Збирач потоків

CUDA Version 13 features new CPU resources, unified Arm platforms, and additional operating systems supported.

Engineers across many disciplines are aware of and concerned with lightning—and for good reasons. A lightning strike can cause significant structural damage, house and forest fires, and severe electrical surges (Figure 1).

Figure 1 The intensity of a lightning strike is always awe-inspiring and represents a millisecond-level transient of hundreds of kiloamps. Source: Science Daily

Even if the strike is not directly on the equipment (in which case the unit is probably “fried”), the associated transients induced in nearby wires and paths can be damaging. Lightning can also be mystifying: some people who have been hit have no ill effects; others have some temporary or long-lasting physical and mental impairments; and for some….well, you know how it ends.

Measuring lightning

For these reasons, protection against the effects of lightning to the extent possible is an important factor in many designs. These efforts can include the use of lightning rods, which provide low-impedance paths to Earth ground functioning as a near-infinite source and sink for electrons, gas-discharge tubes (GDTs), and metal oxide varistors (MOVs), among other devices. Implementing protection is especially challenging when there are multiple strikes, as they can erode the capabilities of the protective devices.

This natural phenomenon occurs most frequently during thunderstorms, but has also been observed during volcanic eruptions, extremely intense forest fires, and surface nuclear detonations. There are many available numbers for the voltages, currents, timing, and temperature ranges associated with lightning. While there is obviously no single lightning waveform, Figure 2 shows representative data; note the maximum current of several hundred kiloamps.

Figure 2 These are representative values for lighting-stroke current versus time and current magnitudes; these are not the only ones, of course. Source: Kingsmill Industries Ltd

Researchers have studied lightning for many decades, using a variety of techniques ranging from “man-made” lightning in controlled enclosures, to field measurements in lightning-prone areas, to instigating it with a grounded wire launched into a lightning-prone cloud. There’s also the futile quest to direct and capture lightning’s energy into some sort of project store-and-use scheme. (For fictional demonstration, see the 1931 classic Frankenstein, where lightning is used to energize the doctor’s monster-like creation, or the end of the 1985 classic Back to the Future, where lightning is captured by a rod on the clock tower and used to recharge the flux capacitor of the DeLorean time-travel vehicle .

The standard explanations for lightning and its initiation are like this one from Wikipedia: “Lightning is a powerful natural electrical discharge caused by a buildup of static electricity within storm clouds. This buildup occurs when ice crystals and water droplets collide in the turbulent environment of a cumulonimbus cloud, separating charges within the cloud. When the electrical potential becomes too great, it discharges, creating a bright flash of light and a loud sound known as thunder.”

But what really happens inside the cloud?

Well, maybe that’s only a partial answer, or perhaps it’s misleading. Why so? For decades, scientists have understood the mechanics of a lightning strike, but exactly what sets it off inside thunderclouds remained a lingering mystery. Apparently, it’s much more than static electricity potential finally reaching a “flashover” level.

That mystery may now be solved, as a team at Pennsylvania State University (Penn State) has produced what they say is the complete story. It’s far more complicated than just a huge static-electricity burst; it’s really a mixture of cosmic rays, X-rays, and high-energy electrons.

Their work involves some deep physics and complex analysis. It also introduced me to some new acronyms: initial breakdown pulses (IBPs), narrow bipolar events (NBEs), energetic in cloud pulses (EIPs), and terrestrial gamma ray flashes (TGFs), flickering gamma ray flashes (FGFs), and Initial Electric Field Change (IEC).

They have taken both historical lighting-related data (and there is a lot of that available from multiple sources) with current measurements, presented a hypothesis, correlated the data, developed models, and ran simulations, and put it all together. The result is a plausible explanation that seems to fit the facts, although with natural events such as lightning, you can never be completely sure.

The Penn State research team, led by professor of electrical engineering Victor Pasko, explained how intense electric fields within thunderclouds accelerate electrons. These fast-moving electrons collide with molecules such as nitrogen and oxygen, generating X-rays and sparking a rapid surge of new electrons and high-energy photons. This chain reaction then creates the necessary conditions for a lightning bolt to form, showing the link between X-rays, electric fields, and the physics of electron avalanches.

These electrons radiate energetic photons (X-rays) as they scatter by the nuclei of nitrogen and oxygen atoms in air. These X-rays radiate in all directions, and some fractions are radiated in the opposite direction of electron motion. These particular X-rays lead to the seeding of new relativistic seed electrons due to the photoelectric effect and thus a strong amplification of the original avalanche.

To validate their explanation, the team used mathematical modeling to simulate atmospheric events that match what scientists have observed in the field. These observations involve photoelectric processes in Earth’s atmosphere, where high-energy electrons—triggered by cosmic rays from space—multiply within the electric fields of thunderstorms and release short bursts of high-energy photons. This process, known as a terrestrial gamma-ray flash, consists of invisible but naturally occurring bursts of X-rays and associated very high frequency (VHF) radiation pulses, Figure 3.

