Self-driving cars are quickly becoming the vehicle of choice for futurists. But while many automakers are prioritizing the development of accessible self-driving vehicles by as early as 2019, there’s still a good deal of work to be done before autonomous cars become additions to every American household.
In fact, you may be more likely to have one of these five cool car gadgets or pieces of automotive technology in your vehicle before a four-wheeled robot is driving you to work each morning.
5. Brain-to-Vehicle Technology
Nissan’s innovative “brain-to-vehicle” technology is, frankly, downright crazy.
Announced and showcased at the 2018 Consumer Electronics Show in Vegas, the B2V (brain-to-vehicle) system uses EEG brain waves (electroencephalography) to monitor the driver’s vital signs in an effort to ultimately improve reaction times by milliseconds. The tech then adjusts the vehicle’s path, speed, or braking power to prevent collisions or injury.
Because the ability to measure brain synapses via EEG can oftentimes be problematic, Nissan is cautiously aiming to make B2V a practical application within the next decade.
4. Advanced Tech Car Windows
Rear DVD players and tablet holders are yesterday’s news.
GM (and other automakers) have been developing a new form of rear-seat entertainment to replace the ancient gadgets that have kept kids occupied since the turn of the century. In the future, car windows will become interactive displays that are capable of broadcasting videos, accessing weather and traffic reports, changing in-cabin music, and playing games, among other things.
There are no immediate plans to implement this futuristic technology in upcoming Chevy, GMC, or Buick vehicles, but we are excited to see what the GM engineers can muster up over the next few years.
3. 5G LTE Wi-Fi
It seems like we’ve been living in a 4G world for far too long, hasn’t it? The time has come to make an upgrade.
Kia recently unveiled their newest dashboard concept for driverless cars in Seoul, South Korea, but it’s their marquee 5G LTE connectivity everyone’s raving about. Demonstrated in the Kia HQ, the new 5G connection offers blistering speeds that allow operators to stream bufferless videos, access data, and sync GPS data in the drop of a hat. More importantly, the increased speed of 5G is undoubtedly necessary if autonomous vehicles are to take over the roads.
No standard rollout for 5G service has been agreed upon federally or within the industry, so you may be waiting a couple years before it’s available in new vehicles.
2. 3D-Printed Car Parts
Maybe your cousin first introduced you to 3D printers by showing you his custom-designed fidget spinner. Soon enough, carmakers will be taking 3D printing to the next level.
Last year, Ford announced a future strategy to manufacture large-scale auto parts using a specialty 3D printer, which will theoretically reduce the cost of such car parts and vehicles in general. These printed auto parts will be highly durable, lighter in weight, and can be produced virtually labor-free.
To guarantee the 3D-printed car components are safe, Ford and other automakers will continue tests through 2020 and beyond.
1. Wireless EV Car Chargers
For now, electric vehicles must be plugged in to charge their batteries. In the future, charging your EV may be as easy as placing a pad no larger than a floor mat under the chassis.
In 2017, scientists at Stanford University discovered a more efficient way to charge electric vehicles: Wireless charging pads. Much like your Qi phone charger, these EV pads use magnetic resonance and adjusted transmitter frequencies to transfer power organically to the car’s battery pack. In laymen’s terms, this means maintaining your vehicle’s charge may be an unnecessary task entirely.
The biggest perk of this discovery is how it addresses the main disadvantage of all-electric vehicles—a limited driving range. Most EVs are unable to travel more than a few hundred miles before their battery needs to be charged; this solution becomes a charge-as-you-go system that puts those limitations to rest. In theory, the wireless charger enables electric vehicles to operate continually.
Simply can’t wait for the new-age car tech to be available? There’s still a lot to love about the lineup of current 2018 vehicles for sale at our Kansas City car dealerships! Many of our new vehicles have built-in GPS, safety systems, voice-activated Bluetooth connectivity, and convenient features that alleviate your everyday driving stressors. Come take a test drive by contacting your nearest McCarthy Auto Group dealer in Kansas or Missouri.
Sources & Media:


