Tag Archives: Sponsored

Revolutionize Your Design and Test Workflow

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/want-to-innovate-with-testops-learn-how

Revolutionize Your Design and Test Workflow

Agile software development profoundly transformed software development in the 1900s. Far more than a process; Agile created a new way to work.

Today, a similar transformation is happening in test and measurement. TestOps is an innovative approach to product design and test which improves workflow efficiency and speeds product time to market.

Learn more about TestOps and how to accelerate your product development workflow.


The Best U.S. Markets for Rising Engineers, and Why

Post Syndicated from Digikey original https://spectrum.ieee.org/at-work/tech-careers/the-best-us-markets-for-rising-engineers-and-why

Many U.S. cities are on the rise in terms of engineering opportunities and industries, offering good job markets and exciting metro areas to live in

Sometimes, finding success is about being in the right place. Many U.S. cities are on the rise in terms of engineering opportunities and industries, offering good job markets and exciting metro areas to live in beyond just Silicon Valley and the Bay Area, both of which are popular among engineers.

A recent data collection from WalletHub, a personal finance website, compared 100 large metro areas across 20 key metrics from per-capita STEM openings to wage growth. They also gathered insight from industry experts to determine some of the best U.S. cities for a thriving STEM career.

Seattle, Washington

If you are looking for a west coast experience, Seattle and its surrounding suburbs hope to attract professionals. With information technology behemoths Microsoft and Amazon both based there, engineering jobs are plentiful. Amazon alone has 45,000 employees and approximately 10,000 jobs are currently posted. Boeing is also one of the area’s largest employers for those with an aerospace focus. Seattle is also the home of Starbucks and boasts the most coffee shops per capita.

Boston, Massachusetts       

This historic New England city is filled to the brim with colleges and universities including Harvard, Boston University and Massachusetts Institute of Technology (MIT). There are also world-class medical institutions like Massachusetts General Hospital, Brigham and Women’s Hospital and Shriners Hospitals for Children. Research jobs at places like these are always in demand.

Pittsburgh, Pennsylvania

Once the center of the American steel industry, Pittsburgh is an ever-evolving city. While there are no longer any steel mills within Pittsburgh proper, many outlying towns still produce it. It has been named a top city for job growth by many sources, including Forbes. Big name companies like Google, Apple, Intel, Uber, Facebook and RAND have campuses within the city. These companies often have easy access to the talent coming out of Carnegie Mellon University, the University of Pittsburgh and Penn State, though the latter is a bit more centrally located.

Austin, Texas

Austin has a growing tech scene in addition to a thriving art, cultural and entertainment scene. Companies like Facebook, Amazon and Apple have offices in Austin. There are also unique opportunities in Austin for people to learn new skills that are in high demand.

Programs like WeWork’s Flatiron School offers courses in tech skills like software engineering, data science and UX/UI design, both on campus and online. The Austin campus is increasingly popular for people looking to get into Austin’s largest tech sector: software engineering.

Madison, Wisconsin

People are flocking to Madison, Wisconsin, according to a recent Bloomberg review of mid-to-large U.S. cities. The city’s reasonable cost of living and job availability are two key factors for the influx. Epic Systems Corporation, which makes software used in many hospitals, is the largest private employer there with about 10,000 employees.

Huntsville, Alabama

A recent analysis by 24/7 Wall Street found that this southern city has the third largest number of workers in the STEM field at 16%. The median salary is also about $80,000. Coupled with a low cost of living, that amount can go a lot farther than in some major metro areas. Companies like Boeing and Blue Origin employ thousands in Huntsville with an aerospace focus. Other companies like AT&T, IBM and Lockheed Martin also have large offices there.

Many factors influence where people call home. But sometimes, an unexpected location can mean tremendous opportunities. Often, when jobs come to a city, culture, great restaurants and things to do follow. One of these markets may be your key to success.

EMI step-by-step guide from Rohde & Schwarz- Download For Free

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/emi-stepbystep-guide-from-rohde-schwarz-download-for-free

Be able to discover & analyze EMI in a more systematic & methodical approach to solve your problems.

In our free step-by-step guide, we break down the whole EMI design test process into “Locate”, “Capture”, and “Analyze”. Download & learn more.


Tips and Tricks on How to Verify Control Loop Stability

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/tips-and-tricks-on-how-to-verifying-control-loop-stability

Register for our Application Note “Tips and Tricks on how to verify control loop stability”

The Application Note explains the main measurement concept and will guide the user during the measurements and mention the main topics in a practical manner. Wherever possible, a hint is given where the user should pay attention.


JumpStart Guide to Cloud-Based Firewalls in AWS

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/webinar/jumpstart-guide-to-cloudbased-firewalls-in-aws

In this webinar: SANS, Optiv, and AWS Marketplace will lead an in-depth exploration of the key issues to consider when choosing next-generation firewall/threat prevention solutions for integration into a cloud environment, as well as recommend a process for making that important decision.