Figure 3 A conceptual representation of conditions required for transition from fast positive breakdown (FPB) to fast negative breakdown (FNB) based on relationship between the relativistic feedback threshold E0/δ and the minimum negative streamer propagation fields E—cr/δ. Source: Pennsylvania State University

They demonstrated how electrons, accelerated by strong electric fields in thunderclouds, produce X-rays as they collide with air molecules like nitrogen and oxygen, and create an avalanche of electrons that produce high-energy photons that initiate lightning. They used the model to match field observations—collected by other research groups using ground-based sensors, satellites, and high-altitude spy planes—to the conditions in the simulated thunderclouds.

I’ll admit: it’s pretty intense stuff, as demonstrated by a read-through of their paper “Photoelectric Effect in Air Explains Lightning Initiation and Terrestrial Gamma Ray Flashes” published in the Journal of Geophysical Research. (I do have one minor objection: I wish they did not use the term “photoelectric effect” in the title or body of the paper. Although that phrase is technically correct as they use it, I associate it with Einstein’s groundbreaking 1905 paper, which resolved all the contradictions of the data of this phenomenon and instead proposed photons as energy quanta, for which he received the Nobel Prize.)

While the root causes of lightning, as delineated in the work of the Penn State team, are not directly relevant to engineers whose designs must tolerate nearby lightning strikes, it’s still interesting to see what is going on and how even our modern science may still not have all the answers to such a common occurrence. In other words, there’s still a lot to learn about basic natural events.

Have you ever been involved with a design that had to be lightning-tolerant? What standards did you try to follow? What techniques and components did you use? How did you test it to verify the performance?

Related content

• Lightning as an energy harvesting source?
• When Lightning Strikes, Will a Surge Protector Help?
• Pulse power and transient loads: a very different world

References

• Kingsmill Industries Ltd, Characteristics of Lightning Discharges
• Wikipedia, Lightning

The post What initiates lightning? There’s a new and likely better answer. appeared first on EDN.

📢 День Першокурсника 2025 kpi чт, 08/21/2025 - 15:05

India has fast emerged as a global AI and deep learning innovation hub.India is become a hub for some of the most discerning deep learning applications in retail, healthcare, banking, and autonomous systems due to the rising demand.Many small, medium, and large enterprises are integrating artificial intelligence technologies to gain competitive advantage both in the domestic and overseas markets.This article will explore the top 10 deep learning companies in India.

1. Tata Consultancy Services (TCS)

With its Ignio platform, TCS is leading the way in enterprise-grade deep learning solutions. Neural networks are used for predictive analytics, intelligent automation, and anomaly detection. To improve operations and decision-making, it is extensively used in banking, retail, and healthcare.

2. Infosys

Infosys Nia is an AI platform, powered by deep learning, developed by Infosys, that enables usage scenarios such as automation, business intelligence, and predictive modeling. It is used in industries to help streamline processes, predict trends, and improve customer service.

3. Wipro AI

Wipro concentrates on deep learning techniques in NLP and computer vision. Their solutions target cybersecurity, cloud AI, and digital transformation; they allow the clients to detect threats and automatically analyze visual data.

4. Arya.ai

Arya.ai builds deep learning platforms such as BUDDHA to assist enterprises in deploying AI models with little human intervention. It specializes in automated architecture search, model explainability, and compliance-ready systems, particularly for regulated sectors like finance and insurance.

5. HCL Tech

HCL Tech has its own applications for deep learning in predictive maintenance, healthcare diagnosis, and IT infrastructure management. Models are built not only to detect failures of systems before they actually do, but also assist in medical image analysis for speedy diagnoses.

6. Tech Mahindra

Tech Mahindra applies deep learning into telecom, 5G and IoT ecosystems. Through these AI-powered platforms, the customer experience is enhanced by real-time personalization, and network performance is optimized via smart data modeling.

7. Mad Street Den

Mad Street Den, through its platform Vue.ai, focuses on computer vision applications in retail automation. Their deep learning-based models enable visual search, automated tagging, and personalized styling, consequently revolutionizing e-commerce experience.

8. Fractal Analytics

Fractal Analytics works in applying deep learning to provide AI solutions in customer analytics, forecasting, computer vision, and NLP (natural language processing) in the sectors of healthcare and finance. Furthermore, it imparts AI training through its own institute, the Fractal Analytics Academy, and pursues the implementation of fractal machine learning for enhancing model efficiency and scalability.

9. Haptik’s

Haptik’s deep learning abilities cover real-time analytics, customer self-service, and pre-sales guidance, giving enterprises a complete conversational experience.

