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Benefits of a Photorelay 👉 Since photorelays operate by light, there are no mechanical parts. This means less wear and component degradation over time, giving designs higher reliability and longer lifespans. 👉 Furthermore, mechanical relays require a large current to move the armature and drive the output. 👉 Photorelays, on the other hand, are driven by an LED on the input side, meaning the necessary input current for the device will be as low as 3 mA to 5 mA. This is a huge advantage for power savings. 👉 Mechanical relays can suffer from contact bounce (i.e the unwanted closing and opening of the relay contact). Photorelays provide better reliability by removing contact bounce and offering faster switching speeds. 

What are Photorelays? 👉 Photorelays are a subgroup of contactless relays, which, as their name implies, utilizes light as an impulse signal. 👉 A photorelay works by emitting light when current passes through an LED. 👉 The emitted light crosses the isolation boundary to fall on the light sensor of a PDA chip that, in turn, powers and drives the gate of a common source-connected MOSFET pair. 👉 This turns the MOSFET on, allowing AC/DC current flow through the power terminals of the MOSFET. 

👉 A ferrite core is basically an oxide created with iron, manganese and zinc. It is also known as a manganese zinc ferrite. 👉 When a current loaded cable passes through a ferrite core, which carries both noise and data signals, a magnetic field is generated by the current. 👉 Ferrite controls the magnetic field by segregating data current and noise current. The magnetic field of data current flows inside the ferrite, while the magnetic field of noise current flows outside it. And the magnetic loss is converted into heat and dissipated, which suppresses the noise without the need for grounding.

How Ferrite Cores Enhance The Quality Of Power Ferrite cores are used to suppress high-frequency noise and signals on the power supply line. Their effectiveness lies in enhancing power quality. First created in 1930 by Dr Y. Kato and Dr T. Takei, the ferrite core has become one of the most important materials in the electronics industry. The use of the material has increased rapidly, owing to its favourable properties such as low loss of energy and low cost.

REGISTRATION END DATE 17th Oct 2020 NATIONAL QUALIFIER TEST DATE 24th/25th/26th Oct 2020 https://www.tcs.com/careers/TCSCampusHiringYoP2021

Cartoon illustration of the possible starting points for your data science journey. (Drawn by Chanin Nantasenamat)

👉 Silicon photonics technology is widely used to miniaturise optical components and densely pack them on the small surface of a silicon chip. 👉 Researchers capitalised on the advantages of miniaturised photonic circuits and built the world's smallest ultrasound detector called the silicon waveguide-etalon detector or SWED. 👉 SWED monitors changes in light intensity propagating through the miniaturised photonic circuits.

World's Smallest Ultrasound Detector, 100 Times Tinier Than Human Hair, Developed by Scientists A team of European researchers has developed the world's smallest ultrasound detector that is based on miniaturised photonic circuits on top of a silicon chip. With a size 100 times smaller than an average human hair, the new detector can visualise features that are much smaller than previously possible, leading to what is known as super-resolution imaging, said the team from Helmholtz Zentrum Munchen and the Technical University of Munich (TUM) in Germany.

The Pangolin Scales Project is a mind-reading dress that can visualize what you're thinking.

👉 With the technology in place, drivers can step out of their vehicles in a designated area and then simply use an app to start the automated parking process. 👉 They can also use the app to summon their vehicles back to the designated area when it’s time to leave. 👉 While the system needs infrastructure to work, that doesn’t mean it can only be used for future parking spaces: Bosch’s sensors can be retroactively installed in old buildings and structures. 👉 “Automated parking solutions bring value to garage owners by allowing for the more efficient use of spaces inside a parking garage,” Ford’s announcement reads. 👉 “With automated valet parking, the same amount of space can accommodate up to 20 percent more vehicles.”