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Dolby Vision Technology: HORIZON Ultra offers an unparalleled home theater experience with true Dolby Vision, ensuring exceptional brightness, color accuracy, and premier image quality.
Impressive Brightness with 2300 ISO Lumens:
Ultra-High Brightness: Enjoy stunning image detail day and night with HORIZON Ultra’s 2300 ISO Lumens, providing ultra-high brightness and lifelike color for an immersive viewing experience.
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Intelligent Screen Adaption 3.0:
Enhanced ISA Technology: Our upgraded ISA technology, Intelligent Screen Adaption 3.0, optimizes environmental adaptability, ensures easy usage, facilitates wall color adjustment, enables optical zoom, and introduces other advanced features for an unparalleled viewing experience.
Premium Audio with Dual 12W Harman Kardon Speakers:
Theater-Quality Sound: Immerse yourself in three-dimensional surround sound with HORIZON Ultra’s dual 12W Harman Kardon speakers, enhanced by DTS Studio Sound Technology, delivering an unforgettable theater audio experience.
State-of-the-Art Dolby Vision: HORIZON Ultra provides an unmatched home theater experience with Dolby Vision, ensuring exceptional brightness, color accuracy, and image quality.
Versatile Brightness: Enjoy stunning image detail at any time with 2300 ISO Lumens, providing ultra-high brightness for a lifelike viewing experience.
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Intelligent Viewing Adaptability: ISA 3.0 optimizes environmental adaptability, wall color adjustment, optical zoom, and other features for enhanced usability.
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Elevate your home entertainment with HORIZON Ultra, where cutting-edge technology and intelligent features converge for an unparalleled visual and audio experience.
Intelligent Eye Protection
Intelligent Screen Alignment
21 × 22 × 14 in
In the Box
1. Brightness (light output) will vary depending on usage conditions. White light output measured in accordance with ISO 21118. The nominal value represents the average value of mass production and is tested under ideal laboratory conditions in the performance mode/high power mode.
2. For the best viewing experience. we recommend using a projection size of 60-120 inches. Exceeding this range may affect the quality of your projected content. The display quality may vary based on product usage habits and environmental conditions.
3. Android TV is a trademark of Google LLC.
4. Router required.
5. 25,000 hours is the theoretical lifespan of the light source. The actual lifespan may vary due to differences in environmental conditions, product usage habits and the mode selected.
6. The actual storage capacity is subject to change based on various factors, such as system usage, software version, and settings used.
7. Measured under an ambient temperature of 25°C with a 1-meter distance from the machine. Results may vary based on different testing environments, conditions, and the product being evaluated. This data comes from XGIMI laboratories.
8. The measured size may vary based on configuration, manufacturing, and measurement method.
9. The measured weight may vary based on configuration, manufacturing process, and measurement method.
* Actual product features and specifications (including appearance, color, and size) and actual display aspects (including backgrounds, interface, and icons) may vary by country. Please consult the point of sale for further information.
* All performance data in the preceding pages are theoretical values obtained by XGIMI internal laboratories through tests conducted under particular conditions. Refer to the aforementioned product details for more information on the specific testing conditions. Actual performance may vary based on individual product configurations. software versions, application conditions, and environmental factors. All data is subject to actual usage.
* XGlMl makes every effort at the time of publicationto ensure the accuracy of product information it provides. Due to subsequent changes involving product batches, production, and supply factors, it may be necessary for XGlMl to make changes and adjustments to text and images so that they match the performance, specifications, indexes, and components of the actual product. Product information is subject to such changes and adjustments without notice.
* Operating temperature: 0℃to 40℃.
* All parameters listed on this page are measured in an XGIMl internal test environment for mass production. User experiences may vary in different settings, usage conditions, software versions, etc. Please check the official XGlMl website for detailed test standards and data.
* The product will be attached with a printed manual. However, the electronic manual will be updated on the XGlMl website. If there is any discrepancy or conflict between the printed and the electronic manual, please refer to the latest electronic manual on the official website: https://indoorgolfvalley.com/
* The typical value of ΔE≈1 for color accuracy in the factory production of XGIMI HORIZON Ultra is obtained from the XGIMI Optical Laboratory. The calibration parameters will take effect when the high color accuracy mode is correctly activated in the system. Color accuracy may vary slightly depending on factors such as projection usage time and lab testing equipment. Please refer to your actual experience for an accurate assessment.
* SGS Certification Number: PT/23/GEN/0063
* The Wall Color Adaption feature needs to be enabled in the system settings to take effect. Once activated, it can calibrate the picture based on wall colors with a color temperature ranging from 3000K to 15000K. However, the calibration effect may vary depending on the wall color. For optimal results, we recommend using it in dimly lit environments.
* All of XGIMI’s currently available floor stands and ceiling mounts are incompatible with HORIZON Ultra.


University of Cádiz
Installation of Ecovolt solar panels water preheating system for low temperatures and hot climates
This 80-panel installation is designed to preheat water for a fish farm. The application required a low target temperature (around 22ºC), in addition to having high electricity consumption. The annual production per panel in these latitudes is 425 kWh electric and 840 kWh thermal. The ECOVOLT system is a hybrid panel that is covered with a high efficiency photovoltaic laminate. It is able to ensure a good yield even in hot climates, where typically it would be badly affected by the very high temperatures. The ratio of thermal to electrical production of the panel is close to 2:1.
ECOVOLT hybrid solar panels produce hot water at low temperatures while generating electricity with an improved performance over regular photovoltaic panels. Simultaneous production means that the energy generation of the panel is up to twice that of a standard photovoltaic panel, taking full advantage of the solar energy and, thus, reducing fossil fuel consumption.
Using hybrid panels in the fish farm is the first instance of them being employed for this purpose in either Spain or Europe. As it is an uncovered panel, the ECOVOLT hybrid system works at a lower temperature than other solar panels, benefiting the performance of the photovoltaic laminate even in hot climes where high temperatures negatively impact efficiency.


Published in Science, 28 February 2019: A team from Northwestern University has published on their wireless sensor technology, used for intrapartum and newborn monitoring.
"In neonatal intensive care units (NICUs), continuous monitoring of vital signs is essential, particularly in cases of severe prematurity. Current monitoring platforms require multiple hard-wired, rigid interfaces to a neonate’s fragile, underdeveloped skin and, in some cases, invasive lines inserted into their delicate arteries. These platforms and their wired interfaces pose risks for iatrogenic skin injury, create physical barriers for skin-to-skin parental/ neonate bonding, and frustrate even basic clinical tasks. Technologies that bypass these limitations and provide additional, advanced physiological monitoring capabilities would directly address an unmet clinical need for a highly vulnerable population.
The advances outlined in the publication serve as the basis for a skin-like technology that not only reproduces capabilities currently provided by invasive, wired systems as the standard of care, but also offers multipoint sensing of temperature and continuous tracking of blood pressure, all with substantially safer device-skin interfaces and compatibility with medical imaging. By eliminating wired connections, these platforms also facilitate therapeutic skin-to-skin contact between neonates and parents, which is known to stabilize vital signs, reduce morbidity, and promote parental bonding. Beyond use in advanced hospital settings, these systems also offer cost-effective capabilities with potential relevance to global health."
This paper shows preliminary studies on neonates admitted to the NICU, and demonstrates that their device performs comparably to more advanced clinical-standard monitoring systems.
Read the full article here.