In this webinar:

SANS, Optiv, and AWS Marketplace will lead an in-depth exploration of the key issues to consider when choosing next-generation firewall/threat prevention solutions for integration into a cloud environment, as well as recommend a process for making that important decision.

Attendees will learn:

·         How cloud design affects the selection and use of next-generation firewalls and threat protection capabilities

·         Needs and capabilities associated with firewalls and threat prevention capabilities, including intrusion prevention, antivirus, logging and alerting, event correlation, continuous dynamic updating of threat databases, and malware protection

·         Business, technical, and operational considerations for cloud-based firewall protection, including AWS-specific considerations and real-world success observations

 Key questions for potential vendors to determine which products are well-suited for integration and implementation in your AWS environment

Data Center Innovation Starts Here

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/data-center-innovation-starts-here

Ten Things You Need to Know About Data Center Innovation

The demand for data is exploding, and data center operators are bombarded daily with new information about emerging technologies. 

Keysight’s new poster, Ten Things You Need to Know About Data Center Innovation, is the calm in the storm, putting the essential information you need today front and center.

Need to make decisions about 400GE and Gen5 computing standards?

This is where to start.


ANSYS 5G Antenna Solutions

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/ansys-5g-antenna-solutions

Accelerate Antenna Design with ANSYS 5G Simulation Solutions

ANSYS 5G simulation solutions empower you to solve your most complex challenges for the 5G ecosystem from devices to networks to data centers. ANSYS tools simulate antenna-to-antenna coupling and environmental effects on signal propagation to improve capacity and data rates for wireless applications.

Customers report they were able to improve antenna performance 5x and reduce development cycle by 25%.

Learn how ANSYS simulation solutions can help accelerate your 5G antenna design. 


Cosmic Ray Failures of Power Semiconductor Devices

Post Syndicated from ABB Semiconductor original https://spectrum.ieee.org/energy/renewables/cosmic-ray-failures-of-power-semiconductor-devices

Cosmic ray failures are sudden events caused by cosmic particles in devices subjected to a high electric field strength

The increased failure rate of traction propulsion converters in the early 1990s, lead to the recognition of cosmic ray failure mode for power devices. The famous experiment, whereby the failure rate of devices in a blocking condition in a laboratory were compared to the blocking failure rates in a salt-mine, was undertaken by Siemens engineers. The absence of failure in the salt mine supported the hypotheses of cosmic ray particles as the root cause of the failures [1]. Further tests executed by ABB on the Jungfraujoch at 3580 m above sea level (a.s.l), confirmed this hypothesis. Additional tests with proton beams made it reproducible in the laboratory. This leads to improved design and statement in regard to ruggedness of power semiconductor devices.

Cosmic particles
Primary cosmic particles (typically protons) are generated in remote areas of the universe e.g. in the supernovae. The particle energy can be extremely high; several orders of magnitude higher than artificially accelerated particles in the most powerful accelerators such as the one in the CERN research centre. But these are not the particles that directly cause device failure on the earth. During their travel towards the earth, many particles are deflected by the sun and earth’s magnetic field. This is why the cosmic particles detected on earth vary with the 11 years activity cycle of the sun. Those particles that are approaching the earth interact with the atmosphere. In this interaction, a shower of new, secondary, tertiary, … particles (protons, neutrons, electrons, …) are generated. Up to an altitude of 10,000 – 15,000 m the generation of particles is dominant, whereas nearer earth altitudes, absorption of particles dominates. At the surface, the x’th generation of the initial primary cosmic can be detected (terrestrial cosmic). A typical flux is 20 neutrons per cm2 per hour (sea level New York), see Figure 1.From this description, one can conclude that the flux of terrestrial cosmic particles is dependent on altitude. Dependencies on the latitude, due to the influence of the earth’s magnetic field, and the actual sun activity, can be neglected for a first order estimation.

As the atmosphere is absorbing cosmic particles, other materials could be used as a shield. For example, a 45 cm layer of concrete reduces the intensity of cosmic neutron particles by half [3]. But as for a significant shielding effect, heavy shielding would be necessary which is not an option for many applications.

Failure mode

Most cosmic particles pass the semiconductor devices without any interaction. With a certain probability the cosmic particles interact with the nucleus of a silicon atom in the device. Then the energy of the particle displaces the hit atom and may generate new particle species. Although a microscopic defect in the silicon crystal is generated, the concentration of the generated defects, even during the lifetime, would not lead to a measurable degradation for typical irradiation conditions, for a non-operating device. The situation might be different for operated semiconductor devices. Logic devices, or memories, store their information, typically, through a small charged capacitor. Here the deposited energy of a cosmic particle may lead to a bit flip and therefore to a loss of information. In devices that support an electric field, the deposited energy of a cosmic particle may lead to a local charge cloud that is amplified through the electric field. A short current pulse may be detected at the biased device. This effect is used for particle detectors for physical experiments to identify and count high energetic particles. In devices that support a high electric field, like power semiconductor devices, the deposited energy may lead to formation of a streamer, a conducting pipe in the blocking semiconductor device see Figure 2. In such a case the device may be destroyed as shown in Figure 3.

