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Archiving system incorporates AI and machine learning elements

Thu, Mar 21, 2019

Enhanced functions for radiologists, new collaboration tools and artificial intelligence (AI) integration are provided in the latest Telemis Multimedia Archiving and Communication System (MACS).

Version 4.90 of Telemis’ archiving and transmission platform is future-proofed for machine learning (ML) and adds advanced capabilities for diagnosis and collaboration.

Telemis-Medical Version 4.90 also simplifies the capture, storage, comparison and sharing of key diagnostic data through improved image registration functionalities, says Telemic, with the introduction of goniometry tools and enhanced collaboration options. The software also offers integration modules that will speed the incorporation of new and emerging AI and ML techniques.

The latest version of MACS was been developed with a focus on addressing the challenges facing today’s radiologists. Recognising that image comparison is a significant portion of a radiologist’s work, Telemis has developed registration capabilities that allow alignment and comparison between images whatever the modalities (CT/MR/PT), the table positions and the timespan between the series. There are optional report input tools that combine advanced image viewing, dictation management and voice recognition, to simplify and speed up the collection, recording and analysis of radiology measurements.

Medical images can be now captured by peripherals such as smartphones and tablets and then automatically linked with the patient ID and the user ID via scan barcodes and QR codes. These more flexible and faster features have been designed not only for medical facilities with multiple sites but also for emergency units, dermatologists and surgeons.

Telemis-Medical Version 4.90 includes a new feature, TM-Community, which facilitates exchanges between Telemis customers. It also includes TM-Publisher Web which supports the secure distribution of images to external professionals such as GPs and consultant physicians. The TM-Publisher Web tool includes a new uploader module that allows internal and external contacts to send DICOM or non-DICOM images for second opinions. For data exchange and GDPR compliance, the new audit system allows operators to centralise access control and management.

Telemis-Medical Version 4.90 offers modules that speed the integration of AI tools. The AI-Box is designed to harmonise the exchange processes between multimedia archiving and communications systems and AI algorithms, making it easier to use the best algorithm for a given pathology.

http://www.telemis.com

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Dual-output digital PoL regulator saves space in ICT applications

Thu, Mar 21, 2019

Designed for high current ICT applications, the BMR469 family of digital point of load (PoL) regulators has been introduced by Flex Power Modules. The BMR469 delivers high power density, up to 160A per square inch, to save valuable board space in space constrained designs.

There are two variants with different output currents. The 80A BMR4690000 measures 25.4 x 12.7 x 11.6mm (1.00 x 0.50 x 0.46-inch) and the 50A BMR4696001 has a low profile with a maximum height of 5.8mm (0.23-inch). This model can be used where designers need to find space for a large processor heatsink, or who want to place the PoL regulator on the underside of the PCB. The low height of the BMR4696001 also makes it possible to place it very close to the processor, thus improving transient response, says Flex Power Modules.

Both versions are configurable as either dual outputs or a single, higher-power output. Designers can use one part to cover different requirements, for example to drive different processors or FPGA rails, which helps simplify power system design, adds Flex.

The BMR4690000 variant provides two independent 40A outputs for dual configurations, or one 80A rail in single-output operation mode. The BMR4696001 provides two 25A outputs or one 50A rail in single-output operation mode. Up to four modules can be paralleled for current sharing, delivering a total of up to 320A for the BMR4690000 and 200A for the BMR4696001.

The BMR469 can be configured via pin-strap or PMBus, according to the application. The regulator is also supported by a simulation model in Flex’s Power Designer software, for design and debug. Using Flex Power Designer’s advanced simulation functions, designers can optimise configuration parameters to achieve a stable control loop with fast load transient responses.

The BMR469 is suitable for a range of applications in the ICT market and designs that require high power density and a digital architecture, such as test equipment or simulator manufacturers. The BMR469 is capable of providing sufficient power to drive components such as processors, FPGAs and ASICs.

Efficiency is typically 92.6 per cent at half load (12Vin, 5Vout). The input voltage range is 7.5 to 14V, and output range is 0.6 to 5.0V. The BMR469 meets safety requirements according to IEC/EN/UL 62368-1, and offers a mean time between failures (MTBF) of 18.49 million hours.