Motorised Blinds And Curtains In Beaconsfield, Buckinghamshire
Motorised Roller Blinds From Only £140.00 – including charger and remote.
Why Choose Motorised Blinds?
- Child safe
- Wire free
- Lifts a blind measuring up to 8 sq/m
- 4 hour recharge just twice a year
- Smart home compatible “hey Alexa, close the blind”
- Operate remotely from your smartphone or tablet
- Quiet and smooth soft start and stop
- Retro fit to existing blinds with a 32mm or 40mm tube
Battery Powered Blinds And Curtains
The battery blind motorisation systems available today are incredible. They are quiet, fast and run for long time between charges. Charging a motorised blind is as easy as charging a mobile phone.
The beauty of battery operated motorised blinds and curtains is that they can be installed once a project has been completed. You also avoid the cost of an electrician. We can even easily retrofit motors to existing blinds.
The most popular product is battery motorised roller blinds and the motors are great. They are quiet, stylish and very easy to use via remote control, an app on you phone or via a smart speaker.
Hardwired Blinds and Curtains
Connecting your curtains and blinds to your mains power supply is very convenient. Installing hardwired motorised blinds or curtain tracks means you do not need to recharge batteries (although this is only required a couple of times a year and is very easy). You are also future proofing your home for new technologies and innovation’s.
I can coordinate with your architect, designers, contractors and electricians. Providing drawings and wiring diagrams when required. Ensuring the correct power supply is installed exactly where it needs to be so that the final installation is seamless.


The spinner is a very simple bot that simply charges up the capacity (the green squat cylinder in the image) via the solar panel, which then discharges through the motor when a certain voltage is reached. This is exactly the same circuit as the symet (with some adjustment of component values), but the bot is configured “standing on its head” so that the head spins around when the motor fires.
This was a fairly easy robot to build. One thing to be aware of is that when you have your circuit on the breadboard, running a motor with no load, the motor will spin for much longer than it does under load. I had to retrofit a larger timing capacitor on the Miller engine to have this guy spin for a reasonable amount of time on each charge. You can see the solar engine here:
The copper loops are actually large C-clips from some large (projector or copier) lens assemblies, hot-glued onto the motor body, and soldered to eachother.


If your microwave doesn't turn on, there is probably a really simple reason why. When it comes to taking care of your microwave, don't throw your microwave out. More than likely, all you need to do is fix a small part in order to get your microwave working again.
Damaged Ceramic Fuse
Your microwave has a ceramic fuse that is located inside the microwave, near the power cord. In order to access the ceramic fuse, you need to unplug your microwave and remove the back panel. The ceramic fuse controls the power to your microwave, and when the ceramic fuse isn't working right, your microwave will not power on.
To test and see if the issue is the ceramic fuse, you can use a multimeter to test the fuse and see if it is conducting energy or not. Your microwave may have a few different fuses that you are going to want to check out.
Damaged Thermal Fuse
Another type of fuse that your microwave has is a thermal fuse. A thermal cutout, or thermal fuse, is designed to keep your microwave from overheating. It helps keep your microwave from getting too hot and dangerous. The thermal fuse is located behind the cabinet. In order to test the thermal fuse, you need to disconnect the thermal fuse from the terminals inside of your microwave. Then you need to use a multimeter to test the thermal fuse for damage.
Check the Cooling Fan
When you are checking out the thermal fuse, you should also check the cooling fan. The cooling fan helps keep your microwave from overheating, and your microwave may not turn if the fan is not working correctly.
Inspect the Door Latch
If the door is not latching properly, then your microwave may not start up. Your door latch doesn't just open and close the door; when the door is closed, the latch engages a switch that lets the microwave know that power can be sent to the microwave. If the latch is damaged, which can happen from slamming or pulling the microwave open with force, your microwave may not turn on.
Have a microwave repair shop fix your microwave so that it turns on. More than likely, an easy fix will get your microwave operating again. No need to trash your microwave when all you need is one little part to get it working like new again for you.Share


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Brighter Viewer - LED Magnifier
About the product:
- The extra-large viewing screen rotates 360 degrees, so you can position it for the best angle for any job!
- It's free-standing, so your hands can focus on the details.
- There's even a built-in LED light for instant illumination!
- Perfect for all magnification needs.
- Color: White.
- Material: ABS.
- Size: 19.5*14.5*15cm.
- 1 x Brighter Viewer - LED Magnifier.
- Please allow 1-3cm measuring deviation due to manual measurement.
- Due to the different monitor and light effect, the actual color of the item might be slightly different from the color showed on the pictures.


Ezcap USB 2.0 ISDB-T Tuner Stick with Remote Control for PC SCXTV020
- Watch ISDB-T digital TV on your PC or laptop, in a window or full screen.
- Record ISDB-T digital TV to your PCs harddisk, Playback your TV recordings at any time onto your PC screen.
- USB ISDB-T receiver includes a portable antenna, so you can watch digital TV at home or while your travel.
- ISDB-T receiver for the best TV reception. And a small portable ISDB-T antenna for watching digital TV on-the-go.
- Record digital TV programs to disk, and play them back to your PC screen in full original digital quality.
- Plug and play, powered by USB port.Schedule play or recording.
- Auto channel scanning.Pause shows whenever you want.
1 × USB 2.0 ISDB-T Tuner Stick
1 × Set of Accessories