The failure of devices due to cosmic rays are sudden events, without any precursor. Therefore, they are often called ‘Single Event Burnout’ (SEB). The probability of a device failure depends on the intensity of the cosmic irradiation (therefore on the altitude and shielding as previously explained), and strongly on the electric field strength and distribution in the power semiconductor device (therefore on the applied blocking voltage and device design). Other influencing parameters are device temperature and beam direction.


For testing of semiconductor devices for cosmic ray ruggedness, data needs to be acquired in a reasonable testing time. This can be reached by:

  • Testing many devices in parallel to get a higher probability of failure events during the test time.

  • Increasing the sensitivity of the tested devices, by operating them during the test at higher blocking voltages than in typical applications. The failure rate for a typical application then needs to be extrapolated. This method was used in the beginning of the cosmic ray ruggedness investigation .

  • Another way to accelerate testing is to increase the cosmic ray flux. As seen before, the intensity of cosmic particles increases to an altitude of 10,000 – 15,000 m a.s.l. In the beginning of cosmic ray ruggedness investigation of power semiconductor devices, this effect was used to reduce test time. ABB operated a test lab at the High Altitude Research Station, Jungfraujoch in the Swiss Alps at 3580 m, see Figure 4. At this altitude the intensity of cosmic particles is approximately a factor of 10 higher that at sea level.

But even with acceleration, testing times are still in the order of several months to years. This is too long, especially for verification testing during the development phase of semiconductors with several learning cycles.

A much faster way to get the relevant data is to use artificial particle beams, like neutron or proton beams. Studies showed, that the failure rates generated by natural cosmic particles very well correspond to data generated in artificial particle beams, see Figure 5. The test time for such a setup reduces to minutes.

Specification of devices ruggedness

Some power semiconductor suppliers specify the cosmic ray ruggedness of their devices either in the data sheet or in an application note e.g. [5]. The parameters for the failure probability, such as applied bias, junction temperature or altitude, are given for an unshielded device. This helps to estimate the failure rate of the power semiconductor under the individual application conditions and to choose the right device.



H. Kabza, H.-J. Schulze, Y. Gerstenmaier, P. Voss, J. Wilhelmi, W. Schmid, F. Pfirsch und K. Platzöder, „Cosmic Radiation as a Cause for Power Device Failure and Possible Countermeasures,“ in Proc. of the 6th Internat. Symposium on Power Semiconductor Devices & IC’s, Davos. Switzerland, 1994.


O. C. Allkhofer und P. K. F. Grieder, ,,Cosmic Rays on earth,“ Physics Data , Bd. 25, Nr. 1, 1984.


F. J. Ziegler, „Terrestrial cosmic rays,“ IBM J. Res. Develop., Bd. 40, Nr. 1, pp. 19-39, 1996.


C. Findeisen, E. Herr, M. Schenkel, R. Schlegel und H. Zeller, „Extrapolation of cosmic ray induced failures from test to field conditions for IGBT modules,“ Microelectronics Reliability, Bd. 38, pp. 1335 – 1339, 1998.


H. Zeller, „Cosmic ray induced breakdown in high voltage semicoductor devices, microscopic model and phenolenological lifetime prediction,“ in 6th International Symposium on Power Devices & IC’s , Davos, Switzerland, 1994.


5SYA 2046-03, „Failure rates of IGCTs due to comsic rays,“ ABB Application Note, 2014.

Infographic cosmic rays influence on semiconductors

Failure rates of fast recovery diodes due to cosmic rays

Failure rates of IGBT modules due to cosmic rays

Failure rates of IGCTs due to cosmic rays

Solve Your Thin Film Challenges in High-Volume Compound Semi Manufacturing

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/addressing-thin-film-challenges-in-highvolume-compound-semiconductor-manufacturing-a-360degree-solution

In this white paper, you’ll learn how investing in a robust, reliable thin film deposition solution will better position compound semi manufacturers for high-volume production.

Scaling into high-volume production for compound semiconductor manufacturing does not just involve achieving a higher throughput and factory output. Compound semi manufacturers need to invest in a robust, reliable thin film deposition solution that is configured for high throughput and excellent precision. In this white paper, you’ll learn how a flexible configuration with the right hardware, software and partner support will lead to a better production process and performance and a lower cost of ownership.


How to Build an Endpoint Security Strategy in AWS

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/webinar/how-to-build-an-endpoint-security-strategy-in-aws

Cloud endpoint security is increasingly relevant in today’s business world and is critical to successful cloud migrations. In this webinar, SANS and AWS Marketplace will discuss this evolution and what it means for your AWS environment.

