reactive micro-services development using Spring Reactor, state-of-the-art component-based client side MVVM implementation with Angular 2, ngrx (Redux pattern), TypeScript and reactive WebSockets.
The document discusses how NVIDIA has helped advance GPU computing and artificial intelligence over the past 25 years. It summarizes some of NVIDIA's key accomplishments, including developing the first programmable GPU in 1999, powering many of the world's fastest supercomputers and AI systems, and creating technologies like CUDA that have accelerated AI research and applications. The document also outlines how NVIDIA's Volta GPU architecture and platforms like DGX-2 are further advancing AI and high performance computing.
Palestra apresentada por Pedro Mário Cruz e Silva, Solution Architect da NVIDIA, como parte da programação da VIII Semana de Inverno de Geofísica, em 19/07/2017.
This document provides an overview of NVIDIA's accelerated computing capabilities across a wide range of industries and applications. It highlights that NVIDIA GPUs power the majority of the world's top supercomputers and are used for AI, robotics, science, and more. New product announcements include updates to NVIDIA's computing platforms, networking, security, and simulation technologies.
Enabling Artificial Intelligence - Alison B. LowndesWithTheBest
This document discusses NVIDIA's deep learning technologies and platforms. It highlights NVIDIA's GPUs and deep learning software that accelerate major deep learning frameworks and power applications like self-driving cars, medical robotics, and natural language processing. It also introduces NVIDIA's deep learning supercomputer DGX-1 and embedded module Jetson TX1 for edge devices. The document promotes NVIDIA's deep learning events and career opportunities.
This document provides an overview of Alison B Lowndes' work in artificial intelligence and how AI is being applied across various industries. It discusses using sensors and AI for applications in automotive, communications, consumer goods, financial services, education, manufacturing, media, online services, healthcare, oil and gas, retail, transportation, and utilities. It also briefly outlines Alison's role at a frontier development lab focusing on using AI to help "spaceship earth."
This document provides a disclaimer and overview of a presentation on reactive Java, robotics, and IoT using technologies like Reactor, RxJava, Angular 2, and Raspberry Pi. It discusses key concepts like reactive programming, reactive streams, functional reactive programming, and achieving high performance. The presentation will include tales about robotics complexity, domain-driven design, imperative vs reactive programming, and code demonstrations.
IPT presentation @ jProfessionals 2016 on Java and JavaScipt Reactive Robotics and IoT including: Domain Driven Design (DDD), high-performance reactive micro-services development using Spring Reactor, state-of-the-art component-based client side MVVM implementation with Angular 2, ngrx (Redux pattern), TypeScript and reactive WebSockets.
The document discusses how NVIDIA has helped advance GPU computing and artificial intelligence over the past 25 years. It summarizes some of NVIDIA's key accomplishments, including developing the first programmable GPU in 1999, powering many of the world's fastest supercomputers and AI systems, and creating technologies like CUDA that have accelerated AI research and applications. The document also outlines how NVIDIA's Volta GPU architecture and platforms like DGX-2 are further advancing AI and high performance computing.
Palestra apresentada por Pedro Mário Cruz e Silva, Solution Architect da NVIDIA, como parte da programação da VIII Semana de Inverno de Geofísica, em 19/07/2017.
This document provides an overview of NVIDIA's accelerated computing capabilities across a wide range of industries and applications. It highlights that NVIDIA GPUs power the majority of the world's top supercomputers and are used for AI, robotics, science, and more. New product announcements include updates to NVIDIA's computing platforms, networking, security, and simulation technologies.
Enabling Artificial Intelligence - Alison B. LowndesWithTheBest
This document discusses NVIDIA's deep learning technologies and platforms. It highlights NVIDIA's GPUs and deep learning software that accelerate major deep learning frameworks and power applications like self-driving cars, medical robotics, and natural language processing. It also introduces NVIDIA's deep learning supercomputer DGX-1 and embedded module Jetson TX1 for edge devices. The document promotes NVIDIA's deep learning events and career opportunities.
This document provides an overview of Alison B Lowndes' work in artificial intelligence and how AI is being applied across various industries. It discusses using sensors and AI for applications in automotive, communications, consumer goods, financial services, education, manufacturing, media, online services, healthcare, oil and gas, retail, transportation, and utilities. It also briefly outlines Alison's role at a frontier development lab focusing on using AI to help "spaceship earth."
Real-Time Cloud Robotics in Practical Smart City ApplicationsC2RO Cloud Robotics
This document discusses real-time cloud robotics and its applications in smart cities. It introduces the C2RO cloud robotics platform, which uses stream processing to connect low-cost robotic devices virtually and process data. The document addresses the challenge of latency in cloud robotics and proposes a hybrid cloud/edge computing model to distribute processing. It provides examples of using C2RO for object recognition and SLAM. The document also describes a people counting project in collaboration with Philips and MIT using C2RO to process data from smart street lights.
Hire a Machine to Code - Michael Arthur Bucko & Aurélien NicolasWithTheBest
Bucko and Nicolas share their vision and products, as well as their explanation of what Deckard is. They provide insights from the software development team. They believe coding can resolve problems that we face. Specifically, source coding is the solution that they teach you and they have hopes for in fixing human errors.
Michael Arthur Bucko & Aurélien Nicolas
The document discusses the implementation of an on-premise AI platform at MIMOS Berhad, a Malaysian research institute. The platform makes use of existing on-premise services such as a private cloud, distributed storage, and authentication platform. It provides an AI training facility using containers on VMs, with distributed training and GPU/CPU support. A version management system stores AI models and applications in Docker images. Deployment is supported on the private cloud and edge devices using containers. The goal is to enable internal development and hosting of AI projects in a secure, customizable manner.
Implementing AI: Running AI at the Edge: Embedding low-cost intelligence with...KTN
The Implementing AI: Running AI at the Edge, hosted by KTN and eFutures, is the second event of the Implementing AI webinar series.
To make products more intelligent, more responsive and to reduce the data generated, it is advantageous to run AI on the product itself, as opposed to in the cloud.
The focus of this webinar was the opportunities and challenges of moving the AI processing to “the Edge”. The webinar had four presentations from experts covering overviews of the opportunity, implementation techniques and case studies.
Find out more: https://ktn-uk.co.uk/news/just-launched-implementing-ai-webinar-series
NVIDIA Deep Learning Institute 2017 基調講演NVIDIA Japan
このスライドは 2017 年 1 月 17 日 (火)、ベルサール高田馬場で開催された「NVIDIA Deep Learning Institute 2017」の基調講演にて、NVIDIA Chief Scientist and SVP of Research の Bill Dally が講演したものです。
The document discusses several pillars for national AI initiatives, including establishing AI centers of excellence, reskilling the workforce, and investing in key industries to drive growth and solve economic and social challenges. It also outlines different approaches for designing and optimizing AI systems, such as using GANs and GPU-accelerated simulations. Overall, the document promotes the development and application of AI through collaboration between universities, industry, and government.
Three sentences summarizing the document:
The document discusses NVIDIA's work in artificial intelligence and accelerated computing, including their research in areas like speech synthesis, computer vision, healthcare, and virtual worlds. It presents several of NVIDIA's products and initiatives like DGX systems, Omniverse, and Clara that are aimed at advancing national AI programs and industrial and academic research. The document also outlines NVIDIA's vision for developing human-scale neural networks and a digital twin of Earth to help address global challenges around climate change through predictive modeling and simulation.
Adaptive Neighbor Discovery for Mobile and Low Power Wireless Sensor Networks Dimitrios Amaxilatis
Adaptive neighbor discovery is a technique that adapts beaconing rates in wireless sensor networks based on neighborhood changes. It uses a stability metric to determine if nodes can relax beaconing. Stable nodes with consistent neighborhoods reduce beaconing, while unstable nodes increase beaconing to update neighbors. Simulations show it reduces beacons by 90% in stable environments. Real world tests on a testbed show it extends network lifetime by 20% and handles mobility better than fixed neighbor discovery approaches. Further work includes evaluating duty cycling and using it with other network protocols.
The document discusses NVIDIA's efforts to harness virtual reality and AI for scientific applications. It summarizes NVIDIA's development of GPUs, CPUs, and DPUs to rearchitect data centers for AI workloads. It also discusses several AI tools and frameworks developed by NVIDIA, including simulations, digital twins, virtual worlds, AI assistants, and tools for industries like climate science, robotics, and autonomous systems.