Here’s iOS file system / PIN encryption as I understand it. I originally pastebin’d this but folks thought it was worth keeping around. (Thanks to Andrey Belenko for his suggestions for edits).
Block 0 of the NAND is used as effaceable storage and a series of encryption “lockers” are stored on it. This is the portion that gets wiped when a device is erased, as this is the base of the key hierarchy. These lockers are encrypted with a hardware key that is derived from a unique hardware id fused into the secure space of the chip (secure enclave, on A7 and newer chipsets). Only the hardware AES routines have access to this key, and there is no known way to extract it without chip deconstruction.
One locker, named EMF!, stores the encryption key that makes the file system itself readable (that is, directory and file structure, but not the actual content). This key is entirely hardware dependent and is not entangled with the user passcode at all. Without the passcode, the directory and file structure is readable, including file sizes, timestamps, and so on. The only thing not included, as I said. Is the file content.
Another locker, called BAGI, contains an encryption key that encrypts what’s called the system keybag. The keybag contains a number of encryption “class keys” that ultimately protect files in the user file system; they’re locked and unlocked at different times, depending on user activity. This lets developers choose if files should get locked when the device is locked, or stay unlocked after they enter their PIN, and so on. Every file on the file system has its own random file key, and that key is encrypted with a class key from the keybag. The keybag keys are encrypted with a combination of the key in the BAGI locker and the user’s PIN. NOTE: The operating system partition is not encrypted with these keys, so it is readable without the user passcode
There’s another locker in the NAND (what Apple calls the class 4 key, and what we call the DKEY). The DKEY is not encrypted with the user PIN, and in previous versions of iOS (<8), was used as the foundation for encryption of any files that were not specifically protected with “data protection”. Most of the file system at the time used the Dkey instead of a class key, by design. Because the PIN wasn’t involved in the crypto (like it is with the class keys in the keybag), anyone with root level access (such as Apple) could easily open that Dkey locker, and therefore decrypt the vast majority of the file system that used it for encryption. The only files that were protected with the PIN up until iOS 8 were those with data protection explicitly enabled, which did not include a majority of Apple’s files storing personal data. In iOS 8, Apple finally pulled the rest of the file system out of the Dkey locker and now virtually the entire file system is using class keys from the keybag that *are* protected with the user’s PIN. The hardware-accelerated AES crypto functions allow for very fast encryption and decryption of the entire hard disk making this technologically possible since the 3GS, however for no valid reason whatsoever (other than design decisions), Apple decided not to properly encrypt the file system until iOS 8.


Applications of Soft Robotics
From re-growing broken limbs to creating extra strong muscles, everything that we once deemed to be impossible can come true with the advent of Soft Robotic technology. Since the first soft robots were invented in 2011, this field of technology has exploded with potential in almost every sector imaginable.
What are Soft Robots?
The field of soft robotics is the side of robotics that draws the most inspiration from nature. Unlike traditional robotics, soft robots work with highly malleable and compliant materials such as silicone elastomers and hydraulic fluidics. This allows soft robots to accomplish many humanoid tasks that were originally impossible through traditional robotics.
Some of the most promising areas of application for soft robotics include wearable soft robots, prosthetic limbs, and origami muscle robots. Each area traditionally focuses on biomimetics; however, once developed, these technologies have invaluable uses in many areas. Combined, these robots have the potential to bring about the next revolution in biomimetics and transform the way we live and function as human beings.
Wearable Soft Robots
One of the greatest challenges in robotics is providing muscular support such that we can mimic the human muscles. This can be invaluable to patients recovering from surgery or those with motor impairments. Current technology is limited in that it cannot recreate soft tissues or muscles. Previous attempts at providing muscular support used bulky motors or fluidic actuators which require external pumps, making them inaccessible to those that need it.
The soft robotic approach to this problem is perhaps the most viable in that it allows us to mimic the motion of these soft tissues and doesn’t require any bulky equipment or external compression. The soft robotic version essentially includes a stretchable pump and a McKibben actuator. The actuator is powered by an electrically driven fluid system, which makes it very lightweight without the need for any external help. The stretchable pump makes it possible for the whole device to mould itself around the tissue and provide maximum support.
Although the recent advances in this soft wearable technology are quite promising, these muscle supporting robots are far from being commercially available. However, there is much research currently underway, and this technology may become commercially available in the near future.
The idea of prosthetic limbs has been around for almost a decade and a half. This type of technology can be invaluable to those who have lost body parts due to accidents, or even to veterans injured at war. However, creating fully functioning replacement limbs is a task that is harder than it seems.
Current attempts at creating prosthetics largely use 3D Printing technology to design and print custom arms and legs for humans and even animals. This works great in terms of customization, however, these prosthetics are stiff and do not respond well to motion. Soft robotics makes it possible for us to create fully-functional body parts that can not only adjust to human motion but also mimic it. This is done through the use of highly flexible materials such as thermoplastic polyurethane (TPU). In order to mimic human motion, strong pneumatic actuation is used. The entire assembly is guided by a myriad of sensors placed on the apparatus, which tell the artificial parts what to do.
There are many prosthetic limbs and replacements available on the market today. However, true prosthesis is only possible through the use of soft robotics which is currently under development at many major research institutions.
As mentioned before, soft robotics takes much of its inspiration from nature. Many things in nature, such as proteins and enzymes, are in fact actuated through a complex folding motion. This type of actuation provides tremendous power which allows them to lift enormous weights and propel through the dense medium of human tissue. This is also exactly what origami robots aspire to do.
Fundamentally, origami robots are just plain sheets of metal or plastic that fold into certain shapes; allowing them to walk, throw, and even swim. Unlike naturally folding actuators, origami robots use micro pneumatic actuators which enable them to fold into these complex shapes. These shapes are then manipulated by the same actuators. It is this folding, unfolding, and re-folding motion that makes origami robots so powerful. What makes these robots so desirable is that they can fold into impossibly tight spaces and expand as required, all without losing the power of pneumatics.
Currently, all these robots can do is fold and roll around. They may not seem to be very useful today; however, once the technology has evolved, it can be an invaluable tool in many applications (including the prosthetics discussed above!).
Next Steps for Soft Robotics
The future of soft robotics is bright. There is much research going on in the sectors mentioned above and the applications for the technology are limitless. For example, origami robots can also be used as climbing robots for maintenance and inspection of buildings. In the future, the field of prosthetics is also projected to grow and be able to mimic animal motion along with the human motion. Accurate mimicry of animal motion can also cause major ripples in the automation industry. Wearable technology is also projected to be available not only to the injured but also to the general populace, giving us a boost in our day-to-day activities.
There is no doubt, however, that the sector most impacted by the advent of soft robotics will be biomimetic – the study of mimicking nature. Current technology in the field simply uses rigid bodies to create the illusion of natural movement, however, soft robotics enables us to experience the real deal. A great example of this is bird flight. It is well known that bird flight is the most efficient way of flying; however, gliders and “bird drones” really only create the illusion of bird flight using rigid bodies. True bird flight can only be possible with the evolution of soft robotics.
At the current pace of the field of soft robotics, we can expect to be able to move from illusion to reality very shortly.