Autonomous Valet System Ford and Bosch show off how cars can park themselves in Detroit

👉 “We have seen tremendous transformation in sound technology. From bulky sound boxes kept in the corners of a room, we have moved to headphones that give hands-free high quality sound experience with very less power. We are going to do the same for display and personal computing,” says Rohildev Nattukallingal, founder and CEO, Nimo Planet. 👉 Nimo has competitors such as Google Glass, Magic Leap, Microsoft HoloLens and the Indian Jio Glass. Nattukallingal said his device is lighter, has bigger display and is more economical than its competitors. 👉 It is a new experience that gives freedom to work from anywhere at any time with the ultimate comfort of working effectively with multi-screens, he added. 👉 The Nimo team has been working for the last seven years in the human machine interface and wearable technology area. Its first product was a smart ring called Neyya (formerly called Fin), which is a gesture based wireless device.

👉 A wearable computing device with multi-screen capabilities, manufactured by a Kochi-based startup, is planning to take on tech giants such as Google, Microsoft and Apple. 👉 Nimo Planet is betting big on the Qualcomm-based Smart Glass that enables a 60-inch display in 3-meter distance. 👉 With a motion of the head, the device can enable the user to experience up to six screens. It will be HD-equivalent display using waveguide display technology.

Nimo Planet: Get productive with this India-made wearable The smart glass has 64GB ROM, Wi-Fi, Bluetooth and 6DOF head tracking. It runs on Planet OS, a unique and simple operating system developed by the team using Android Open Source Projects, which is highly optimised for low power architecture and simple to use.

👉 USB-C supports the USB Power Delivery (USB PD) specification. A USB 2.0 port can deliver just 2.5 watts of power, about enough to charge a phone. 👉 USB 3.1 ups this figure to about 15 watts. But USB PD can deliver up to 100 watts of power, more than six times what USB 3.1 can. This opens up the potential for laptop-powered projectors based on USB-C.

What is USB-C? 👉 USB Type-C, usually referred to as just USB-C, is a relatively new type of connector for delivering data and power to and from computing devices. 👉 Because the USB-C plug is symmetrical, it can be inserted either way, eliminating the frustrations of earlier USB ports and putting it on a par with Apple’s reversible Lightning plug. This alone makes it a hit for me, but USB-C is also closely linked to several powerful new technologies, including USB 3.1, Thunderbolt 3, and USB Power Delivery. 👉 Most USB-C ports are built on the USB 3.1 data-transfer standard. The second-generation protocol of USB 3.1 can theoretically deliver data speeds of up to 10Gbps — twice as fast as USB 3.0 and first-gen USB 3.1, which both top out at 5Gbps. 

Machine Learning 👉 Machine learning is a form of artificial intelligence where machines are given data and then allowed to make sense of it. Over time the algorithms improve through experience similar to human development. Machine learning algorithms simulate the brain and copy the process that we as humans use to learn and be intelligent. In our brains, we have trillions of neurons that are connected. The learning process is a series of trial and error, but once the task is done successfully, connections are made between neurons in the brain to affect future performance. 👉 The development of artificial neural networks (ANN) was key to helping computers think and understand similarly to how humans do. Essentially, ANNs operate from a system of probability—based on the data that is fed into it, it can make decisions and predictions with a certain degree of certainty. A feedback loop helps the system understand if the actions it took were right or wrong. Based on that, the system can modify its approach in the future. Put simply; the machine learns. 👉 Computer engineers began to code machines to think like humans rather than teaching machines how to do everything. Machines learn from all the data that is available to them just as our human brains do.

Artificial Intelligence 👉 As the umbrella term, artificial intelligence describes the concept of machines being able to be intelligent and complete “smart” tasks, those that were originally thought to require human intelligence. 👉 With traditional AI tools, the precise rules of operation are coded by engineers to tell the computers exactly what data to analyse and what output is expected. Artificial intelligence systems work really well for rule-based tasks—things that require explicit knowledge and those where we can write down instructions from beginning to end. 👉 For tacit knowledge—knowledge we gain through experience—such as in natural language processing, traditional AI didn’t perform successfully because it was too cumbersome or impossible to write rules for every scenario in these situations. 👉 Once engineers started to imagine the efficiencies of coding machines to think on their own, machine learning was born.