This document discusses the use of Robot Operating System 2 (ROS 2) and Data Distribution Service (DDS) for smart manufacturing. ROS 2 is an open-source robotics middleware that has gained popularity for use in mobile robots, industrial robots, and autonomous vehicles. It allows for distributed, decentralized control through the use of DDS as its underlying middleware for data distribution. The document outlines the history and releases of ROS 2, its advantages over a centralized ROS 1 architecture, and examples of its use in industrial applications such as multiple autonomous guided vehicles (AGVs) and 5G factory networks.
This document discusses NVIDIA's work in accelerating AI through its GPUs and AI platforms. It highlights several key projects including Project SOL which showcases real-time ray tracing in Minecraft using RTX GPUs, Omniverse which is a 3D design collaboration platform, and NASA Mars lander visualizations. It also discusses NVIDIA's 25 years of accelerated computing, enabling enterprise AI through frameworks and solutions, and its Selene supercomputer built using DGX A100 systems. The document provides information on the powerful NVIDIA A100 GPU and its CUDA ecosystem. It outlines how NVIDIA is breaking AI performance records and developing tools like Jarvis for conversational AI. In summary, the document show
This document provides an update on PGI compilers and tools for heterogeneous supercomputing. It discusses PGI's support for OpenACC directives to accelerate applications on multicore CPUs and NVIDIA GPUs from a single source. It highlights new compiler features including support for Intel Skylake, AMD EPYC and IBM POWER9 CPUs as well as NVIDIA Volta GPUs. Benchmark results show strong performance of OpenACC applications on these platforms. The document also discusses the growing adoption of OpenACC in HPC applications and resources available to support OpenACC development.
Implementing AI: Running AI at the Edge: Adapting AI to available resource in...KTN
The Implementing AI: Running AI at the Edge, hosted by KTN and eFutures, is the second event of the Implementing AI webinar series.
To make products more intelligent, more responsive and to reduce the data generated, it is advantageous to run AI on the product itself, as opposed to in the cloud.
The focus of this webinar was the opportunities and challenges of moving the AI processing to “the Edge”. The webinar had four presentations from experts covering overviews of the opportunity, implementation techniques and case studies.
Find out more: https://ktn-uk.co.uk/news/just-launched-implementing-ai-webinar-series
Talk on using AI to address some of humanities problemsAlison B. Lowndes
This document discusses Nvidia's work in artificial intelligence and accelerated computing. It highlights Nvidia's DGX A100 system which provides an order of magnitude better performance and power efficiency compared to prior systems. The document also mentions Nvidia's Selene supercomputer which features thousands of A100 GPUs and is capable of simulating complex earth systems and climate models. Finally, it promotes Nvidia's NGC catalog which provides curated AI tools, frameworks, models and workflows to accelerate the development of AI applications.
Accelerating open science and AI with automated, portable, customizable and r...Grigori Fursin
Validating experimental results from articles has finally become a norm at many systems and ML conferences. Nowadays, more than half of accepted papers pass artifact evaluation and share related code and data. Unfortunately, lack of a common experimental framework, common research methodology and common formats places an increasing burden on evaluators to validate a growing number of ad-hoc artifacts. Furthermore, having too many ad-hoc artifacts and Docker snapshots is almost as bad as not having any (!), since they cannot be easily reused, customized and built upon.
While overviewing more than 100 papers during artifact evaluation at PPoPP, CGO, PACT, Supercomputing and other conferences, we noticed that many of them use similar experimental setups, benchmarks, models, data sets, environments and platforms. This motivated us to develop Collective Knowledge (CK), an open workflow framework with a unified Python API to automate common researchers’ tasks such as detecting software and hardware dependencies, installing missing packages, downloading data sets and models, compiling and running programs, performing autotuning and co-design, crowdsourcing time-consuming experiments across computing resources provided by volunteers similar to SETI@home, applying statistical analysis and machine learning, validating results and plotting them on a common scoreboard for open and fair comparison, automatically generating interactive articles, and so on: http://cKnowledge.org.
In this presentation we will introduce CK concepts and present several real world use cases from General Motors and Arm
on collaborative benchmarking, autotuning and co-design of efficient software/hardware stacks for deep learning. We also present results and reusable CK components from the 1st ACM ReQuEST optimization tournament: http://cKnowledge.org/request. Finally, we introduce our latest initiative to create
an open repository of reusable research components and workflows to reboot and accelerate open science, quantum computing and AI!
Implementing AI: Running AI at the Edge: ClickCV – Providing high-performance...KTN
1. Beetlebox provides the ClickCV computer vision library and tools to develop real-time low latency computer vision applications using FPGAs without requiring hardware expertise.
2. FPGAs offer high performance through parallel processing and precise control over latency, throughput, and power consumption compared to CPUs, but traditionally required hardware expertise to program.
3. Xilinx's Vitis tools including the Vitis Vision library, Vitis AI, and unified software development platform allow development of FPGA applications using C/C++ and popular frameworks like OpenCV, reducing the need for hardware expertise.
Intel IT has undergone a cloud journey to develop a hybrid open cloud. Their goals were to deliver applications and data to improve productivity, drive transformation to an automated hybrid cloud infrastructure, and accelerate the industry's transformation to cloud. Currently they have a large private cloud but are moving workloads to their limited public cloud and hybrid cloud model. Their hybrid cloud will provide applications in minutes across locations and clouds with common identity and data sharing.
NVIDIA Is Revolutionizing Computing - June 2017 NVIDIA
Here's our latest story as well as recent major announcements, featuring the epicenter of GPU computing, the era of AI, the world's largest gaming platform, and more.
Robotic surgery is performed using a robotic system called the Da Vinci. The Da Vinci system allows surgeons to perform complex surgery through small incisions using robotic arms. It provides surgeons with improved vision, precision, and control over open and laparoscopic surgery. Robotic surgery offers patients less pain, blood loss, scarring and faster recovery times compared to open surgery. Dr. Meenakshi Sundaram is a robotic surgeon at Apollo Hospitals in Chennai who performs procedures in urology and gynecology using the Da Vinci system.
Robotic Surgery by muthugomathy and meenakshi shetti.Qualcomm
Here is the very animatedly designed Presentation that explains briefly about Robotic Surgery , Uses of Robobic Surgery, Robotic Surgery Advantages and Disadvantages and about its future scope.
Real-Time Cloud Robotics in Practical Smart City ApplicationsC2RO Cloud Robotics
This document discusses real-time cloud robotics and its applications in smart cities. It introduces the C2RO cloud robotics platform, which uses stream processing to connect low-cost robotic devices virtually and process data. The document addresses the challenge of latency in cloud robotics and proposes a hybrid cloud/edge computing model to distribute processing. It provides examples of using C2RO for object recognition and SLAM. The document also describes a people counting project in collaboration with Philips and MIT using C2RO to process data from smart street lights.
Hire a Machine to Code - Michael Arthur Bucko & Aurélien NicolasWithTheBest
Bucko and Nicolas share their vision and products, as well as their explanation of what Deckard is. They provide insights from the software development team. They believe coding can resolve problems that we face. Specifically, source coding is the solution that they teach you and they have hopes for in fixing human errors.
Michael Arthur Bucko & Aurélien Nicolas
The document discusses the implementation of an on-premise AI platform at MIMOS Berhad, a Malaysian research institute. The platform makes use of existing on-premise services such as a private cloud, distributed storage, and authentication platform. It provides an AI training facility using containers on VMs, with distributed training and GPU/CPU support. A version management system stores AI models and applications in Docker images. Deployment is supported on the private cloud and edge devices using containers. The goal is to enable internal development and hosting of AI projects in a secure, customizable manner.
Implementing AI: Running AI at the Edge: Embedding low-cost intelligence with...KTN
The Implementing AI: Running AI at the Edge, hosted by KTN and eFutures, is the second event of the Implementing AI webinar series.
To make products more intelligent, more responsive and to reduce the data generated, it is advantageous to run AI on the product itself, as opposed to in the cloud.
The focus of this webinar was the opportunities and challenges of moving the AI processing to “the Edge”. The webinar had four presentations from experts covering overviews of the opportunity, implementation techniques and case studies.