As a motor for innovation, electrical engineering is of central importance for value-added networks worldwide. Diverse impulses and cross-industry development services have made the electrical industry the leading sector for digitisation – combined with a multitude of future technologies. The transformation of energy systems, which is now one of the most important issues in our society, also requires appropriate technologies and is presenting the electronics industry with new challenges.
Thanks to our extensive, heterogeneous range of electrical engineering expertise and innovative thinking, ep's particular strengths include
- Sensor technology
- Control units
ep provides fresh ideas for electrical engineering projects
As the driving force behind Industry 4.0, electrical engineering is playing a key role in the digital transformation. This applies, for example, to the connection between SmartHome technologies and the simulation of intelligent energy networks. Smart-home systems have a strong impact on the energy flows in smart grids. The goal here is not only to increase comfort in private homes, but also to regulate electricity consumption efficiently – for example via smart control of heating and lighting. Experts from ep facilitate transparent, cross-sector evaluations and development of electrical engineering solutions.
From our ep magazine
Perfectly designed valve technology:
With its electric, hydraulic and hybrid drive solutions, Moog Industrial in Böblingen ensures energy efficiency, higher productivity and lower operating costs for industry. Its product range includes servo and proportional directional control valves, two-way built-in servo valves and radial piston pumps as well as electro-hydraulic, electromechanical and electric hydrostatic drive systems, electric servomotors and servo controllers.
Our ep magazine provides an insight into the daily work of our ep employee at Moog Industrial in the field of valve technology.
link to article [German]
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The Simprint corporate office is open Monday through Friday from 8:00am to 5:00pm. (CST)
4545 Cambridge Rd. Fort Worth, Texas 76155
Office: +1 972.753.0200
Fax: +1 214.614.4613
The Web Handler in its simplest form provides a buffer loop between the printer and post-processor. Several options are available. The drive motor may be either AC powered or DC powered. In either the AC or DC versions, a web turner may be employed to invert the web.
An option to the basic version uses an AC torque motor to pull the web. The torque motor turns on when 6 ppi pulses are sent from the printer or when the Jog switch is pressed and turns off when the 6 ppi pulses stop or the Jog switch is released. No sensor tower is used with an AC drive motor. The AC motor is a torque motor that keeps the web under a slight tension and pulls as long as the printer is running. The motor torque is controlled by a transformer located in the electrical panel.
Some systems with high-speed printers and long web paths employ a larger (Hi-Torque) motor.
Web Inverter Option Either of the configurations above may include a frame with two additional diagonal bars and a vertical roller to invert the web.


Certainly! Let’s delve into the exciting world of web hosting trends. As technology evolves, web hosting remains at the forefront of innovation. Here are some of the latest trends that are shaping the future of web hosting:
Blockchain, known for its use in cryptocurrencies like Bitcoin, is an encrypted database system. It stores information in blocks, which are then linked together in a chain.
Web developers can leverage blockchain for secure and tamper-proof transactions across the internet, without the need for intermediaries.
Its potential extends beyond cryptocurrencies, as it can revolutionize various business sectors by enhancing cybersecurity and reducing risks of cybercrimes.
Progressive Web Apps (PWA):
PWAs combine the best of web and mobile app experiences. They load quickly, work offline, and provide a seamless user experience.
PWAs enhance engagement, especially on mobile devices, by offering features like push notifications and smooth performance.
Internet of Things (IoT):
IoT integration with web hosting allows devices to communicate and share data over the internet.
Web hosts are adapting to handle IoT traffic, ensuring scalability and security for connected devices.
Accelerated Mobile Pages (AMP):
AMPs optimize web pages for lightning-fast loading on mobile devices.
Google prioritizes AMPs in search results, making them essential for better visibility and user experience.
Voice Search Optimization:
Users increasingly rely on voice commands for searches. Web developers must optimize websites for voice-based queries.
Voice search impacts SEO and content strategy, emphasizing conversational and natural language patterns.
AI-driven chatbots enhance customer support and engagement.
They handle queries, provide personalized responses, and improve user satisfaction.
Content Personalization with Machine Learning:
Machine learning algorithms analyze user behavior to deliver personalized content.
Customized experiences lead to higher engagement and conversions.
Virtual Reality (VR):
VR integration in web hosting creates immersive experiences.
It’s used in e-commerce, real estate, and education sectors, allowing users to explore products and spaces virtually.
Serverless computing eliminates the need to manage servers.
Developers focus on code, and cloud providers handle infrastructure, improving scalability and cost-effectiveness.
Cloud hosting offers flexibility, scalability, and cost savings.
Web hosts adopt cloud infrastructure to meet varying demands and ensure high availability.
These trends are reshaping the web hosting landscape, providing opportunities for innovation and improved user experiences. Stay informed and embrace these advancements to stay ahead in the competitive digital world! 🚀🌐