10. Zensar Technologies

Zensar Technologies furthers deep learning in AI and ML activities. The company uses deep learning techniques as part of the Vinci AIOps platform, an operational platform that improves IT operations through event correlation, anomaly detection, root cause analysis, and intelligent automation. This system thereby uses deep learning and NLP to learn and respond intelligently to IT systems.

Conclusion:

India’s deep learning ecosystem is rising at lightning pace. Indian companies, from the likes of established IT giants TCS and Infosys to swanky startups like Mad Street Den, contributing to shaping the global AI landscape with revolutionary applications.

The post Top 10 Deep Learning Companies in India appeared first on ELE Times.

Активні студенти та аспіранти КПІ ім. Ігоря Сікорського відзначені КМДА і Солом'янською РДА! kpi чт, 08/21/2025 - 11:23

Decade-long partnership overcame complex payload design challenges to empower next-generation environmental research from space

• A deeply-coupled partnership between TI and SAC-ISRO helped enable the mission payloads for the NISAR satellite, which is currently orbiting Earth.
• TI’s space-grade power management, mixed signal and analog technologies optimize system performance and allow the satellite to operate in the harsh environment of space over the mission’s lifetime.
• NISAR is the first satellite to use dual-band synthetic aperture radar technology to monitor the Earth’s ecosystems, natural hazards and climate patterns.

Texas Instruments (TI) semiconductors are enabling the radar imaging and scientific exploration payloads for the NASA-Indian Space Research Organization (ISRO) synthetic aperture radar (NISAR) satellite, which was recently launched into orbit. The launch of the satellite culminates a decade-long partnership between TI and the ISRO to optimize the performance of the electronic systems responsible for this Earth-observation mission. NISAR is equipped with TI’s radiation-hardened and radiation-tolerant products that enable designers to maximize power density, precision and performance in their satellite systems.

Engineering a first-of-its-kind satellite for Earth observation

The ISRO describes NISAR as the first Earth-observation mission to use dual-band synthetic aperture radar (SAR) technology, enabling the system to capture precise, high-resolution images during the day, night and all weather conditions. TI’s technology is enabling the satellite’s next-generation capabilities through efficient power management, high-speed data transfer, and precise signal sampling and timing.

The NISAR satellite will image the entire planet every 12 days, offering scientists greater understanding of changes to Earth’s ecosystems, ice mass, vegetation biomass, sea-level rise and groundwater levels. The agencies also expect the data to improve real-time monitoring of natural hazards such as earthquakes, tsunamis, volcanoes and landslides.

“From selecting the right products to ensuring consistent support across development cycles, TI’s technical expertise helped us navigate complex payload requirements,” said Shri Nilesh Desai, Director, Space Applications Centre (SAC), ISRO. “A deeply coupled partnership, specifically focused on high-impact mixed signal and analog semiconductors, enabled ISRO to meet the system-level requirements for a satellite in low Earth orbit. Together, we achieved the space-grade performance standards needed for this important mission.”

Addressing complex design challenges with TI’s space-grade portfolio

Throughout the project life cycle, TI’s system expertise and space-grade semiconductors, which are designed to withstand the harshest space environments, helped enable the advanced S-band SAR capabilities of the NISAR mission. The company provided:

• Radiation-hardened power management die for SAC-ISRO developed point-of-load hybrid power module, helping optimize size, weight and power for the mission payloads.
• Analog-to-digital converters with ultra-high sampling rates and high resolution, allowing the satellite payload to generate fine-grained, high resolution radar imagery.
• High-performance interface technology, which enables high-speed data transfer between different satellite subsystems to ensure reliable communication.
• A clocking solution that enables the precise time alignment and synchronous, coherent sampling required for high-precision SAR systems.

“As the NISAR satellite is now in orbit, I reflect on the decade-long partnership that brought us here and how our teams are already looking to what’s next, developing new technologies that will enable future missions,” said Elizabeth Jansen, TI India’s sales and applications director. “Building on more than 60 years of expertise, TI’s radiation-hardened and radiation-tolerant semiconductors are ready to meet the evolving demands of the space market. Our broad and reliable space-grade portfolio is ever-expanding and pushing the limits of what’s possible in the next frontier.”

The post TI semiconductors enable advanced Earth-observation capabilities of ISRO’s first-of-its-kind NISAR mission appeared first on ELE Times.

• Infineon India has signed a Memorandum of Understanding (MoU) with the Department for Promotion of Industry and Internal Trade (DPIIT)
• This further strengthens Infineon’s long-standing commitment to foster the country’s startup ecosystem
• Recent startup success stories contribute to energy-efficient e-mobility and smart e-health solutions

India is rapidly emerging as a hub for semiconductor innovation. As a global leader in power semiconductors and the Internet of Things (IoT), Infineon has been collaborating with Indian start-ups for years, recognizing the importance of this in accelerating innovation. With a focus on supporting advancement and entrepreneurship in the country the company has formed partnerships with various organizations, including NITI Aayog, Startup India, and the Ministry of Electronics and Information Technology (MEITY), to promote the “Make in India” initiative and foster startup growth.