Today’s cloud-based endpoint security solutions differ significantly from traditional on-premises solutions. Still considered a basic security requirement, endpoint security is the cornerstone of any successful cloud migration strategy.

In this webcast, SANS analyst Thomas Banasik identifies the top challenges businesses face when migrating to the cloud and walks through the process of protecting cloud assets by using a defense-in-depth architecture to create a readily deployable, fully integrated endpoint security strategy.

Attendees will learn:

  • Evaluate security, migration, scale, speed and complexity requirements
  • Implement key endpoint security capabilities, including integrated machine learning, EDR, UBA and DLP solutions
  • Deploy endpoint security agents and use a single pane of glass platform to increase visibility
  • Employ agentless monitoring for synchronized threat intelligence

Register for this webinar to be among the first to receive the associated whitepaper written by Thomas J. Banasik.

Industrial Enclosure Cooling Applications: Filter Fans

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/industrial-enclosure-cooling-applications-filter-fans

Maximize cooling performance to protect critical systems from damaging heat

Download this white paper to learn about thermal management in industrial enclosures, selecting the right climate control system and more.

The Growing Health and Economic Crisis of Chronic Conditions in the U.S.

Post Syndicated from Mercer original https://spectrum.ieee.org/at-work/education/the-growing-health-and-economic-crisis-of-chronic-conditions-in-the-us

These health conditions are driving up healthcare costs. Here’s how a new IEEE member benefit can help prepare for them

In the next five years, it is estimated that ongoing, chronic illnesses or conditions like heart disease, cancer, stroke, arthritis, and diabetes, among others, will impact nearly half the U.S. population and be responsible for 7 out of every 10 deaths.1 Currently, 60% of Americans are living with one chronic condition; 40% with two or more.2

People with chronic conditions are the primary users of healthcare services: they account for 81% of hospital admissions; 91% of all prescriptions filled; and 76% of all physician visits.1 Chronic conditions contribute to 90% of all healthcare spending3 (99% of Medicare spending1) and are the leading cause of the significant increases in healthcare costs in the U.S.

  • Healthcare premiums for employer-sponsored family coverage have increased 87% since 2000.1

  • Healthcare costs for people with a chronic condition are five times higher ($7,900 annually) than for those without a condition.4

  • Average deductible and coinsurance payments increased 176% and 67%, respectively, over a 10-year period and out-of-pocket spending rose 54%.5

While chronic conditions are driving up the costs and usage of healthcare, they are often preventable.

The U.S. Centers for Disease Control and Prevention estimates1 that eliminating these three risk factors — poor diet, inactivity, and smoking — would prevent:

  • 80% of heart disease and stroke.

  • 80% of type 2 diabetes.

  • 40% of cancer.

Regardless of age, you can act and make lifestyle changes to help prevent a chronic condition from happening to you. Now is also a good time to start preparing financially in case such a condition impacts your family.

Your basic health insurance covers many of the medical and treatment costs associated with a chronic condition. But most policies have deductibles, limitations, and benefit maximums that could become expensive with an ongoing chronic condition. For this reason, insurance carriers are beginning to offer chronic illness insurance policies and riders to help offset out-of-pocket expenses.

Recently, to evolve with the changing health and lifestyle needs of its members, IEEE negotiated to add a chronic illness rider to its IEEE Member Group Term Life Insurance Plan.

Based on member feedback and concerns about the financial impact of long-term chronic illness and the need for all-inclusive coverage, IEEE backed this particular benefit because it offered broad coverage for a variety of chronic conditions, unlike some plans that may limit coverage to one or a few specific illnesses or diseases.

With this rider, insured individuals under age 80 can accelerate some of their term-life insurance benefits if they qualify for chronic illness benefits. These benefits can be used to pay for medical or other expenses they choose.

The chronic illness rider is available to IEEE Members and spouses under age 65 residing in the U.S., (excluding Connecticut, Idaho, Louisiana, Minnesota, Montana, North Carolina, Ohio, South Dakota, Utah, and Washington).

Visit www.ieeeinsurance.com  for more details.*

This information is provided by the IEEE Member Group Member Insurance Program Administrator, Mercer Health & Benefits Administration, LLC, in partnership with IEEE to provide IEEE Members with important insurance, health and lifestyle information.

*Including features, costs, eligibility, renewability, limitations, and exclusions.

The IEEE Member Group Term Life Insurance Plan is available in the U.S. (except territories), Puerto Rico and Canada (except Quebec). This plan is underwritten by New York Life Insurance Company, 51 Madison Ave., New York, NY 10010 on Policy Form GMR

The IEEE Member Group Insurance Program is administered by:

Mercer Health & Benefits Administration LLC, 12421 Meredith Drive, Urbandale, IA 50398

In CA d/b/a Mercer Health & Benefits Insurance Services LLC, AR Insurance License #100102691 CA Insurance License #0G39709, 87572 (5/19) Copyright 2019 Mercer LLC. All rights reserved.