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The Tech & Gadget world is at its rapid pace than ever before. It’s challenging to stay with the current trend in the fast-growing tech world. Well, We’re uniformly studying and researching new gadgets and regularly refresh this catalog with new releases and critic picks.
Whether you’re searching for perfect innovative home accessories or want to create a great sound system, this is the ideal place to begin. Here a complete list of the 10 Coolest gadgets you must try in 2021.
Apple Watch Series 6:
Apple Watch Series 6 is not only a fabulous health tracker but also a part of tech that can transform your life. Elements it’ll track like your sleep, heartbeat, and even blood oxygen saturation, which experts believe to be a great indicator of your overall health. If it detects any irregularities, it’ll recommend you to catch a doctor.
The electric toothbrush – Philips Sonicare Smart 9500:
Yes, it’s expensive, but if money does not matter, this electric toothbrush is for you. With five cleaning methods, the Philips Sonicare Smart 9500 is extremely customizable, and apart from the excellent clean, you’ll receive a battery life of 14 days.
The video doorbell – Nest Hello Video Doorbell:
The Google Nest Video Doorbell is the most beneficial thing you can grab right now. The experience is usually smooth from the Google offshoot, permitting you to handle alerts and fix pre-recorded communications with ease.
Vaonis Vespera smart telescope:
The Vaonis telescope will allow you to take their wondrous technology to observe deep-sky objects like nebulas and galaxies. The telescope grabs the images hitting its sensors and shares a live-view through WIFI to your smartphone or tablet.
Moorebot announced a robot that operates as an autonomous monitoring camera on wheels, powered by AI technology. Those giant Truck-looking tires provide it with the self-driving mobility service over fixed cameras. Rather than one of those “Beware of Dog” warnings, you’ll need one that states “Beware of Robot.”
JBL Tour Pro+ Earbuds:
Another year, another eight thousand repetitions of earbuds. This year at CES, it announced a new Tour line formed of these truly wireless earbuds and a combination of over-ear cans. The JBL buds are interesting because they promise advanced Noise Cancelling and much more.
LG Transparent OLED TV:
An OLED TV by LG for the bedroom with a transparent screen. According to The Verge, the screen size is 55 inches, and it can go upto 40 per cent transparent even when you are watching something on TV.
Cove comes up with the promise to reduce stress by wearing this head band-type device for 20 minutes a day. By light vibrations behind the ears, Cove reportedly activates the part of the brain that controls tension and reduces stress.
NowLight self-powered lamp:
The NowLight is a hand-cranked fast charger that, with a minute of pulling the connected chord, can charge your device within 15 minutes.
The gadget itself is about the weight and size of a little bag of sugar, and set up is easy. Just connect the chord and crank.
Otterbox Gaming Accessories:
Otterbox declared a 2021 gaming accessories line in partnership with Xbox. There is a grippy Xbox controller case so you can game securely and an Xbox controller shell to carry reliably. There’s also a claw to change mobile gaming with a controller in one conjoined ecosystem.
you can checkout our Top 10 affordable gadgets under 10K


The retail store has informed you that no documentation of the current network exists. There are numerous types of data communications that occur in a retail company, and the employees are willing to explain to you what information they work with and the steps that are involved to process the daily business transaction paperwork.
Assume that the retail store is currently using open systems interconnection (OSI) and transmission control protocol/Internet protocol (TCP/IP) in a dual-stacked environment. This has proven to be memory-intensive and has caused an inability for application internetworking to occur.Network Reference Model (OSI vs. TCP/IP) Comparison (4–5 pages)
The project deliverables for this week are as follows:
- Create a network reference model diagram of the current network that describes the role of each layer for both OSI and TCP/IP that are used to transmit data between the devices and applications specifically in your retail store.
- Create a revised network reference model diagram of the proposed network solution (using OSI or TCP/IP) that describes the hardware and software that are used to transmit data between the devices and applications in your retail stores.
- Based on the current dual-stacked network environment, create a data flow diagram for both OSI and TCP/IP that shows at least 4 typical network connections that are made by users in your retail store. Show how the data and information flow from the user workstation to the application using both the OSI and TCP/IP network models and the impact of encapsulation.
- Create a revised data flow diagram based on the proposed network solution that shows at least 4 typical network connections that are made by users in your retail store. Show how the data and information flow from the user workstation to the application using the chosen network model (using OSI or TCP/IP) and the impact of encapsulation.
- Provide an analysis as to how this part of the project fulfills the mission and 1 or more goals of the case study organization.
- Note: Use Microsoft Visio or equivalent to create the network reference model (current and revised) and data flow (current and revised) diagrams. You will embed the diagrams in the Word document and also provide them as attachments. See your Web resources for additional diagramming tools.
- All sources should be cited both in-text and in References using APA format.
- Name the document “yourname_IT640_IP2.doc”


Progetto strategico Legge 449/97
(Fondi 2000) Settore "Piattaforme ITC abilitanti, complesse, ad oggetti,
distribuite" finanziato dal MIUR.
The goal of the RoboCare project is to build a multi-agent system which generates
user services for human assistance. The system is to be implemented on a distributed
and heterogeneous platform, consisting of a hardware and software prototype.
MAVR is responsible of the unit of image processing. Its role is to build
a platform able to reconstruct 3D models of the scene viewed by the robots.
To the scope, MAVR will work on collections of range data, to transform them
into polygonal models.
In particular, the following themes will be developed inside the project:
Acquisition of range data.
Range data compression.
Multi-scale surface reconstruction in real-time.
Application of the color field to the 3D models.
First milestone (May 2003)
Second milestone (October 2003)
Borghese N.A., Maggioni M. and Ferrari S., (2003) Multi-Scale Approximation
with Hierarchical Radial Basis Functions Networks, IEEE Trans. Neural Networks,


|Birth||8 September 1962|
Sergei Tochitsky (born September 8, 1962) is a Belarussian research scientist at the University of California, Los Angeles.
Sergei Tochitsky was born in 1962 in Minsk, Belarus. He obtained both Master and Bachelor of Science degrees in optical engineering from the Byelorussian Polytechnic Academy in 1985 and in 1992 got a Ph.D. in laser physics from the National Academy of Sciences of Belarus. From 1993 to 1994 he was a postdoc at the National Tsing Hua University and in 1996 became a visiting professor at the Brookhaven National Laboratory. Since that year and until 1997 Sergei was the Royal Society guest researcher and worked at the Cavendish Laboratory of the University of Cambridge. Between 1998 and 2000 he was a postdoc at the University of California, Los Angeles where since 2000 he holds a research scientist position.
- 2017 – Elected Fellow, Optical Society of America
- 2018 – Fellow, the Optical Society