Find out more: https://ktn-uk.co.uk/news/just-launched-implementing-ai-webinar-series
NVIDIA Deep Learning Institute 2017 基調講演NVIDIA Japan
このスライドは 2017 年 1 月 17 日 (火)、ベルサール高田馬場で開催された「NVIDIA Deep Learning Institute 2017」の基調講演にて、NVIDIA Chief Scientist and SVP of Research の Bill Dally が講演したものです。
The document discusses several pillars for national AI initiatives, including establishing AI centers of excellence, reskilling the workforce, and investing in key industries to drive growth and solve economic and social challenges. It also outlines different approaches for designing and optimizing AI systems, such as using GANs and GPU-accelerated simulations. Overall, the document promotes the development and application of AI through collaboration between universities, industry, and government.
Three sentences summarizing the document:
The document discusses NVIDIA's work in artificial intelligence and accelerated computing, including their research in areas like speech synthesis, computer vision, healthcare, and virtual worlds. It presents several of NVIDIA's products and initiatives like DGX systems, Omniverse, and Clara that are aimed at advancing national AI programs and industrial and academic research. The document also outlines NVIDIA's vision for developing human-scale neural networks and a digital twin of Earth to help address global challenges around climate change through predictive modeling and simulation.
Adaptive Neighbor Discovery for Mobile and Low Power Wireless Sensor Networks Dimitrios Amaxilatis
Adaptive neighbor discovery is a technique that adapts beaconing rates in wireless sensor networks based on neighborhood changes. It uses a stability metric to determine if nodes can relax beaconing. Stable nodes with consistent neighborhoods reduce beaconing, while unstable nodes increase beaconing to update neighbors. Simulations show it reduces beacons by 90% in stable environments. Real world tests on a testbed show it extends network lifetime by 20% and handles mobility better than fixed neighbor discovery approaches. Further work includes evaluating duty cycling and using it with other network protocols.
The document discusses NVIDIA's efforts to harness virtual reality and AI for scientific applications. It summarizes NVIDIA's development of GPUs, CPUs, and DPUs to rearchitect data centers for AI workloads. It also discusses several AI tools and frameworks developed by NVIDIA, including simulations, digital twins, virtual worlds, AI assistants, and tools for industries like climate science, robotics, and autonomous systems.
This document discusses the use of Robot Operating System 2 (ROS 2) and Data Distribution Service (DDS) for smart manufacturing. ROS 2 is an open-source robotics middleware that has gained popularity for use in mobile robots, industrial robots, and autonomous vehicles. It allows for distributed, decentralized control through the use of DDS as its underlying middleware for data distribution. The document outlines the history and releases of ROS 2, its advantages over a centralized ROS 1 architecture, and examples of its use in industrial applications such as multiple autonomous guided vehicles (AGVs) and 5G factory networks.
This document discusses NVIDIA's work in accelerating AI through its GPUs and AI platforms. It highlights several key projects including Project SOL which showcases real-time ray tracing in Minecraft using RTX GPUs, Omniverse which is a 3D design collaboration platform, and NASA Mars lander visualizations. It also discusses NVIDIA's 25 years of accelerated computing, enabling enterprise AI through frameworks and solutions, and its Selene supercomputer built using DGX A100 systems. The document provides information on the powerful NVIDIA A100 GPU and its CUDA ecosystem. It outlines how NVIDIA is breaking AI performance records and developing tools like Jarvis for conversational AI. In summary, the document show
This document provides an update on PGI compilers and tools for heterogeneous supercomputing. It discusses PGI's support for OpenACC directives to accelerate applications on multicore CPUs and NVIDIA GPUs from a single source. It highlights new compiler features including support for Intel Skylake, AMD EPYC and IBM POWER9 CPUs as well as NVIDIA Volta GPUs. Benchmark results show strong performance of OpenACC applications on these platforms. The document also discusses the growing adoption of OpenACC in HPC applications and resources available to support OpenACC development.
Implementing AI: Running AI at the Edge: Adapting AI to available resource in...KTN
The Implementing AI: Running AI at the Edge, hosted by KTN and eFutures, is the second event of the Implementing AI webinar series.
To make products more intelligent, more responsive and to reduce the data generated, it is advantageous to run AI on the product itself, as opposed to in the cloud.
The focus of this webinar was the opportunities and challenges of moving the AI processing to “the Edge”. The webinar had four presentations from experts covering overviews of the opportunity, implementation techniques and case studies.
Find out more: https://ktn-uk.co.uk/news/just-launched-implementing-ai-webinar-series
Talk on using AI to address some of humanities problemsAlison B. Lowndes
This document discusses Nvidia's work in artificial intelligence and accelerated computing. It highlights Nvidia's DGX A100 system which provides an order of magnitude better performance and power efficiency compared to prior systems. The document also mentions Nvidia's Selene supercomputer which features thousands of A100 GPUs and is capable of simulating complex earth systems and climate models. Finally, it promotes Nvidia's NGC catalog which provides curated AI tools, frameworks, models and workflows to accelerate the development of AI applications.
Accelerating open science and AI with automated, portable, customizable and r...Grigori Fursin
Validating experimental results from articles has finally become a norm at many systems and ML conferences. Nowadays, more than half of accepted papers pass artifact evaluation and share related code and data. Unfortunately, lack of a common experimental framework, common research methodology and common formats places an increasing burden on evaluators to validate a growing number of ad-hoc artifacts. Furthermore, having too many ad-hoc artifacts and Docker snapshots is almost as bad as not having any (!), since they cannot be easily reused, customized and built upon.
While overviewing more than 100 papers during artifact evaluation at PPoPP, CGO, PACT, Supercomputing and other conferences, we noticed that many of them use similar experimental setups, benchmarks, models, data sets, environments and platforms. This motivated us to develop Collective Knowledge (CK), an open workflow framework with a unified Python API to automate common researchers’ tasks such as detecting software and hardware dependencies, installing missing packages, downloading data sets and models, compiling and running programs, performing autotuning and co-design, crowdsourcing time-consuming experiments across computing resources provided by volunteers similar to SETI@home, applying statistical analysis and machine learning, validating results and plotting them on a common scoreboard for open and fair comparison, automatically generating interactive articles, and so on: http://cKnowledge.org.
In this presentation we will introduce CK concepts and present several real world use cases from General Motors and Arm
on collaborative benchmarking, autotuning and co-design of efficient software/hardware stacks for deep learning. We also present results and reusable CK components from the 1st ACM ReQuEST optimization tournament: http://cKnowledge.org/request. Finally, we introduce our latest initiative to create
an open repository of reusable research components and workflows to reboot and accelerate open science, quantum computing and AI!
Implementing AI: Running AI at the Edge: ClickCV – Providing high-performance...KTN
1. Beetlebox provides the ClickCV computer vision library and tools to develop real-time low latency computer vision applications using FPGAs without requiring hardware expertise.
2. FPGAs offer high performance through parallel processing and precise control over latency, throughput, and power consumption compared to CPUs, but traditionally required hardware expertise to program.
3. Xilinx's Vitis tools including the Vitis Vision library, Vitis AI, and unified software development platform allow development of FPGA applications using C/C++ and popular frameworks like OpenCV, reducing the need for hardware expertise.
Intel IT has undergone a cloud journey to develop a hybrid open cloud. Their goals were to deliver applications and data to improve productivity, drive transformation to an automated hybrid cloud infrastructure, and accelerate the industry's transformation to cloud. Currently they have a large private cloud but are moving workloads to their limited public cloud and hybrid cloud model. Their hybrid cloud will provide applications in minutes across locations and clouds with common identity and data sharing.
NVIDIA Is Revolutionizing Computing - June 2017 NVIDIA
Here's our latest story as well as recent major announcements, featuring the epicenter of GPU computing, the era of AI, the world's largest gaming platform, and more.
Robotic surgery is performed using a robotic system called the Da Vinci. The Da Vinci system allows surgeons to perform complex surgery through small incisions using robotic arms. It provides surgeons with improved vision, precision, and control over open and laparoscopic surgery. Robotic surgery offers patients less pain, blood loss, scarring and faster recovery times compared to open surgery. Dr. Meenakshi Sundaram is a robotic surgeon at Apollo Hospitals in Chennai who performs procedures in urology and gynecology using the Da Vinci system.