1. The Growing Crisis of Chronic Disease in the United States, Partnership to Fight Chronic Disease

2. About Chronic Diseases, Center for Disease Control

3. Health and Economic Costs of Chronic Diseases, Center for Disease Control

4. “The Rising Cost of Healthcare by Year and Its Causes,” Kimberly Adadeo. The Balance

5. “Increases in cost-sharing payments continue to outpace wage growth,” Gary Claxton, Larry Levitt, Matthew Rae and Bradley Sawyer; Kaiser Family Foundation. Peterson-Kaiser Health System Tracker

5G Terms and Acronyms Defined

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/5g-terms-and-acronyms-defined

Want to sound like a 5G expert?

With so many 5G terms talked about these days, it’s easy to get confused. Even more terms and acronyms are on the way. We’ve got you covered with our up-to-date publication quality list of over 90 terms, ranging from AM Distortion to Xn Interface. This handy resource is sure to make you sound like a 5G expert and is perfect for sharing with your colleagues or students.


Robotic Animal Agility

Post Syndicated from LEMO original https://spectrum.ieee.org/robotics/industrial-robots/robotic-animal-agility

Packed with sensory systems and equipped with revolutionary joints, the ANYmal robot is perfectly at ease on even the roughest terrain. It will soon be ready to inspect industrial sites, sewage systems and agricultural fields with complete autonomy.

An off-shore wind power platform, somewhere in the North Sea, on a freezing cold night, with howling winds and waves crashing against the impressive structure. An imperturbable ANYmal is quietly conducting its inspection.

ANYmal, a medium sized dog-like quadruped robot, walks down the stairs, lifts a “paw” to open doors or to call the elevator and trots along corridors. Darkness is no problem: it knows the place perfectly, having 3D-mapped it. Its laser sensors keep it informed about its precise path, location and potential obstacles. It conducts its inspection across several rooms. Its cameras zoom in on counters, recording the measurements displayed. Its thermal sensors record the temperature of machines and equipment and its ultrasound microphone checks for potential gas leaks. The robot also inspects lever positions as well as the correct positioning of regulatory fire extinguishers. As the electronic buzz of its engines resumes, it carries on working tirelessly.

After a little over two hours of inspection, the robot returns to its docking station for recharging. It will soon head back out to conduct its next solitary patrol. ANYmal played alongside Mulder and Scully in the “X-Files” TV series*, but it is in no way a Hollywood robot. It genuinely exists and surveillance missions are part of its very near future.

img 1

Off-shore oil platforms, the first test fields and probably the first actual application of ANYmal. ©ANYbotics

This quadruped robot was designed by ANYbotics, a spinoff of the Swiss Federal Institute of Technology in Zurich (ETH Zurich). Made of carbon fibre and aluminium, it weighs about thirty kilos. It is fully ruggedised, water- and dust-proof (IP-67). A kevlar belly protects its main body, carrying its powerful brain, batteries, network device, power management system and navigational systems.

ANYmal was designed for all types of terrain, including rubble, sand or snow. It has been field tested on industrial sites and is at ease with new obstacles to overcome (and it can even get up after a fall). Depending on its mission, its batteries last 2 to 4 hours.

On its jointed legs, protected by rubber pads, it can walk (at the speed of human steps), trot, climb, curl upon itself to crawl, carry a load or even jump and dance. It is the need to move on all surfaces that has driven its designers to choose a quadruped. “Biped robots are not easy to stabilise, especially on irregular terrain” explains Dr Péter Fankhauser, co-founder and chief business development officer of ANYbotics. “Wheeled or tracked robots can carry heavy loads, but they are bulky and less agile. Flying drones are highly mobile, but cannot carry load, handle objects or operate in bad weather conditions. We believe that quadrupeds combine the optimal characteristics, both in terms of mobility and versatility.”

What served as a source of inspiration for the team behind the project, the Robotic Systems Lab of the ETH Zurich, is a champion of agility on rugged terrain: the mountain goat. “We are of course still a long way” says Fankhauser. “However, it remains our objective on the longer term.

The first prototype, ALoF, was designed already back in 2009. It was still rather slow, very rigid and clumsy – more of a proof of concept than a robot ready for application. In 2012, StarlETH, fitted with spring joints, could hop, jump and climb. It was with this robot that the team started participating in 2014 in ARGOS, a full-scale challenge, launched by the Total oil group. The idea was to present a robot capable of inspecting an off-shore drilling station autonomously.