Memorandum sparks startup innovation in IoT, electromobility, and security

As part of its ongoing efforts, Infineon India has signed a Memorandum of Understanding (MoU) with the Department for Promotion of Industry and Internal Trade (DPIIT) this year. The MoU aims to develop, foster, and promote the country’s innovation ecosystem by encouraging and supporting engineering students, product startups, innovators, and entrepreneurs through design challenges using Infineon’s innovative products to address applications of relevance for India.

“We are committed to empowering India’s startup ecosystem in microelectronics”, said Vinay Shenoy, Managing Director of Infineon India. “Partnerships such as the MoU with DPIIT allow us to work with innovative startups, giving them access to state-of-the-art technologies and our local and global networks. In return, we tap into their agility and entrepreneurial spirit, driving mutual growth and strengthening India’s innovation ecosystem.”

Propelling the Indian startup ecosystem

Infineon India has collaborated with various incubators and innovation ecosystems for years, including the Foundation for Science Innovation & Development at IISC Bangalore, IIT Madras Incubation Cell, and Artpark, AI & Robotics Technology Park @IISC. These partnerships have enabled the company to support startups and innovators in the country, and provide them with access to resources, expertise, and funding. Some of the key initiatives undertaken by Infineon India include the AI Challenge with Startup India and AGNIi, the solar pump motor drive challenge, and the MoU with MEITY to support the MEITY startup hub. These initiatives have helped to promote innovation and entrepreneurship in the country and have provided a platform for startups and innovators to showcase their ideas and products.

Startup collaborations for sustainable e-mobility and smart e-health

Recent Infineon partnerships with startups like e-Drift Electric, EYDelta or Mimyik are successful examples of collaboration with significant impact on e-mobility and e-charging as well as smart health solutions.

As part of Infineon’s co-innovation program, e-Drift Electric is contributing to the development of electric vehicle (EV) charging infrastructure. The start-up is focusing on creating energy-efficient modules using Infineon’s Si-SiC-MOSFET portfolio. As the adoption of EVs accelerates, it is increasingly important to develop an energy-efficient and robust charging infrastructure to ensure a cleaner and greener future for transportation in India.

For EYDelta the partnership with Infineon enables a faster product development and manufacturing of electric motors and motor controllers for multiple sectors like e-mobility, drones, and aerospace. By integrating AI-driven diagnostics and cloud-connectivity the solutions enable smarter IoT-ecosystems, help optimizing energy consumption, reduce emissions, and drive sustainable transportation systems in India and abroad.

The cooperation with Mimyk, a startup, spun out of the Indian Institute of Science Bangalore, is focusing on metabolic health monitoring. Infineon provided latest microcontrollers as well as access to the global Infineon semiconductor network. This partnership will accelerate development cycles and transform health monitoring to make health tracking smarter and easily accessible for everyone.

This demonstrates how Infineon’s co-innovation program fosters a strong ecosystem in India, empowering startups to grow as well as accelerating innovation-to-customer value, together.

The post Infineon strengthens startup ecosystem in India appeared first on ELE Times.

The company is launching devices across the gamut of power applications, including a GaN driver, dual-channel automotive driver, and battery-protection MOSFET.

submitted by /u/nihilianth [link] [comments]

Learn the hybrid design configurations used in today’s TWS earbuds, along with the engineering challenges that OEMs face when designing hybrid models.

To know more about the project, here's my repo link: https://github.com/0101shift/Project_OAK submitted by /u/0101shift [link] [comments]

We are told that LED-based lighting will provide a very long service life per bulb, but here comes “Sportin’ Life” again (from Porgy and Bess) to put the lie to that claim. (It ain’t necessarily so.)

These four LED lamps each went dark after only a few months of service despite their packages’ promise (Figure 1).

Figure 1 Four LED bulbs that failed after a few months despite their service life being over 20 years.

Similarly, one of the five LED lamps in this ceiling fixture also went dark after only a few months of service (Figure 2).

Figure 2 One in five LED bulbs in this ceiling lamp was rendered nonfunctional only after a few months.

In my eighty years in this world, I have only twice seen a new incandescent lamp fail so soon after being put into service. One lamp had a service life of thirty minutes and the other one died almost instantly.

I tried to cut open one of the four failed conical LED lamps to see what specifically had gone wrong, but I couldn’t manage to penetrate the shroud. Those plastic bulb enclosures were made of really tough stuff. Failing in that effort, I simply threw the four of them out.

Nevertheless, four for four strikes me as a pretty shabby history. I replaced each of the four with products from a different manufacturer, and so far, since pre-pandemic times, those LED bulbs are still working.

It can be done.

John Dunn is an electronics consultant and a graduate of The Polytechnic Institute of Brooklyn (BSEE) and of New York University (MSEE).