Robotic Surgery by muthugomathy and meenakshi shetti.Qualcomm
Here is the very animatedly designed Presentation that explains briefly about Robotic Surgery , Uses of Robobic Surgery, Robotic Surgery Advantages and Disadvantages and about its future scope.
Robotic surgery uses robotic systems to aid surgeons during surgical procedures. It was developed to overcome limitations of minimally invasive surgery and enhance open surgery capabilities. Some key systems discussed are da Vinci, ZEUS, and AESOP. Robotic surgery provides advantages like enhanced precision, decreased fatigue and pain, and telemedicine capabilities. However, disadvantages include safety risks if errors occur in the robot and high costs. Further research is still needed to evaluate robotic surgery's efficacy, safety, and cost-effectiveness.
Robotics are used in various applications in biomedical science and healthcare. They can assist nurses by transporting supplies between wards. Medical robots help surgeons by enhancing dexterity and precision during surgical procedures. Robots are also used for rehabilitation through robotic prosthetics and orthotics. Future developments include more autonomous robot surgeons with haptic feedback and reliable remote surgical capabilities.
Artificial intelligence (AI) is everywhere, promising self-driving cars, medical breakthroughs, and new ways of working. But how do you separate hype from reality? How can your company apply AI to solve real business problems?
Here’s what AI learnings your business should keep in mind for 2017.
Hackathon: “IPTPI and LeJaRo Meet The Real World”Trayan Iliev
This document discusses a hackathon event called "RoboLearn Hackathon: IPTPI and LeJaRo meet the Real World" hosted in Sofia, Bulgaria on December 4, 2015. It introduces Trayan Iliev, the presenter, and his company IPT that specializes in Java training. The presentation covers how to build robots with Java platforms like Lego Mindstorms, Raspberry Pi, Arduino and others. Code examples are provided for controlling motors and sensors on Lego robots using the LeJOS Java library.
Adding Value To Your Strategic PartnershipsThom. Poole
The document discusses how building trust with customers and partners through ethical behavior can provide a competitive advantage for companies. It emphasizes maintaining privacy, being transparent, encouraging opt-ins for marketing through creative ideas, and treating customers well. Building trust is key as customers are more loyal to brands they trust.
Leadership of Open Innovation by Paul Sloane★ Tony Karrer
Paul Sloane is a well-known author and speaker on open innovation. In this session, Paul will takes through the breadth of what open innovation can be for organizations and the value it can bring. Of course, innovation where other parties are involved means a different leadership approach. Paul takes us through keys to effective leadership when open innovation is part of our innovation strategy.
In this session, you will learn:
What is Open Innovation and why is it important for your business?
Who is using Open Innovation?
What are the main difficulties and impediments to OI and how can we overcome them?
What is crowdsourcing and how can we use it?
This document discusses robotics and its potential future applications. It defines a robot as a machine that can sense its environment and interact with the physical world. The technology of robotics is presented as an important part of mechatronics with applications in nano-techniques, smart machine technology, and control of complex systems like humanoid robots and vehicles. Different types of robots are described including mobile, rolling, walking, remote-control, and virtual robots. Advantages include performing dangerous tasks while disadvantages include potential job losses and high costs. The document concludes that intelligent robots will offer novel applications in areas like space, underwater environments, construction, and embedded systems.
Smart machines -esitys Tampereella 02/2016Immo Salo
The smart machine era will be the most disruptive in the history of IT, according to Gartner. Smart machines, which include robots, self-driving cars, and other cognitive computing systems that can make decisions without human intervention, were listed by Gartner among the top 10 strategic technology trends for several years in a row. The smart machine era will have a more disruptive impact than any previous developments in information technology.
The robotics market is expected to grow significantly by 2025, reaching over $50 billion annually. Within retail, robots are being used across the supply chain from inventory to delivery. Applications range from stocking shelves to product picking to checkout and delivery. Technologies are also being developed to analyze customer behavior in stores in real time using sensors and cameras to better understand traffic patterns. One example is Digeiz, which uses 3D motion sensors to monitor customer paths and identify busy and empty areas of the store. The development of humanoid robots for customer service faces challenges due to the difficulty of replicating human interactions.
We’ve all seen the generative art produced by Google’s Deep Dream project. What would a curriculum generated by an AI look like? Could we use the digital exhaust of learner and institutional data to improve teaching and learning outcomes? What new ethical issues would this raise? Slides for my talk from the BETT 2017 Learn Live: HE stage.
Center of Digital Excellence (CODE) is a company has shaped up to impart training education in schools and colleges in the next generation technologies of 21st Century.
Prototype Summer School: How to make an interactive light displayNeil Winterburn
Prototype, initiated by Neil Winterburn and Laura Pullig for FACT explores digital making as a creative tool to explore art. The summer school was led by Neil Winterburn, Hwa Young Jung, Stef Jayne and FACTLab’s Radamas Anja.
Over three days young people tinkered with Raspberry Pi’s, Arduinos and Mbots, prototyping robots that water plants, greet visitors to FACT, navigate mazes and send messages to Donald Trump.
This document discusses the rise of smart machines and the technologies enabling them, including cloud computing, big data, robotics, and the Internet of Things. It describes how these technologies are powering different categories of smart machines like movers (self-driving cars), doers (industrial robots), and sages (artificial intelligence systems). While smart machines will significantly disrupt many industries and jobs, they will also drive innovation and create new types of work that require skills in technologies like machine learning.
Technology is disrupting nearly every part of our daily lives.
Smartphones have allowed us to stay connected to each other at literally every moment of our lives, whether it's on our daily commutes or on faraway vacations.
The Internet of Things (IoT) is making us more connected than ever with smart home devices that can control our lights and thermostats and order food for us with simple voice commands.
Robo advisors are making investing more accessible and more affordable for everyone.
And the list is growing.
Almost every industry has been disrupted by digital technologies over the past decade. And, in 2017 we expect to see more revolutionary developments impacting our businesses, careers, and lives.
BI Intelligence, Business Insider's premium research service, has put together a list of 30 Big Tech Predictions for 2017 across Mobile, Digital Media, Payments, IoT, E-Commerce, and Fintech. Some of these major predictions include:
Autonomous car road tests
Snapchat and Amazon rattling the digital ad space
VR hardware competing with popular gaming consoles
The grocery industry making the move online
Mobile wallets adding value to users
Insurtech ascending with investments from legacy players and tech giants
Social video taking 2017 by storm
My jPrime 2016 presentation shows example of Domain-Driven Design (DDD), Event Sourcing (ES) and Functional Reactive Programming (FRP) using Reactor and Redux in a showcase of Java robotics - two small robots IPTPI (Raspberry Pi 2 + Ardiuno) and LeJaRo (LeJOS).
Reactive Microservices with Spring 5: WebFlux Trayan Iliev
On November 27 Trayan Iliev from IPT presented “Reactive microservices with Spring 5: WebFlux” @Dev.bg in Betahaus Sofia. IPT – Intellectual Products & Technologies has been organizing Java & JavaScript trainings since 2003.
Spring 5 introduces a new model for end-to-end functional and reactive web service programming with Spring 5 WebFlow, Spring Data & Spring Boot. The main topics include:
– Introduction to reactive programming, Reactive Streams specification, and project Reactor (as WebFlux infrastructure)
– REST services with WebFlux – comparison between annotation-based and functional reactive programming approaches for building.
– Router, handler and filter functions
– Using reactive repositories and reactive database access with Spring Data. Building end-to-end non-blocking reactive web services using Netty-based web runtime
– Reactive WebClients and integration testing. Reactive WebSocket support
– Realtime event streaming to WebClients using JSON Streams, and to JS client using SSE.
Reactive Java Robotics & IoT with Spring ReactorTrayan Iliev
On April 4-th, 2017 in cosmos coworking camp – Sofia, Trayan Iliev will talk about “Reactive Java Robotics and IoT with Spring Reactor” (http://robolearn.org/reactive-java-robotics-iot-spring-reactor/).
The event is organized by DEV.BG and it is part from the user group Internet of Things.