Up against dozens of competitors, the ETH Zurich team was the only team to enter the competition with such a quadrupedal robot. They didn’t win, but the multiple field tests were growing evermore convincing. Especially because, during the challenge, the team designed new joints with elastic actuators made in-house. These joints, inspired by tendons and muscles, are compact, sealed and include their own custom control electronics. They can regulate joint torque, position and impedance directly. Thanks to this innovation, the team could enter the same competition with a new version of its robot, ANYmal, fitted with three joints on each leg.

The ARGOS experience confirms the relevance of the selected means of locomotion. “Our robot is lighter, takes up less space on site and it is less noisy” says Fankhauser. “It also overcomes bigger obstacles than larger wheeled or tracked robots!” As ANYmal generated public interest and its transformation into a genuine product seemed more than possible, the startup ANYbotics was launched in 2016. It sold not only its robot, but also its revolutionary joints, called ANYdrive.

Today, ANYmal is not yet ready for sale to companies. However, ANYbotics has a growing number of partnerships with several industries, testing the robot for a few days or several weeks, for all types of tasks. Last October, for example, ANYmal navigated its way through the dark sewage system of the city of Zurich in order to test its capacity to help workers in similar difficult, repetitive and even dangerous tasks.

Why such an early interest among companies? “Because many companies want to integrate robots into their maintenance tasks” answers Fankhauser. “With ANYmal, they can actually evaluate its feasibility and plan their strategy. Eventually, both the architecture and the equipment of buildings could be rethought to be adapted to these maintenance robots”.

img 2

ANYmal requires ruggedised, sealed and extremely reliable interconnection solutions, such as LEMO. ©ANYbotics

Through field demonstrations and testing, ANYbotics can gather masses of information (up to 50,000 measurements are recorded every second during each test!) “It helps us to shape the product.” In due time, the startup will be ready to deliver a commercial product which really caters for companies’ needs.

Inspection and surveillance tasks on industrial sites are not the only applications considered. The startup is also thinking of agricultural inspections – with its onboard sensors, ANYmal is capable of mapping its environment, measuring bio mass and even taking soil samples. In the longer term, it could also be used for search and rescue operations. By the way, the robot can already be switched to “remote control” mode at any time and can be easily tele-operated. It is also capable of live audio and video transmission.

The transition from the prototype to the marketed product stage will involve a number of further developments. These include increasing ANYmal’s agility and speed, extending its capacity to map large-scale environments, improving safety, security, user handling and integrating the system with the customer’s data management software. It will also be necessary to enhance the robot’s reliability “so that it can work for days, weeks, or even months without human supervision.” All required certifications will have to be obtained. The locomotion system, which had triggered the whole business, is only one of a number of considerations of ANYbotics.

img 3

Designed for extreme environments, for ANYmal smoke is not a problem and it can walk in the snow, through rubble or in water. ©ANYbotics

The startup is not all alone. In fact, it has sold ANYmal robots to a dozen major universities who use them to develop their know-how in robotics. The startup has also founded ANYmal Research, a community including members such as Toyota Research Institute, the German Aerospace Center and the computer company Nvidia. Members have full access to ANYmal’s control software, simulations and documentation. Sharing has boosted both software and hardware ideas and developments (built on ROS, the open-source Robot Operating System). In particular, payload variations, providing for expandability and scalability. For instance, one of the universities uses a robotic arm which enables ANYmal to grasp or handle objects and open doors.

Among possible applications, ANYbotics mentions entertainment. It is not only about playing in more films or TV series, but rather about participating in various attractions (trade shows, museums, etc.). “ANYmal is so novel that it attracts a great amount of interest” confirms Fankhauser with a smile. “Whenever we present it somewhere, people gather around.”

Videos of these events show a fascinated and sometimes slightly fearful audience, when ANYmal gets too close to them. Is it fear of the “bad robot”? “This fear exists indeed and we are happy to be able to use ANYmal also to promote public awareness towards robotics and robots.” Reminiscent of a young dog, ANYmal is truly adapted for the purpose.

However, Péter Fankhauser softens the image of humans and sophisticated robots living together. “These coming years, robots will continue to work in the background, like they have for a long time in factories. Then, they will be used in public places in a selective and targeted way, for instance for dangerous missions. We will need to wait another ten years before animal-like robots, such as ANYmal will share our everyday lives!”

At the Consumer Electronics Show (CES) in Las Vegas in January, Continental, the German automotive manufacturing company, used robots to demonstrate a last-mile delivery. It showed ANYmal getting out of an autonomous vehicle with a parcel, climbing onto the front porch, lifting a paw to ring the doorbell, depositing the parcel before getting back into the vehicle. This futuristic image seems very close indeed.

*X-Files, season 11, episode 7, aired in February 2018

Do You Know Your Oscilloscope’s Signal Integrity?

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/do-you-know-your-oscilloscopes-signal-integrity

Ebook: How to Determine Oscilloscope Signal Integrity

High oscilloscope signal integrity is critical but often misunderstood! Whether you are debugging your latest design, verifying compliance against an industry standard, or decoding a serial bus, it is important that your oscilloscope displays a true representation of your signal. Learn how to verify that your instrument has the high signal integrity you need with the “How to Determine Oscilloscope Signal Integrity” eBook.