 Related Content

• Teardown: What killed this LED bulb?
• What’s the storage life of idled LED light bulbs?
• Incandescent lamps and service life
• Rich voltage, poor voltage: My incandescent tale
• The burned-out bulb mystery
• The LED: incandescent light bulb heir apparent

The post The empty promise of the LED bulb’s lifetime appeared first on EDN.

Design Idea (DI) contributors have recently explored various possibilities for ON/OFF power control using just a momentary contact “shiny modern push-button,” many of which build off of Nick Cornford’s “To press on or hold off? This does both.”

These ideas are interesting, and they’ve suggested a different notion. Figure 1 takes the one-button power control concept a bit further. It uses its button to provide six bits of resolution to a kilowatt of variable AC power, addressing adjustable applications like heating blankets, lamp dimming, motor speed, etc. I like it because, well, shouldn’t there be a bit (or even six) more to life than just ON/OFF?

Figure 1 Variable AC power control with a simple pushbutton. When S1 is pushed, counter U1 ramps through the 64 DAC codes in a 210 / 120Hz = 8.5-second cycle and stops on any selected power setting when S1 is released.

Wow the engineering world with your unique design: Design Ideas Submission Guide

Power control method

The power control method employed in Figure 1 is variable AC phase angle conduction via thyristor Q3. It’s wired in the traditional way except that the 6-bit DAC driven by CMOS counter U1 fills in for the usual phase adjustment pot. Because, unlike Q3, the DAC circuitry isn’t bidirectional, the D1-4 rectifier is needed to feed it DC and keep it working and counting through 60-Hz alternations.

Full power Q3 efficiency is around 99%, but its maximum junction temperature rating is only 110 °C. Adequate heatsinking of Q2 will therefore be necessary if output loads greater than 200 W are expected.

Adjusting U1 to the desired power setting is accomplished by pushing and holding switch S1. This connects the 120-Hz full-wave rectifier signal from the D1-D4 bridge to the Schmitt trigger formed by R2, R3, and U1’s internal non-inverting q0 input buffer.

The subsequent division of the 120 Hz signal by U1’s ripple divider chain makes flip-flop q5 toggle at 120/25 = 3.75 Hz, q6 at 120/26 = 1.875 Hz, and so forth down to q10 at 120/210 = 0.117 Hz. This gives a ramp time of 8.5 seconds for the full 0 (= full OFF) to 63 (= full ON) code cycle. Meanwhile, digital integration of the raw signal from switch S1 by U1’s counters suppresses switch contact bounce.

When the desired power setting (lamp brightness, motor speed, etc.) is reached, release the button, i.e., just let go! However, due to the fairly rapid toggle rate of the lower counter stages, a bit of practice may be required to accurately hit a target setting on the first try.

DAC topology

The DAC topology is straightforward. Just six (R4 through R9) binary-weighted resistors make up a summing network that produces a 0-V to 15-V input to the Q1 Q2 complementary current-mode output buffer.

Q1 provides nominal compensation for Q2’s Vbe offset and tempco, as well as sufficient current gain to allow use of multi-megohm resistances in the summation network. This is important because operating power for the DAC is basically stolen from Q3’s phase control signal.

This (as you probably noticed), nicely avoids the need for a separate power supply, but it provides only microamps of current for U1 and friends. So, a power-thrifty topology was definitely needed.

DAC reference Z1 is remarkably content with its meager share of this starvation diet. It maintains a usefully constant regulation despite only a single-digit microamp bias, which is impressive for an 11-cent (in singles) part. Meanwhile, U1 daintily sips only tens of nanoamps.

R11 and C3 provide an initial reset to OFF when power is first applied.

At this point, you might reasonably ask: Is this scheme any better than a simple pot with a twistable knob? Well, don’t forget the “shiny modern push-button” factor.

Stephen Woodward’s relationship with EDN’s DI column goes back quite a long way. Over 100 submissions have been accepted since his first contribution back in 1974.

Related Content

• To press on or hold off? This does both.
• To press ON or hold OFF? This does both for AC voltages
• Latching power switch uses momentary pushbutton
• A new and improved latching power switch
• Latching power switch uses momentary-action pushbutton

The post A different twist to the power pushbutton problem: A kilowatt AC DAC appeared first on EDN.

By: STMicroelectronics

Smartphones have become some of the most ubiquitous devices in modern history. For most of us, the smartphone is an indispensable tool to not only communicate, but to manage our lives – work, personal relationships, travel, shopping, entertainment, photography, video creation. In short, smartphones have become a hub for life. 

 The touchscreen was transformational in the smartphone’s adoption and use. But in the future, the smartphone is set to become a platform for immersive experiences. And when aligned to innovations that will extend battery life and even see smartphones harvesting their own energy, along with new ways to stay constantly connected, their usefulness will only increase.  