Program:
1. Robotics, IoT & Complexity. Domain-Driven Design (DDD). Reactive programming. Reactive Streams (java.util.concurrent.Flow);
2. High performance non-blocking asynchronous programming on JVM using Reactor project (using Disruptor/RingBuffer);
3. Implementig reactive hot event streams processing with Reactor: Flux & Mono, Processors;
4. End-to-end reactive web applications and services: Reactor IO (REST, WebSocket) + RxJS + Angular 2;
5. IPTPI robot demo – reactive hot event streams processing on Raspberry Pi 2 + Arduino with embedded and mobile interfaces: http://robolearn.org/
For the lecturer: Trayan Iliev
– founder and manager of IPT – Intellectual Products & Technologies (http://iproduct.org/) – company for IT trainings and consultancy, specialized in Java, Fullstack JavaScipt, web and mobile technologies
– 15+ years training and consulting experience
– lecturer on the conferences, organized by BGJUG and BGOUG – 9 presentations
– organizer of hackathons on Java robotics & IoT in Sofia and Plovdiv
– presenter on international developer conferences: jPrime, jPofessionals, Voxxed Days
The document discusses various topics related to reactive and functional programming including NGRX, RxJS, Redux, Reactive Streams specification, and computing derived data using Reselect. It provides code examples for setting up an NGRX application with state management, effects, selectors, and composing the root reducer. It also discusses hot and cold streams, converting cold streams to hot, and the anatomy of RxJS operators.
Microservices with Spring 5 Webflux - jProfessionalsTrayan Iliev
The document discusses reactive microservices using Spring 5 WebFlux. It introduces reactive programming concepts like Reactive Streams and Project Reactor. It explains how Spring 5 supports reactive programming with WebFlux, reactive repositories, and hot event streaming. Code examples for WebFlux routing, handlers, and reactive clients are available on GitHub.
Spring 5 Webflux - Advances in Java 2018Trayan Iliev
The document discusses a presentation on functional reactive services with Spring 5 WebFlux. It introduces functional reactive programming (FRP), Project Reactor, building REST services with Spring 5 WebFlux including routers, handlers, filters, and reactive repositories. It also covers end-to-end non-blocking reactive service-oriented architecture with Netty, reactive WebClients, and real-time event streaming to JavaScript clients using server-sent events (SSE). The presentation code examples are available on GitHub.
Making Machine Learning Easy with H2O and WebFluxTrayan Iliev
Machine learning is becoming a must for many business domains and applications. H2O is a best-of-breed, open source, distributed machine learning library written in Java. The presentation shows how to create and train machine learning models easily using H2O Flow web interface, including Deep Learning Neural Networks (DNNs). The session provides a tutorial how to develop and deploy fullstack-reactive face recognition demo using React + RxJS WebSocket front-end, OpenCV, Caffe CNN for image segmentation, OpenFace CNN for feature extraction, H20 Flow for face recognition interactive model training and export as POJO. The trained POJO model is incorporated in a real-time streaming web service implemented using Spring 5 Web Flux and Spring Boot. All demo is 100% Java!
Stream Processing with CompletableFuture and Flow in Java 9Trayan Iliev
Stream based data / event / message processing becomes preferred way of achieving interoperability and real-time communication in distributed SOA / microservice / database architectures.
Beside lambdas, Java 8 introduced two new APIs explicitly dealing with stream data processing:
- Stream - which is PULL-based and easily parallelizable;
- CompletableFuture / CompletionStage - which allow composition of PUSH-based, non-blocking, asynchronous data processing pipelines.
Java 9 will provide further support for stream-based data-processing by extending the CompletableFuture with additional functionality – support for delays and timeouts, better support for subclassing, and new utility methods.
More, Java 9 provides new java.util.concurrent.Flow API implementing Reactive Streams specification that enables reactive programming and interoperability with libraries like Reactor, RxJava, RabbitMQ, Vert.x, Ratpack, and Akka.
The presentation will discuss the novelties in Java 8 and Java 9 supporting stream data processing, describing the APIs, models and practical details of asynchronous pipeline implementation, error handling, multithreaded execution, asyncronous REST service implementation, interoperability with existing libraries.
There are provided demo examples (code on GitHub) using Completable Future and Flow with:
- JAX-RS 2.1 AsyncResponse, and more importantly unit-testing the async REST service method implementations;
- CDI 2.0 asynchronous observers (fireAsync / @ObservesAsync);
Fog computing is a system level architecture that distributes computing, storage, control and networking functions closer to users along the continuum between IoT devices and the cloud. It aims to address issues like high latency and network congestion that result from processing and analyzing IoT data solely in the cloud. Key characteristics include supporting real-time interactions, mobility, low latency applications and an extremely large number of heterogeneous devices.
The document discusses various technology trends and software development methodologies. It covers topics like agile software development, Node.js, cloud computing, containers, DevOps, Internet of Things, NoSQL databases, and big data. It also discusses programming languages and frameworks that are trending like Go, Swift, Rust, Dart, and Julia. Continuous integration and tools like Docker, Jenkins, Puppet and Vagrant that support DevOps are also mentioned.
Fog computing is a system-level architecture that distributes computing, storage, control and networking functions closer to users along the continuum between IoT devices and the cloud. It aims to address issues like high latency and network congestion that result from processing all IoT data in the cloud. Key characteristics of fog computing include its ability to support location awareness, mobility and real-time interactions through a geographically distributed deployment.
The Cytoscape Cyberinfrastructure extends Cytoscape and its community into web-connected services.The CI is a Service Oriented Architecture that supports network biology oriented computations that can be orchestrated into repeatable workflows.
OpenSource API Server based on Node.js API framework built on supported Node.js platform with Tooling and DevOps. Use cases are Omni-channel API Server, Mobile Backend as a Service (mBaaS) or Next Generation Enterprise Service Bus. Key functionality include built in enterprise connectors, ORM, Offline Sync, Mobile and JS SDKs, Isomorphic JavaScript and Graphical API creation tool.
In questo workshop abbiamo visto le best practices per l'uso di React Native, come l'organizzazione di file e cartelle e la comunicazione con i servizi di back-end, nel contesto di un progetto reale come Planet App per la gestione IoT del quartiere.
Building Robotics Application at Scale using OpenSource from Zero to HeroAlex Barbosa Coqueiro
Today, organizations are using robotics to address a host of business challenges, from the self-driving car to autonomous walkers to assist older adults, exploring various environments from deep oceans to other planets like Mars. In the past, the integration of these robots took a significant amount of time and effort, and it required specialized expertise in this field. Still, this scenario has dramatically changed thanks to adopting a real-time production system with Linux and the Robot Operating System (ROS). ROS is an open-source software framework for robot development, including middleware, drivers, libraries, tools, and commonly used algorithms for robotics. In this session, we walk the audience through the steps from design to deployment robots using ROS2 Foxy (new version of ROS) from zero to hero using live demo using Python 3 (rclpy) with DDS (Data Distribution Service) simulating real-world environments with Gazebo (open-source 3D robotics simulator). In a nutshell, I will cover designing, developing, testing, and deploying intelligent robotics applications at scale, including integration with critical components, and discuss models that allow for optimized large fleet management.
This document discusses cloud computing and Google App Engine. It provides definitions of cloud computing, utility computing, software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS). It also describes Google App Engine, including its development environment, supported and non-supported technologies for Java, and architecture. Key benefits and factors of cloud computing are outlined as well.
FIWARE Wednesday Webinars - How to Develop FIWARE NGSI Interfaces for RobotsFIWARE
How to Develop FIWARE NGSI Interfaces for Robots - 6th May 2020
Corresponding webinar recording: https://youtu.be/m5JWxlMMuqk
This webinar will present different alternatives to develop FIWARE-Ready robots and the main FIWARE components that can facilitate/empower these developments.
Chapter: Robotics
Difficulty: 3
Audience: Technical Domain Specific
Presenter: Francisco Meléndez (Senior Technical Evangelist, FIWARE Foundation)
UBC’s Cloud Innovation Centre (CIC) invites students to our AWS RoboMaker webinar and live lab on Thursday, July 22 from 1:00 to 3:30 pm PST. In this session, special guest Alex Coqueiro, will introduce you to AWS Robomaker, a service that makes it easy to develop, test, and deploy intelligent robotics applications at scale. We walk through the features of integrating key components into robotics, deploying a single solution, and discuss the uniquely designed models that allow for optimized robots use cases to get you to production fast. We will cover use cases, implementation, simulation, and deployment. Demos will be implemented using Python.