University of Southampton Uses the USRP and LabVIEW to Change the Way It Teaches Wireless Communications

Post Syndicated from National Instruments original https://spectrum.ieee.org/computing/software/university-of-southampton-uses-the-usrp-and-labview-to-change-the-way-it-teaches-wireless-communications

The University of Southampton has been looking at new and innovative ways to teach the principles of wireless communication at a time when there is significant interest in wireless technologies

Demonstrating the Practical Challenges of Wireless Communications

Most electronics education worldwide teaches wireless communications with a typical focus on  communications theory. At the University of Southampton, educators have taken a different outlook in teaching students the practical aspects of communication technology to better prepare them for their careers in industry. Students focus on the rapid prototyping of a wireless communications system with live radio frequency (RF) signal streaming for a practical approach to communications education. With this approach, students gain a valuable experience in manipulating live signals for a greater understanding of wireless communication and the associated practical challenges.

A Real Communications System to Demonstrate Practical Concepts

The University of Southampton have accomplished this demonstration of the practical concepts of wireless communication as part of their masters course in wireless communications. The focus was on creating a wireless communications system to demonstrate the concept of differential-quadrature phase-shift keying(DQPSK) and how it is used within wireless communications. The students were given a USRP™ (Universal Software Radio Peripheral) and tasked with building a DPSK transceiver in a practical session. Before this they attended a one-hour lecture on the USRP and how to use it to achieve their learning outcomes. Additionally were given a pre-session assignment to do, which familiarised them with LabVIEW and its environment.

Practical Challenges of Wireless Communication

Southampton students were tasked with building one half of a wireless communications system. The setup consisted of an incomplete DQPSK demodulator, which needed to be completed so that a modulated signal sent by a separate USRP device could be decoded. To complete this task, a number of steps covering different concepts are required so that the end result is a fully working communications system.

The students first applied a filter to the received and down-converted signal and compared this to the input of the filter in the transmitter of the system. They then down sampled the data to detect, synchronize, and extract the DPSK symbols from the waveform and compare them to those in the transmitter. Finally, students demodulated and decoded these DPSK symbols to recover the message bits, which are again compared with those in the transmitter.

After these three features were implemented into the demodulator, students rigorously tested their system by comparing their constellation graph and signal eye diagram to those of the transmitter, which is shown below.

The constellation diagram gives a visual overview of how the different phases in the phase-shift keying modulation scheme matched up to symbols and how they are represented within the signal envelope. They are important because they give a visual overview of how much interference or distortion is in a signal or channel and are a quick way of seeing if everything is functioning normally. The eye diagram gives a similar visual reference in that it helps show all of the different types of symbols within a channel superimposed over each other to see the characteristics of the system. From this students could infer characteristics such as if the symbols were too long, short, or noisy or poorly synchronized. If the eye is “open”, as it is in the above diagram, then it infers minimal distortion in the signal. If the signal was distorted, then the eye pattern begins to close, decreasing the spaces in the pattern.

Four Out of Five Students Would Like to Make More Use of USRPs

After the conclusion of the module on communications system, students completed questionnaires about their satisfaction and provided feedback on the practical session.

More than four out of five students, 82 percent, said that in the future they would like to make use of the USRP in the taught aspects of their course. In addition, 75 percent of students said that they would like to make use of the USRP in their MSc research projects—showing its great potential in all aspects of wireless communications education and research.

One student said that “The USRP gives an avenue for exploration. It is a good tool to bridge the gap between practical and theory.” Whilst another said that “The USRP vividly helps me understand the theory that I learned in class.” This shows that Southampton has created a strong benchmark in practical communications education.

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How AI is Starting to Influence Wireless Communications

Post Syndicated from National Instruments original https://spectrum.ieee.org/computing/software/how-ai-is-starting-to-influence-wireless-communications

Machine learning and deep learning technologies are promising an end-to-end optimization of wireless networks while they commoditize PHY and signal-processing designs and help overcome RF complexities

What happens when artificial intelligence (AI) technology arrives on wireless channels? For a start, AI promises to address the design complexity of radio frequency (RF) systems by employing powerful machine learning algorithms and significantly improving RF parameters such as channel bandwidth, antenna sensitivity and spectrum monitoring.

So far, engineering efforts have been made for smartening individual components in wireless networks via technologies like cognitive radio. However, these piecemeal optimizations targeted at applications such as spectrum monitoring have been labor intensive, and they entail efforts to hand-engineer feature extraction and selection that often take months to design and deploy.

On the other hand, AI manifestations like machine learning and deep learning can invoke data analysis to train radio signal types in a few hours. For instance, a trained deep neural network takes a few milliseconds to perform signal detection and classification as compared to traditional methodologies based on the iterative and algorithmic signal search and signal detection and classification.