 A powerful processor in your pocket

Smartphones have become incredibly powerful processing devices. Indeed, in comparison to the most powerful supercomputers of the 1980s, today’s smartphones can process information more than 5,000 times faster. 

In some ways, however, the way that we interact with our smartphones has progressed least since their arrival. For many people, the touchscreen remains the primary – if not only – way that they access and view the interactive services and rich experiences provided by their smartphone. The coming years will see that transformed and, with it, the idea of what a smartphone is. 

A reduced reliance on the smartphone display as the principal way to interact with the device and receive information fundamentally changes the role of the smartphone. As a powerful computing device in its own right, but also connected to cloud-based computing resources, the smartphone potentially becomes a platform for delivering immersive experiences and valuable services to the user in numerous new ways.  

New models for smartphone interaction

Voice assistants have become one of the first steps into a new world of accessing services via our smartphones. Whether issuing voice commands and queries directly into the device or having these relayed via connected headphones and earbuds, consumers are realising the convenience of voice and audio interaction. An additional benefit, of course, is that the smartphone itself can remain in a pocket or bag, out of harm’s way. 

Eyeglasses featuring augmented reality (AR) display technology are an ideal solution. These can visually display directions in the user’s eyeline, while also overlaying other useful or interesting information. With more information and experiences layered over the real world, discovering a new city will be more rewarding than ever before, with less potential for a misstep along the way. 

Artificial intelligence (AI) will also enable proactive and predictive services that help us manage our daily lives. For example, by understanding the current traffic conditions, AI might bring an alert for your next meeting across town 30 minutes earlier. With the alert appearing on your smartwatch, more efficient travel could be proposed, with directions to the closest public transport appearing in your eyeglasses’ AR display. 

Gesture recognition and haptic feedback

Gesture recognition is emerging as another way to interact with services provided by smartphones. Less obvious that either using a touchscreen or voice, subtle gestures to make or answer calls or respond to messages will be quick and convenient methods of interaction. Who knows, you might well respond to the latest message received with an actual thumbs up, rather than having to find and type the emoji itself.  

We might be on the cusp of a whole new vocabulary of gestures as commands. Google is one company looking at how devices can be controlled by natural human gestures, many of which we use subconsciously. Other advances in hardware, such as the latest generation of Time-of-Flight (ToF) sensors, will support more accurate detection of gestures in and around smartphones. 

Haptic feedback is the use of vibrations or sensations to enrich the experience of using a device. At a basic level, most of us already experience haptic feedback in our smartphone use. Vibrations rather than a ringtone to signify an incoming call is a simple example, but the nature and application of haptic feedback is rapidly evolving. 

Imagine shopping online and being able to ‘feel’ different types of fabric through haptic feedback via your smartphone’s screen. Subtle vibrations from different parts of smart eyeglasses could be used to enrich visual experiences or help with directions. Research is even looking at ultrasound and “mid-air” haptics, where the sensation of physical touch is created in the air. Such haptic feedback could augment gesture control or enhance touchless interfaces. 

The potential for neural interfaces

Though still in its early stages, the idea of interacting with devices merely by thinking is becoming more real. Various non-invasive neural interfaces are in development.  

Electroencephalography (EEG) sensors placed on the head via headsets, or potentially even embedded in hats and headbands, are a direct way to tap into the brain’s activity. Neural wristbands detect signals from nerves connecting the brain to an individual’s hands, whereby just thinking about a gesture or action could act as a command.  

So-called “silent speech” interfaces detect subtle changes in expression or movements in vocal chords, where simply mouthing words would be detected as accurately as voice. Data from wearables such as smartwatches, rings, and earbuds, could identify cognitive load and emotional state, triggering proactive alerts, suggestions, or experiences to help alleviate issues.  

Projecting further into the future, neural interfaces and advanced haptic feedback could be combined to create a new world of deeply immersive experiences, all powered by the not-so-humble smartphone. 

Always connected

Of course, this vision of the smartphone as a platform for new services and experiences relies on an almost constant connection to cloud-based computing resources. Fortunately, alongside the innovations in smartphone interface technologies, we’re seeing continued development of technologies that ensure we remain connected, wherever we are. 

As we recently highlighted, the need to connect the world of increasingly intelligent “things” – not only smartphones, but billions of sensors, machines, and consumer products – is being supported by innovation in communications technology. This includes further evolution of established infrastructure, with 6G telecommunications networks arriving in the coming years, but also the significant expansion of satellite-based communications networks.  

When the smartphone arrived it was exactly that: a phone with additional capabilities. We can all appreciate how far it has moved beyond that simple description, and over a relatively short period of time. While we might need a new name for the device, we certainly need to change our understanding of what this powerful pocket processing device represents.

New ways to interact with our smartphones, innovation in the delivery of seamless immersive experiences, universal connection, and improved battery life and self-charging, will see them become the primary digital platform for every aspect of our lives.