The document discusses the design and implementation of an Internet of Things (IoT) testbed framework with an enhanced performance approach. It aims to create an open IoT testbed that is accessible locally and over the internet for developers to create and test IoT applications and for data engineers to perform analytics on generated data. The testbed will host a range of sensors and be able to interface with microcontrollers like Arduino and Raspberry Pi to account for heterogeneous devices. It seeks to address challenges with proprietary systems like vendor lock-in and provide solutions for insufficient control, lack of concurrency, and diminished reusability.
Rapid Web API development with Kotlin and KtorTrayan Iliev
Introduction to Kotlin and Ktor with flow, async and channel examples. Ktor is an async web framework with minimal ceremony that leverages the advantages of Kotlin like coroutines and extensible functional DSLs..
Sensor data is streamed in realtime from Arduino + accelerometeres, gyroscopes & compass 3D, ultrasound distance sensor, etc. using UDP protocol. The data processing is done with reactive Java alterantive implementations: callbacks, CompletableFutures and using Spring 5 Reactor library. The web 3D visualization with Three.js is streamed using Server Sent Events (SSE).
A video for the IoT demo is available @YouTube: https://www.youtube.com/watch?v=AB3AWAfcy9U
All source code of the demo is freely available @GitHub: https://github.com/iproduct/reactive-demos-iot
There are more reactive Java demos in the same repository - callbacks, CompletableFuture, realtime event streaming. Soon I'll add a description how to build the device and upload Arduino sketch, as well as describe CompletableFuture and Reactor demos and 3D web visualization part with Three.js. Please stay tuned :)
Learning Programming Using Robots - Sofia University Conference 2018 Trayan Iliev
Learn information technologies by creating your own robots and IoT projects. Robotics and IoT offer rich opportunities for practical and active learning of core information technologies, programming languages and software architectures. Presentation includes examples of teaching practices and robotics projects, and offers suggestions why and how to use them to achieve better students' motivation, engagement, creativity, and connection between theory and practice.
Active Learning Using Connected Things - 2018 (in Bulgarian)Trayan Iliev
Learn about active learning methods and practices using Robotics, IoT, and "smart things" projects. Includes examples of teaching practices and robotics projects, and offers suggestions why and how to use them to achieve better students' motivation, engagement, creativity, and connection between theory and practice. Several blended learning models are compared - Flipped Classroom, Stations/Labs Rotation, Flex model. Project support for individual learning styles is discussed.
Presentation from BGOUG conference Nov 17, 2017.
Since September 2017, Java 9 is generally available. It offers many enhancements:
• Modularity – provides clear separation between public and private APIs, stronger encapsulation & dependency management.
• JShell – using and customizing Java 9 interactive shell by example
• Process API updates – feature-rich, async OS process management and statistics
• Reactive Streams, CompletableFuture and Stream API updates
• Building asynchronous HTTP/2 and WebSocket pipelines using HTTP/2 Client and CompletableFuture composition
• Collection API updates
• Stack walking, and other language enhancements (Project Coin)
Discussed topics are accompanied by live demos available for further review @ github.com/iproduct.
Presentation discusses the best practices when writing higher order components (HOCs), and presents examples how to write them according to React recommendations.
Topics include: maximizing HOC factories composability, using ES7 decorators, wrapping context DI in HOCs, handling async state changes using RxJS Observanels and separation of concerns between presentation and business logic components. Examples (@GitHub projects - referenced in the presentation) are given using react, redux, react-router-redux, redux-observable, recompose, and reselect.
Presentation is highlighting novelties in SPA development with Angular 2 (+Ionic 2 demo) with real code examples.
We created together simple Ng2 application with Angular CLI.
All the code is available on GitHub (link to demos is at the end of presentation).
Prerequisites:
1. Install NodeJS. It is better to install version 6 or 4x. Read about NPM.
2. Install TypeScript + editor (Visual Studio Code or Sublime 3).
3. Install Angular 2 Command Line Interface (Angular CLI):
npm install -g angular-cli
MVC 1.0 is an action-oriented framework building on experience with previous frameworks such as Struts, Spring MVC, VRaptor etc. It is based on JAX-RS, CDI and BeanValidation JavaEE technologies and provides a standard, view specification neutral way to build web applications. Among supported view template frameworks are: JSP, Facelets, Freemarker, Handlebars, Jade, Mustache, Velocity, Thymeleaf, etc.
NOTE: MVC 1.0 JavaEE 8 API Specification is in early draft stage, and is subject to change based on open community process.
IPT High Performance Reactive Programming with JAVA 8 and JavaScriptTrayan Iliev
Presentation @ jProfessionals BGJUG Conference
Sofia, November 22, 2015 by IPT – IT Education Evolved, High Performance Reactive Programming Workshop - Dec 15-17,2015 http://iproduct.org/en/course-reactive-java-js/
You are welcome to join us!
Low-latency, high-throughput reactive and functional programming in Java using Spring Reactor, RxJava, RxJS, Facebook React, Angular 2, Reactive Streams, Disruptor (ring buffer), Reactor & Proactor design patterns, benchmarking & comparison of concurrency implementations. December 15 - 17, 2015 - Workshop: High Performance Reactive Programming with JAVA 8 and JavaScript - http://iproduct.org/en/course-reactive-java-js/
IPT Workshops on Java Robotics and IoTTrayan Iliev
Learn how to build your own robot & how to program it in Java with IPT workshops & hackathons. Two small robots: LeJaRo - "the leJOS java robot" & IPTPI - Raspberry Pi 2 enabled robot with higher processing capabilities + distance US and optical sensors, line follow sensor array, cameras, encoders and more. Get first hand experience and jump start in JAVA robotics. Find more on http://robolearn.org/. Children of ALL AGES are Welcome :)
The document outlines a presentation given by Trayan Iliev on building robots with Java. It discusses various robotics platforms that can be used like Lego Mindstorms, Raspberry Pi, Arduino, and shows example Java code for controlling motors and sensors on a Lego robot using the LeJOS library. The code sample moves the robot forward until detecting an obstacle based on color sensor readings, then backs up and turns to repeat the process in a loop.
Novelties in Java EE 7: JAX-RS 2.0 + IPT REST HATEOAS Polling Demo @ BGOUG Co...Trayan Iliev
Presentation shows by example (IPT Polling Demo JAXRS20 HATEOAS, https://github.com/iproduct/IPT-Polling-Demo-JAXRS20-HATEOAS/wiki) the novelties in JAX-RS 2.0 and REST HATEOAS:
- Standardized REST Client API;
- Client and server-side asynchronous HTTP request processing;
- Integration of declarative validation using JSR 349: Bean Validation 1.1;
- Improved server-suggested content negotiation;
- Aspect-oriented extensibility of request/response processing using Filters and Interceptors;
- Dynamic extension registration using DynamicFeature interface;
- Hypermedia As The Engine Of Application State (HATEOAS) REST architectural constraint support using state transition links (support for new HTTP Link header as well as JAXB serialization of resource links).
[IPT, http://iproduct.org]
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
2. 2
Trademarks
Oracle®, Java™ and JavaScript™ are trademarks or registered
trademarks of Oracle and/or its affiliates.
LEGO® is a registered trademark of LEGO® Group. Programs are not
affiliated, sponsored or endorsed by LEGO® Education or LEGO®
Group.
Raspberry Pi™ is a trademark of Raspberry Pi Foundation.
Other names may be trademarks of their respective owners.
3. Tales of JAVA Robotics
3
There are several tales to share:
Tale of Robotics, IoT and Complexity
Tale of Common Sense: DDD
Tale of two cities - Imperative and Reactive
Tale of two brave robots: LeJaRo and IPTPI
And some real reactive Java + TypeScript / Angular 2 /
WebSocket code
4. 4
High Performnce Reactive JAVA
Reactive programming. Reactor & Proactor design
patterns. Reactive Streams (java.util.concurrent.Flow)
High performance non-blocking asynchronous apps
on JVM using Reactor project & RxJava
Disruptor (RingBuffer), Flux & Mono, Processors
End-to-end reactive web applications and services:
Reactor IO (REST, WebSocket) + RxJS + Angular 2
Demo - reactive hot event streams processing on
Raspberry Pi 2 (ARM v7) based robot IPTPI.