The BMR4690000 is available now, and the BMR4696001 will be available in April 2019.

http://www.flex.com

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IoT Innovations Challenge – #KeysightIoTChallenge

Thu, Mar 21, 2019

One Idea Is All It Takes

Keysight Technologies is inviting undergraduate and graduate students worldwide to participate in its IoT Innovation Challenge. To enter, students must design a low-power sensor network strategy in one of two Innovation Tracks.

Students will compete via online written and video submissions to win an all-expenses-paid trip to the Grand Final at the World Maker Faire in New York, September 21-22, 2019. Six teams will advance to the final, where they will demonstrate their prototypes live before a panel of judges.

Prizes
The Grand Champion team will win $50,000 in cash and $50,000 of select Keysight test equipment for their school. Two first-place winners in each Innovation Track will win $25,000 in cash and $25,000 of select Keysight test equipment for their school.

Pick Your Innovation Track

Track 1: Smart Land
Design a sensor network strategy to cover one sq. km. of urban area to monitor and report on one or more of the following: air quality, water quality, data quality and sound quality, for at least one year.

Track 2: Smart Water
Design a sensor network strategy to cover a major waterway area to monitor and report, on one or more of the following: acidity, turbidity, and contaminants, for at least one year.

Calling All Students!
This is your chance to make the world better for billions. Are you ready to step up and innovate? Contest open to graduate and undergraduate students. Any student graduating before the Grand Final event is also eligible to participate.

Registration opens April 2019. Contest rules are forthcoming. Sign up now to be notified when registration goes live. #KeysightIoTChallenge

Signup here

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AI computer holds promise for millions of intelligent systems

Wed, Mar 20, 2019

At this week’s GPU Technology Conference in San Jose, California this week, Nvidia has announced an artificial intelligence (AI) computer that makes it possible to create millions of intelligent systems.

There are two versions of the Nvidia CUDA-X Jetson Nano computer, a $99 development kit for developers and makers, and a production-ready module, priced at $129 for companies to create mass-market edge systems.

The small CUDA-X AI computer delivers 472GFLOPS of compute performance for running modern AI workloads and is power-efficient, consuming as little as 5W.

Jetson Nano supports high-resolution sensors, can process many sensors in parallel and can run multiple modern neural networks on each sensor stream. It also supports many popular AI frameworks, allowing developers to integrate preferred models and frameworks.

The Jetson Nano developer kit is priced to bring the power of modern AI to a low-cost platform, for makers, inventors, developers and students to build AI projects, for example mobile robots and drones, digital assistants and automated appliances.

The kit includes support for full desktop Linux and is compatible with many popular peripherals and accessories. Ready-to-use projects and tutorials are included to help makers get started with AI fast.

The Jetson Nano module can be used in embedded applications, including network video recorders, home robots and intelligent gateways with full analytics capabilities.

The design includes power management, clocking, memory and fully accessible input/outputs. The AI workloads are entirely software defined, allowing companies to update performance and capabilities even after the system has been deployed.

To help customers easily move AI and machine learning (ML) workloads to the edge, Nvidia has worked with Amazon Web Services (AWS) to qualify AWS Internet of Things Greengrass to run optimally with Jetson-powered devices such as Jetson Nano.

Nvidia CUDA-X is made up of over 40 acceleration libraries for graphics processing unit (GPU) -accelerated computing. JetPack SDK is built on CUDA-X and is a complete AI software stack with accelerated libraries for deep learning, computer vision, computer graphics and multimedia processing that supports all of the Nvidia Jetson family, including Jetson AGX Xavier for fully autonomous machines and Jetson TX2 for AI at the edge.

JetPack includes the latest versions of CUDA, cuDNN, TensorRT and a full desktop Linux OS.

A reference platform has also be created to minimise the time spent on initial hardware assembly.

http://www.nvidia.com

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Archiving system incorporates AI and machine learning elements

Dual-output digital PoL regulator saves space in ICT applications

IoT Innovations Challenge – #KeysightIoTChallenge

AI computer holds promise for millions of intelligent systems

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