What if there was an easy way to connect the physical world around us with the digital world? What if we could connect the simplest of things to the Internet and garner invaluable data as a result? That’s what Sigfox sets out to do, to connect millions of sensors to one network that boasts resilience, efficiency and security. Founded in 2009 in France, Sigfox has swept across forty-five countries around the globe and covers close to one billion people with its industry-leading coverage. In Ireland, the Sigfox network is operated by VT IoT, connecting everything from our shopping trolleys to our smoke detectors.
VT IoT provides 97% outdoor population coverage with its IoT network in Ireland (86% indoor population coverage), an unparalleled footprint that Vodafone or other networks would only dream of having. The company is engaged in an infrastructure sharing agreement with RTÉ’s networking branch, 2RN, that has allowed it to roll out the Sigfox network in just a few short years without the need to invest hundreds of millions of euro like mobile networks are forced to do every time a new generation of networks is over the horizon.
Sigfox and VT IoT certainly aren’t unchallenged internationally or in Ireland, Vodafone has hastily launched its own network for the Internet of Things called Narrowband-IoT (NB-IoT), which features fundamentally different characteristics than Sigfox. It is clear that mobile networks such as Vodafone are being beaten in their own game. It must be disturbing for Vodafone to watch new competitors build out their own network at a fraction of the cost and hoover up customers. Hence the reason we see the network pushing NB-IoT throughout Europe. Vodafone and other telecom companies across Europe are finding it more difficult to produce a profit as prices continue to fall, and IoT appears to be a lucrative new revenue stream for them.
Sigfox aims to connect simple things with a simple network. Without question, this is the most important aspect to understanding the purpose of the Sigfox network in the first place. Why do simple things such as sensors that provide data about temperature require a traditional cellular network to communicate? It doesn’t make sense, especially with the battery technology available to us today. Traditional cellular networks, such as the ones that allow you to make a call or stream Netflix on your phone, are unsuitable for connecting the millions of sensors that will interact with the Internet. Cellular networks consume too much power, rely on a constant connection to a base station and are too expensive.
Low Cost Allows Us To Connect More Things
The benefits of good pricing stretch beyond this, Sigfox is a global network for the Internet of Things and this means there is a unified pricing structure across its network. Unlike with NB-IoT, which is operated by different networks in different countries, the cost of accessing the Sigfox network in different countries is much more transparent. This is a gigantic benefit for multinational companies that operate businesses such as shipping. For a better idea of this, look at your mobile phone which is similar to NB-IoT networks. When you travel abroad and roam on other networks, you never know exactly how much it will cost you to use your phone, but you know that the networks will punish you for your use with extra charges. Sigfox operates very differently, if you enter another country, you will be charged the price for accessing the Sigfox network in that country, and won’t be hit by any extra charges.
The cost-effective nature of Sigfox extends to the network provider, in Ireland’s case, VT IoT. As mentioned earlier, deploying and operating a Sigfox network requires significantly less capital and operating expenditure compared to traditional cellular networks. Virtually everything is less expensive, from the equipment required for base stations to the spectrum utilised for the Sigfox network. In fact, as Sigfox uses unlicensed spectrum (868-868.2MHz), VT IoT doesn’t have to pay a penny to Ireland’s telecom watchdog. Compare that to Vodafone, Three and Eir, all of whom collectively pay ComReg millions to obtain a license to use the spectrum for their mobile network. Likewise, NB-IoT uses expensive licensed spectrum, a major reason why networks such as Vodafone choose to pursue this technology.
The Internet of Things promises to connect everything and this is why a cost-effective method of connecting devices is vitally needed. The cost-effective nature of Sigfox means millions of sensors can be connected to the Internet, kickstarting the IoT Revolution. There is no other way to put it, an IoT Revolution will never happen if there isn’t a cost-effective method of connecting things to the Internet, at the moment, Sigfox is the best method.
Low Power Consumption is a Paramount
Sigfox is an extremely energy-efficient method of connecting our devices to the Internet. Tiny sensors are powered by tiny batteries, in many cases, replacing the battery every few weeks or months is just not possible. Sensors connected to the Sigfox network can last for years, the same cannot be said with devices communicating with today’s NB-IoT networks. Think about smart metres, do we want to have to change the battery after a few weeks?
The energy-efficiency associated with Sigfox comes as a direct result of the unique design of the network which is vastly different than traditional cellular networks. An important factor that contributes to the energy-efficiency of Sigfox is the lack of need for synchronisation messages between the sensor and base station. When a sensor on an NB-IoT network sends a message, it requires a synchronisation confirmation, thereby consuming more energy. Another reason for the low power consumption is the fact that sensors connected to the Sigfox network are idle for most of their lifetime, only activating when they need to send a message or receive a downlink message from a base station. Once again, this is in contrast to sensors that connect to an NB-IoT network, which consume more power in standby due to a constant connection to a cellular network.
The power consumption of sensors connected to an NB-IoT network increases as the strength of the signal decreases. This is similar to the phenomenon that causes your phone’s battery to drain quickly when you experience poor network signal, the device needs to work harder to maintain a connection to the nearest base station. The same isn’t an issue with a Sigfox sensor as the power consumption is the same regardless of the signal strength or quality. This makes it easier to predict power consumption on the Sigfox network, in contrast to NB-IoT where power consumption varies wildly depending on the signal conditions.
For an example of the startling difference in battery life between devices connected to an NB-IoT network and those connected to the Sigfox network, let’s look at a tracker which makes use of GPS and WiFi for geolocation. Vodafone provides a bag tracker, V-Bag, which claims a horrible battery life of up to four days and connects to their NB-IoT network. A similar tracker from a company called Invoxia can last for up to six months as it accesses the Sigfox network. The Invoxia tracker is also significantly less expensive over time, which would you buy?
Of course, as with any technology, it will improve with time. Without question, NB-IoT will become more energy-efficient over the coming years. But it is almost inconceivable that NB-IoT will ever become as power-efficient as Sigfox. This huge difference will dictate the use cases for the networks. For example, for sensors that can be operated using mains power, NB-IoT becomes more logical. However, for the majority of sensors, that is, the ones that use battery power, Sigfox will almost always be the best option.