The post Beyond the Screen: envisioning a giant leap forward for smartphones from physical objects to immersive experiences appeared first on ELE Times.

AXT Inc of Fremont, CA, USA – which makes gallium arsenide (GaAs), indium phosphide (InP) and germanium (Ge) substrates and raw materials – says that its China-based manufacturing subsidiary Beijing Tongmei Xtal Technology Co Ltd has been informed that it has satisfied the applicable requirements for a permit to export indium phosphide and has received export permits from the Ministry of Commerce of the People’s Republic of China to resume shipping indium phosphide substrates to certain additional customers...

A subfield of machine learning called “deep learning” uses artificial neural networks to learn from data in an attempt to mimic human learning. Artificial neural networks, inspired by the human brain, are versatile enough to tackle a wide array of issues from speech recognition to image recognition and natural language processing. The top 10 deep learning applications & use cases that are spurring innovation worldwide will be examined in this article.

1. Autonomous Vehicle

Deep learning is crucial for self-driving cars, allowing them to interpret more-or-less simultaneous data streaming from sensors, cameras, and radar systems as they move through the world. Allowing real-time models to engage in split-second decisions, these models help vehicles identify pedestrians, traffic signs, and other vehicles so that safety is ensured. The companies working with these models are at the forefront of autonomous mobility, aiming for fewer accidents and more efficient transport through these means.

2. Healthcare

In medicine, deep learning helps in disease diagnosis and treatment. Cancer, heart illness, and tumors are detected on the basis of medical images such as X-rays, MRIs, and CT scans evaluated with higher accuracy by algorithms. It is useful for drug discovery, remote health monitoring, and personalized medicine as well.

3. Natural Language Processing (NLP)

Natural language processing is a significant feature of deep learning systems that work on text and speech interpretation. Natural language Processing serves certain applications like sentiment analysis, language translation, and customer support chatbots.

4. Facial Recognition

Deep learning-based facial recognition systems essentially identify and verify individuals based on facial characteristics. Its uses for smartphones include a secure method for unlocking, for airports in passenger verification, and for public safety surveillance.

5. Fraud Detection & Finance

Financial entities use deep learning in order to detect fraudulent transactions and cyber threats. These models conduct an agglomeration of data points numbering in the millions as patterns to flag an anomaly that might constitute identity theft, credit card fraud, or insider trading. This proactive approach helps protect the consumer and builds confidence in digital banking systems.

6. Satellite Imaging and Earth Observation

Such deep learning technologies assist in analyzing satellite imagery for climate monitoring, urban planning, and disaster-management applications. It can track deforestation, glacial movement, or the magnitude of damage caused by a natural disaster.

7. In-Vehicle Personalization

Deep learning enhances the driving experience by adapting vehicle settings and features to individual preferences. These systems learn from driver behavior and environmental conditions to optimize comfort, convenience, and entertainment.

8. Robotics and Industrial Automation

Robots with deep learning enable them to perform complex tasks such as object recognition, defect detection, and predictive maintenance in the manufacturing and logistics arenas. These intelligent systems decrease operating expenses, increase efficiency, and lessen human mistake. Robots powered by artificial intelligence are changing industrial processes, from precise assembly lines to warehouse automation.

9. Predictive Maintenance

Predictive maintenance powered by deep learning helps industries anticipate equipment failures before they happen, minimizing downtime and reducing repair costs.

10. Cybersecurity

To avoid hacking and illicit access, deep learning models detect anomalies in network traffic of an automobile. This role grows more and more critical as cars get more and more connected.

Conclusion:

From health care to cyber-security, applications of deep learning are serving as building blocks for the future of technology. This, in turn, shows the process by which AI is mixing itself in everyday life. With more applications being discovered, deep learning will be building smarter, safer, and more efficient systems for all sectors of economy.

The post Top 10 Deep Learning Applications and Use Cases appeared first on ELE Times.

На війні загинув випускник нашого університету Сергій Либенський kpi ср, 08/20/2025 - 11:09

Arc generator modules may be small in scale, but they offer big opportunities for hands-on exploration in electronics. Whether you are experimenting with arc simulation, testing circuit behavior under fault conditions, or simply curious about high-voltage phenomena, these minuscule modules provide a safe and accessible way to dive into the fundamentals.

This blog will present hands-on tips and tricks for working with hobby-grade arc generator modules and circuits—ideal for curious minds and budding engineers eager to explore high-voltage experimentation.

There are several methods for generating electric arcs. However, this post will focus on how to achieve extra-high voltage levels using simple electronic circuits. The spotlight is on a widely available, budget-friendly arc generator module kit designed for DIY enthusiasts. It’s an accessible way to dive into high-voltage experimentation without breaking the bank.

Take a look at the kit below, along with its key technical specs to help you understand what it offers.