RxJava (not Zen only :) coans for self assessment
5. Where to Find the Demo Code?
5
IPTPI Reactive Demo is available @ GitHub:
https://github.com/iproduct/jprime-demo
7. … Even More Complex
7
Cross-section of many
disciplines:
mechanical engineering
electrical engineering
computer science
artificial intelligence (AI)
human-computer interaction
sociology & psychology
Picture by Hugo Elias of the Shadow Robot Company -
http://www.shadowrobot.com/media/pictures.shtml, CC BY-SA 3.0
8. Engineering, Science & Art
8
Source: https://commons.wikimedia.org/w/index.php?curid=551256, CC BY-SA 3.0
9. and How Can We Forget
9
Source: https://commons.wikimedia.org/
w/index.php?curid=234900, CC BY-SA 3.0
Source: Korea Institute of Industrial Technology,
http://news.naver.com/main/read.nhn?
mode=LSD&mid=sec&sid1=102&oid=020&aid=0000371339
10. Robots: The Most Intelligent Things
10
CC BY 2.0, Source:
https://www.flickr.com/photos/wilgengebroed/8249565455/
Radar, GPS, lidar for navigation and obstacle
avoidance ( 2007 DARPA Urban Challenge )
11. The Internet of Things has the potential to change the
world, just as the Internet did. Maybe even more so.
Nearly 50 petabytes of data are captured and created
by human beings
People have limited time, attention and accuracy
Capturing data about things in the real world in real time
Track and count everything, reduce waste, loss & cost.
Know when things need replacing, repairing or recalling
— Kevin Ashton, 'That 'Internet of Things' Thing', RFID Journal,
2009
Internet of Things (IoT)
12. There will be nearly 26 billion devices on the Internet of
Things by 2020.
[Gartner]
More than 30 billion devices will be wirelessly
connected to the Internet of Things by 2020
[ABI Research]
It's expected to be a 19 Trillion USD market
[John Chambers, Cisco CEO]
IoT Perspectives
13. "Basket of remotes" problem – we'll have hundreds of
applications to interface with hundreds of devices that
don't share protocols for speaking with one another
[Jean-Louis Gassée, Apple initial team, and BeOS co-founder]
Only IPv6 addresses are not enough – IoT devices
should be also easily and directly accessible for users
and [their] agents
In read/write mode
Preferably using a standard web browser
Even behind firewalls
IoT - Need for Standards
15. Tracking Complexity
15
We need tools to cope with all that complexity inherent in
robotics and IoT domains.
Simple solutions are needed – cope with problems through
divide and concur on different levels of abstraction:
Domain Driven Design (DDD) – back to basics:
domain objects, data and logic.
Described by Eric Evans in his book:
Domain Driven Design: Tackling Complexity in the Heart of
Software, 2004
16. Common Sense: DDD
16
Actually DDD require additional efforts (as most other
divide and concur modeling approaches :)
Ubiquitous language and Bounded Contexts
DDD Application Layers:
Infrastructure, Domain, Application, Presentation
Hexagonal architecture :
OUTSIDE <-> transformer <-> ( application <-> domain )
[A. Cockburn]
17. Common Sense: DDD
17
Main concepts:
Entities, value objects and modules
Aggregates and Aggregate Roots [Haywood]:
value < entity < aggregate < module < BC
Repositories, Factories and Services:
application services <-> domain services
Separating interface from implementation
18. Imperative and Reactive
18
We live in a Connected Universe
... there is hypothesis that all
the things in the Universe are
intimately connected, and you
can not change a bit without
changing all.
Action – Reaction principle is
the essence of how Universe
behaves.
19. Imperative and Reactive
Reactive Programming: using static or dynamic data
flows and propagation of change
Example: a := b + c
Functional Programming: evaluation of mathematical
functions,
➢ Avoids changing-state and mutable data, declarative
programming
➢ Side effects free => much easier to understand and
predict the program behavior.
Example: books.stream().filter(book -> book.getYear() > 2010)
.forEach( System.out::println )
20. Functional Reactive (FRP)
20
According to Connal Elliot's (ground-breaking paper @
Conference on Functional Programming, 1997), FRP is:
(a) Denotative
(b) Temporally continuous
24. Reactive Streams Spec.
24
Reactive Streams – provides standard for
asynchronous stream processing with non-blocking
back pressure.
Minimal set of interfaces, methods and protocols for
asynchronous data streams
April 30, 2015: has been released version 1.0.0 of
Reactive Streams for the JVM (Java API,
Specification, TCK and implementation examples)
Java 9: java.util.concurrent.Flow
25. Reactive Streams Spec.
25
Publisher – provider of potentially unbounded number
of sequenced elements, according to Subscriber(s)
demand.
Publisher.subscribe(Subscriber) => onSubscribe onNext*
(onError | onComplete)?
Subscriber – calls Subscription.request(long) to
receive notifications
Subscription – one-to-one Subscriber ↔ Publisher,
request data and cancel demand (allow cleanup).
Processor = Subscriber + Publisher
26. FRP = Async Data Streams
26
FRP is asynchronous data-flow programming using the
building blocks of functional programming (e.g. map,
reduce, filter) and explicitly modeling time
Used for GUIs, robotics, and music. Example (RxJava):
Observable.from(new String[]{"Reactive",
"Extensions", "Java"})
.take(2).map(s -> s + " : on " + new Date())
.subscribe(s -> System.out.println(s));
Result:
Reactive : on Wed Jun 17 21:54:02 GMT+02:00 2015
Extensions : on Wed Jun 17 21:54:02 GMT+02:00 2015
27. 27
Performance is about 2 things (Martin Thompson –
http://www.infoq.com/articles/low-latency-vp ):
– Throughput – units per second, and
– Latency – response time
Real-time – time constraint from input to response
regardless of system load.
Hard real-time system if this constraint is not honored then
a total system failure can occur.
Soft real-time system – low latency response with little
deviation in response time
100 nano-seconds to 100 milli-seconds. [Peter Lawrey]
What About High Performance?
28. 28
Mechanical Sympathy – hardware (CPU, cache, memory,
IO, Network), operating system, language implementation
platform (e.g. JVM), and application level code are working
in harmony to minimize the time needed for event (request,
message) processing => 10% / 90% principle
Throughput vs. latency – bus vs. car traveling
Throughput ~ System Capacity / Latency
Achieving low latency may mean additional work done
by system => lowered System Capacity and Throughput
Horizontal scalability is valuable for high throughput. For
low latency, you need simplicity – critical path.
Throughput vs. Latency
29. 29
JVMs can be faster than custom C++ code because of the
holistic optimizations that they can apply across an application
[Andy Piper].
Developers can take advantage of hardware guarantees through
a detailed understanding of:
– Java Memory Model & mapping to underlying hardware
– low latency software system hardware (CPU, cache, memory,
IO, Network)
– avoiding lock-contention and garbage collection
– Compre-And-Swap – CAS (java.util.concurrent.atomic)
– lock-free, wait-free techniques – using standard libraries (e.g.
the LMAX Disruptor)
High Performance Java
30. 30
CPU Cache – False Sharing
Core 2 Core NCore 1 ...
Registers
Execution Units
L1 Cache A | | B |
L2 Cache A | | B |
L3 Cache A | | B |
DRAM Memory
A | | B |
Registers
Execution Units
L1 Cache A | | B |
L2 Cache A | | B |
31. 31
Low garbage by reusing existing objects + infrequent GC
when application not busy – can improve app 2 - 5x
JVM generational GC startegy – ideal for objects living very
shortly (garbage collected next minor sweep) or be immortal
Non-blocking, lockless coding or CAS
Critical data structures – direct memory access using
DirectByteBuffers or Unsafe => predictable memory layout
and cache misses avoidance
Busy waiting – giving the CPU to OS kernel slows program
2-5x => avoid context switches
Amortize the effect of expensive IO - blocking
Low Latency: Things to Remember
32. 32
Parallel tasks can increase your throughput by increasing
system capacity – it is GOOD!
But comes together with concurrent access to shared
resources => you have to provide mutual exclusion (MutEx)
by parallel threads when changing the resources' state (read
only access can be shared by multiple threads)
Mutual exclusion can be achieved in several ways:
– synchronized – hardwired in HotSpot JVM, optimized in J^6
– ReentrantLock, ReadWriteLock, StampedLock →
java.util.concurrent.locks.*
– Optimistic Locking → tryLock(), CAS
Parallelism & Concurrency
33. 33
Simple problem: incrementing a long value 500 000 000 times.