It is important to note that such gains also significantly reduce power consumption and computational requirements. Moreover, a learned communication system allows wireless designers to prioritize key design parameters such as throughput, latency, range and power consumption.

More importantly, deep learning-based training models facilitate a better awareness of the operational environment and promise to offer end-to-end learning for creating an optimal radio system. Case in point: a training model that can jointly learn an encoder and decoder for a radio transmitter and receiver while encompassing RF components, antennas and data converters.

Additionally, what technologies like deep learning promise in the wireless realm is the commoditization of the physical layer (PHY) and signal processing design. Combining deep learning-based sensing with active radio waveforms creates a new class of use cases that can intelligently operate in a variety of radio environments.

The following section will present a couple of design case studies that demonstrate the potential of AI technologies in wireless communications.

Two design case studies

First, the OmniSIG software development kit (SDK) from DeepSig Inc. is based on deep learning technology and employs real-time signal processing to allow users to train signal detection and classification sensors.

DeepSig claims that its OmniSIG sensor can detect Wi-Fi, Bluetooth, cellular and other radio signals up to 1,000 times faster than existing wireless technologies. Furthermore, it enables users to understand the spectrum environment and thus facilitate contextual analysis and decision making.

ENSCO, a U.S. government and defense supplier, is training the OmniSIG sensor to detect and classify wireless and radar signals. Here, ENSCO is aiming to deploy AI-based capabilities to overcome the performance limitations of conventionally designed RF systems for signal intelligence.

What DeepSig’s OmniPHY software does is allow users to learn the communication system, and subsequently optimize channel conditions, hostile spectrum environments and hardware performance limitations. The applications include anti-jam capabilities, non-line-of-sight communications, multi-user systems in contested spectrums and mitigation of the effects of hardware distortion.

Another design case study showing how AI technologies like deep learning can impact future hardware architectures and designs is the passive Wi-Fi sensing system for monitoring health, activity and well-being in nursing homes (Figure 2). The continuous surveillance system developed at Coventry University employs gesture recognition libraries and machine learning systems for signal classification and creates a detailed analysis of the Wi-Fi signals that reflect off a patient, revealing patterns of body movements and vital signs.

Residential healthcare systems usually employ wearable devices, camera-based vision systems and ambient sensors, but they entail drawbacks such as physical discomfort, privacy concerns and limited detection accuracy. On the other hand, a passive Wi-Fi sensing system, based on activity recognition and through-wall respiration sensing, is contactless, accurate and minimally invasive.

The passive Wi-Fi sensing for nursing homes has its roots in a research project on passive Wi-Fi radar carried out at University College London. The passive Wi-Fi radar prototype —based on software-defined radio (SDR) solutions from National Instruments (NI) — is completely undetectable and can be used in military and counterterrorism applications.

USRP transceiver plus LabVIEW

A passive Wi-Fi sensing system is a receive-only system that measures the dynamic Wi-Fi signal changes caused by moving indoor objectives across multiple path propagation. Here, AI technologies like machine learning allow engineers to use frequency to measure the phase changing rate during the measurement duration as well as Doppler shift to identify movements.

Machine learning algorithms can establish the link between physical activities and the Doppler-time spectral map associated with gestures such as picking things up or sitting down. The phase of the data batches is accurate enough to discern the small body movements caused by respiration.

Coventry University built a prototype of a passive Wi-Fi sensing system using Universal Software Radio Peripheral (USRP) and LabVIEW software to capture, process and interpret the raw RF signal samples. LabVIEW, an intuitive graphical programming tool for both processors and FPGAs, enables engineers to manage complex system configurations and adjust signal processing parameters to meet the exact requirements.

On the other hand, USRP is an SDR-based tunable transceiver that works in tandem with LabVIEW for prototyping wireless communication systems. It has already been used in prototyping wireless applications such as FM radio, direction finding, RF record and playback, passive radar and GPS simulation.

Engineers at Coventry University have used USRP to capture the raw RF samples and deliver them to the LabVIEW application for speedy signal processing. They have also dynamically changed the data arrays and batch size of analysis routines to adapt the system to slow and fast movements.

Engineers were able to interpret some captured signals and directly link the periodic change of batch phase with gestures and respiration rate. Next, they examined if the phase of the data batches was accurate enough to discern the small body movements caused by respiration.

AI: The next wireless frontier

The above design examples show the potential of AI technologies like machine learning and deep learning to revolutionize the RF design, addressing a broad array of RF design areas and creating new wireless use cases.

These are still the early days of implementing AI in wireless networks. But the availability of commercial products such as USRP suggests that the AI revolution has reached the wireless doorstep.

For more information on the role of AI technologies in wireless communications, go to Ettus Research, which provides SDR platforms like USRP and is a National Instruments’ brand since 2010.