• Input voltage: 3.7 V to 4.2 V DC
• Input current: < 2 A
• Output voltage: ~15 kV
• Output current: ≤ 0.4 A
• Ignition distance (high voltage bipolar): ≤ 0.5 cm

Figure 1 This compact arc generator kit delivers around 15-kV output using only a handful of components. Source: Author

This is arguably one of the elementary and most accessible kits for electronics enthusiasts looking to explore high-voltage applications. The module requires minimal setup skills, with no circuit-level adjustments needed. While the power output is not exceptionally high, even a minor mishap can result in serious electrical burns. That said, with proper safety precautions in place, the system can produce stunningly high-frequency arcs.

Now, let’s take a look at the schematic diagram to understand how the circuit works.

Figure 2 The schematic diagram demonstrates how the kit produces high voltage through a minimal circuit design. Source: Author

Examining its internal electronics reveals a single-transistor oscillator at the heart of the circuit. This simple yet effective configuration allows high-voltage generation from standard battery cells.

Functionally, it acts as a step-up (booster) transformer system, where a feedback loop controls the switching of a power transistor. The secret to high-voltage output lies in the transformer’s winding setup. It uses two primary coils—main and feedback—alongside a secondary winding that can produce voltages soaring into the kilovolt range.

The diode’s most critical function in this oscillator circuit is to block the reverse voltage pulse generated by the transformer’s collapsing magnetic field. This action is essential for two reasons; it prevents damage to the transistor and ensures a clean transition to the “off” state.

Next is another compact high-voltage boost module (sometimes labelled as XKT203-33) capable of generating up to 30 kV. Specifically engineered for pest control applications, it finds use in devices aimed at eliminating mosquitoes, cockroaches, and other small insects. Despite its impressive output, the module operates efficiently with minimal power input, making it ideal for battery-powered or low-power systems.

The image below presents the aforesaid module alongside its internal schematic for reference. A closer look at the available schematic highlights the use of proprietary components, with a Delon voltage doubler circuit strategically placed at the output stage to deliver the required 30 kV.

Figure 3 The 30-kV module achieves high-voltage generation through an elegantly minimal design. Source: Author

Interestingly, a closer look at two seemingly popular kV generator modules shows that even humble jellybean components can handle the task. Still, integrating custom parts might elevate performance and efficiency.

But before jumping to conclusions, consider this alternative design idea for building your own kV generator module, an approach many have explored with intriguing results. Let’s take a quick look.

Figure 4 The blueprint shows how to generate high-voltage output using an automotive ignition coil. Source: Author

This approach simply utilizes a universal automotive ignition coil to produce high-voltage output, as depicted in the self-explanatory diagram above.

At its core, an ignition coil consists of three main components: a primary winding, a secondary winding, and a laminated iron core. Secondary winding contains significantly more turns of wire than the primary, creating a turn ratio that directly influences the voltage increase. There is a fairly typical range for the ignition coil turns ratio, usually between possibly 50:1 to 200:1, with 100:1 probably being the most common.

Just to add, in an inductive ignition system, the primary winding is typically energized with 12 V or 24 V. When this current is suddenly interrupted, a high-voltage EMF is induced in the secondary winding—often reaching 20 kV to 40 kV—more than enough to jump across a spark gap.

To break it down further, a single switching action by a transistor (BJT/IGBT/MOSFET) initiates the ignition process by allowing current to flow through the ignition coil’s primary winding. The current charges the primary coil, storing energy in its magnetic field. When the transistor turns off and interrupts the current, the magnetic field begins to collapse.

In response, the coil resists the sudden change, causing a rapid rise in voltage across the secondary winding, ultimately generating the high-voltage spark needed for ignition. It’s enough to ionize the air to create a spark.

Back to the subject matter, when driving the ignition coil through either an IGBT or a MOSFET, try experimenting with appropriate square wave pulses. Start with low frequencies around 150 to 350 Hz and duty cycles between 25% and 45% (just to get a feel for the response).

Heads up! Touching the high voltage from the ignition coil will definitely sting. It won’t kill you, but it will make you regret it.

That wraps up this post. I have got plenty more practical tips and insights lined up, so expect fresh content soon. This is just one piece of a much larger puzzle.

Finally, please note that this article is intended purely for informational and educational purposes. It does not promote, endorse, or commercially affiliate with any product, brand, or service mentioned. No sponsorships, no hidden agendas—just straight-up knowledge for curious minds.

T. K. Hareendran is a self-taught electronics enthusiast with a strong passion for innovative circuit design and hands-on technology. He develops both experimental and practical electronic projects, documenting and sharing his work to support fellow tinkerers and learners. Beyond the workbench, he dedicates time to technical writing and hardware evaluations to contribute meaningfully to the maker community.

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The post Hands-on with hobby-grade arc generator modules appeared first on EDN.

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