9 implementations:
‒ SynchronousCounter – while (counter++ < 500000000){}
‒ SingleThreadSynchronizedCounter – 1T using synchronized
‒ TwoThreadsSynchronizedCounter – 2T using synchronized
‒ SingleThreadCASCounter – 1T using AtomicLong
‒ TwoThreadsCASCounter – 2T using AtomicLong
‒ TwoThreadsCASCounterLongAdder – 1T using LongAdder
‒ SingleThreadVolatileCounter – 1T, memory barrier (volatile)
‒ TwoThreadsVolatileCounter – 2T, memory barrier (volatile)
Comparing Concurrent Impl.
34. 34
Test results (on my laptop - quad core Intel i7@2.2GHz):
− SynchronousCounter – 190ms
− SingleThreadSynchronizedCounter – 15000 ms
− TwoThreadsSynchronizedCounter – 21000 ms
− SingleThreadCASCounter – 4100 ms
− TwoThreadsCASCounter – 12000 ms
− TwoThreadsCASCounterLongAdder – 12800 ms
− SingleThreadVolatileCounter – 4100 ms
− TwoThreadsVolatileCounter – 20000 ms
Comparing Concurrent Impl.
35. 35
For more complete micro-benchmarking of
different Mutex implementations see:
http://blog.takipi.com/java-8-stampedlocks-vs-
readwritelocks-and-synchronized/
http://www.slideshare.net/haimyadid/java-8-
stamped-lock
Comparing Concurrent Impl.
36. 36
Non-blocking (synchronous) implementation is 2 orders of
magnitude better then synchronized
We should try to avoid blocking and especially contended
blocking if want to achieve low latency
If blocking is a must we have to prefer CAS and optimistic
concurrency over blocking (but have in mind it always
depends on concurrent problem at hand and how much
contention do we experience – test early, test often,
microbenchmarks are unreliable and highly platform dependent
– test real application with typical load patterns)
The real question is: HOW is is possible to build concurrency
without blocking?
Mutex Comparison => Conclusions
37. 37
Message Driven – asynchronous message-passing allows
to establish a boundary between components that ensures
loose coupling, isolation, location transparency, and
provides the means to delegate errors as messages
[Reactive Manifesto].
The main idea is to separate concurrent producer and
consumer workers by using message queues.
Message queues can be unbounded or bounded (limited
max number of messages)
Unbounded message queues can present memory
allocation problem in case the producers outrun the
consumers for a long period → OutOfMemoryError
Scalable, Massively Concurrent
38. 38
Queues typically use either linked-lists or arrays for the
underlying storage of elements. Linked lists are not
„mechanically sympathetic” – there is no predictable
caching “stride” (should be less than 2048 bytes in each
direction).
Bounded queues often experience write contention on
head, tail, and size variables. Even if head and tail
separated using CAS, they usually are in the same cache-
line.
Queues produce much garbage.
Typical queues conflate a number of different concerns –
producer and consumer synchronization and data storage
Queues Disadvantages
[http://lmax-exchange.github.com/disruptor/files/Disruptor-1.0.pdf]
39. 39
LMAX Disruptor design pattern separates different
concerns in a “mechanically sympathetic” way:
- Storage of items being exchanged
- Producer coordination – claiming the next sequence
- Consumers coordination – notified new item is available
Single Writer principle is employed when writing data in
the Ring Buffer from single producer thread only (no
contention),
When multiple producers → CAS
Memory pre-allocated – predictable stride, no garbage
LMAX Disruptor (RingBuffer)
[http://lmax-exchange.github.com/disruptor/files/Disruptor-1.0.pdf]
40. 40
LMAX Disruptor (RingBuffer) High Performance
[http://lmax-exchange.github.com/disruptor/files/Disruptor-
1.0.pdf]
Source: LMAX Disruptor github wiki - https://raw.githubusercontent.com/wiki/LMAX-
Exchange/disruptor/images/Models.png
LMAX-Exchange Disruptor License @ GitHub: Apache License Version 2.0, January 2004 -
http://www.apache.org/licenses/
41. 41
LMAX Disruptor (RingBuffer) High Performance
[http://lmax-exchange.github.com/disruptor/files/Disruptor-
1.0.pdf]
Source: LMAX Disruptor @ GitHub - https://github.com/LMAX-
Exchange/disruptor/blob/master/docs/Disruptor.docx
LMAX-Exchange Disruptor License @ GitHub: Apache License Version 2.0, January 2004 -
http://www.apache.org/licenses/
42. Project Reactor
42
Reactor project allows building high-performance (low
latency high throughput) non-blocking asynchronous
applications on JVM.
Reactor is designed to be extraordinarily fast and can
sustain throughput rates on order of 10's of millions of
operations per second.
Reactor has powerful API for declaring data
transformations and functional composition.
Makes use of the concept of Mechanical Sympathy
built on top of Disruptor / RingBuffer.
43. Project Reactor
43
Pre-allocation at startup-time
Message-passing structures are bounded
Using Reactive and Event-Driven Architecture patterns
=> non-blocking end-to-end flows, replies
Implement Reactive Streams Specification – efficient
bounded structures requesting no more than capacity
Applies above features to IPC and provides non-
blocking IO drivers that are flow-control aware
Expose a Functional API – organize their code in a
side-effect free way, which helps you determine you are
thread-safe and fault-tolerant
52. Disruptor (Ring Buffer) used in Reactor
52
Reactor provides 3 major types of Processors:
EmitterProcessor – using 0 threads (on same thread)
TopicProcessor using – N threads concurrently
processing the messages (AND operation)
WorkQueueProcessor – N threads alternatively
processing the messages (XOR operation – messages
are processed exactly by one thread – load ballancing
and work distribution)
59. LeJaRo: Lego®
Java Robot
59
Modular – 3 motors (with encoders) – one driving each
track, and third for robot clamp.
Three sensors: touch sensor (obstacle avoidance), light
color sensor (follow line), IR sensor (remote).
LeJaRo is programmed in Java using LeJOS library.
More information about LeJaRo:
http://robolearn.org/lejaro/
Programming examples available @GitHub:
https://github.com/iproduct/course-social-robotics/tre
e/master/motors_demo
LEGO® is a registered trademark of LEGO® Group. Programs of IPT are not
affiliated, sponsored or endorsed by LEGO® Education or LEGO® Group.
72. Takeaways: Why Go Reactive?
72
Benefits using Reactive Programming + DDD:
DDD helps to manage complexity in IoT and Robotics -
many subsystems = sub-domains
Reactive Streams (Fluxes, Monos) = uni-directional data
flows, CQRS, event sourcing, microservices
Reactive Streams can be non-blocking and highly
efficient, or can utilize blocking if needed
Naturally implement state management patterns like
Redux, allow time travel, replay and data analytics
Clear, declarative data transforms that scale (Map-
Reduce, BigData, PaaS)
73. Takeaways: Why Maybe Not?
73
Cons using Reactive Programming + DDD:
DDD requires additional efforts to clearly separate
different (sub) domains – DSL translators, factories...
Reactive Streams utilize functional composition and
require entirely different mindset then imperative – feels
like learning foreign language
Pure functions and Redux provide much benefits,
but there's always temptation to “do it the old way” :)
Tool support for functional programming in Java is still
not perfect (in Eclipse at least :)
74. Where to Find the Demo Code?
74
IPTPI Reactive Demo is available @ GitHub:
https://github.com/iproduct/jprime-demo
75. 75
Resources: RxMarbles & Rx Coans
RxMarbles:
http://rxmarbles.com/
RxJava Koans – Let's try to solve them at:
https://github.com/mutexkid/rxjava-koans
RxJS Koans – for those who prefer JavaScript :)
https://github.com/Reactive-Extensions/RxJSKoans
76. Tale of Simplicity: DDD
76
http://robolearn.org/ Let's move!
http://iproduct.org/
77. Thank’s for Your Attention!
77
Trayan Iliev
CEO of IPT – Intellectual Products
& Technologies
http://iproduct.org/
http://robolearn.org/
https://github.com/iproduct
https://twitter.com/trayaniliev
https://www.facebook.com/IPT.EACAD
https://plus.google.com/+IproductOrg