Unparalleled Coverage, Capacity and Quality
The reason VT IoT is able to provide such a large coverage footprint with so little base stations is the physics of ultra-narrowband modulation which can travel over exceptionally long distances. Not only does the Sigfox network travel over long distances, it will provide excellent indoor and underground coverage with improved densification, important for applications such as smart metres which are typically located underground. Each message is 100 Hz wide, Sigfox uses 192KHz of the available band.
Sigfox provides an excellent quality of service because of the way it is intrinsically designed. A sensor will produce three messages, all identical, on three different frequencies and at three different times (time and frequency diversity). Another feature of Sigfox which ensures a high quality of service is called spatial diversity. This essentially means that when a sensor emits a message, it will be received by at least one base station, usually three. NB-IoT works like traditional cellular networks, connecting to one base station at a time. This same feature means Sigfox is resilient to signal jammers, whereas NB-IoT would be rendered unusable if a jammer were to be present. This opens up more opportunities for using Sigfox, for example, an alarm system.
The IoT revolution will entail millions and billions of devices connecting to one network. Such a large number of independent connections will require a huge amount of capacity, the capacity that would simply be unimaginable to expect from today’s cellular networks. The huge capacity offered by the Sigfox network is a result of the ultra-narrowband modulation which is extremely spectrum efficient as the energy is concentrated into a very small bandwidth (several bytes). Something else to take into account, with Sigfox, capacity is not hindered by the quality of the available signal. So, the capacity does not deteriorate as the signal quality worsens, something that is not seen with traditional cellular networks.
As I’ve mentioned already, Sigfox is a global network for the Internet of Things. This means roaming is seamless, as the device will automatically detect and broadcast in the correct band when moving between continents. In fact, there are just four bands with Sigfox compared to eighteen with NB-IoT. This adds unnecessary complexity and fragmentation to NB-IoT.
Versatility Allows For More Use Cases
Like pretty much any other technology out there, Sigfox also has its limitations and drawbacks. These shortfalls will determine whether or not using the technology is viable on a case by case basis. Features such as a very low bitrate make providing OTA software updates to Sigfox sensors almost impossible. This is where versatility plays a major role in enhancing the core technology. Most Sigfox sensors utilise more than one means of connecting to the Internet, such as Bluetooth, WiFi, NFC or even NB-IoT.
Take for example a Sigfox smoke detector. Let’s pretend there is a major flaw that requires a software update to quash the bug. What do you do? It would be ridiculous to assume that the update could be deployed quickly over the air using Sigfox. It would be equally ridiculous for the manufacturer to have to visit the buildings where the smoke detectors are installed and update them on-site. In this scenario, WiFi, Bluetooth or NB-IoT would be excellent options to deliver the update. They are technologies proven to cater for high-bandwidth applications such as software updates. When the smoke detector receives a message from a Sigfox base station to temporarily activate WiFi, Bluetooth or NB-IoT to allow the update to be carried out, it saves time and energy.
This same versatility also applies to other applications such as the aforementioned bag trackers. Everyone knows that GPS is a very precise method for geolocation, however, that precision collapses when we move indoors. So what happens then, we can’t track anything when it is under a roof? Of course not. Again, we can make use of WiFi to bolster Sigfox. The device can activate WiFi indoors and passively “sniff” the SSID’s which are available without ever having to connect to them. This data can then be compared with a database of recorded WiFi SSID’s and their unique location to determine where exactly the device is. It won’t be as accurate as GPS, but it’s surely better than nothing. Even the base stations that provide coverage feature a form of versatility. If there is no fixed backhaul, 3G or 4G may be utilised instead.
Conclusion: Unlocking the Potential of the IoT Revolution
Sigfox is a global network built for the Internet of Things, built to connect millions of devices to one network. It is vastly different from traditional cellular networks, and that’s where its biggest advantages come from. As we connect more and more devices to the Internet, we will need a network that is able to meet the demands of all these devices. Whether the telecom juggernauts would like to admit it or not, Sigfox is a promising technology, a technology with the power to change the world.
By no means is this a puff piece about Sigfox, it serves a purpose to illustrate that there is a brighter future ahead of us when everything is connected to the Internet of Things, Sigfox is just one method of fulfilling this future. There will be cases where using Sigfox is simply not feasible, the features will determine the applications of the technology. Likewise, NB-IoT is an equally promising technology with its own set of benefits and use cases which I intend to explain further in a later article.
With over 97% outdoor population coverage on VT IoT’s network, Sigfox currently holds a major coverage advantage over any other IoT network in Ireland. That same advantage persists with cost and power consumption, both of which trump that of today’s NB-IoT networks. The global scale of the Sigfox network is a key benefit, along with the unparalleled coverage, capacity and quality that the network provides. The versatility and complementary nature of Sigfox allows the technology to cast a wider net over the number of applications.
The great news is that Sigfox and NB-IoT co-exist in Ireland, and both technologies push the IoT industry forward. Because at the end of the day, while these networks are similar in terms of their fundamental purpose, they were designed for different use cases.


AutoFEM Analysis is the finite element analysis software.
The main feature of the system is its deep integration with AutoCAD
Using AutoFEM Analysis, an AutoCAD user gets a possibility to solve the problem of finite-element modeling of various physical phenomena:
- Static analysis (analysis of structural stress and strain) - the AutoFEM Static Analysis module;
- Stress analysis for structures under cyclic loading action - the AutoFEM Fatigue Analysis module;
- Calculation of natural frequencies (resonances) of structures - the AutoFEM Frequency Analysis module;
- Calculation of critical load (the system's stability) - the AutoFEM Buckling Analysis module;
- Calculations of temperature (or distribution of temperature domains) - the AutoFEM Thermal Analysis module .
The general algorithm of working with AutoFEM Analysis is as follows:
First, the user should create a three-dimensional (3D) model of the product in the AutoCAD 3D environment.
Then, without leaving AutoCAD, the user should create the problem of finite element analysis, referred to as the “Study”.
The model is loaded into an AutoFEM Analysis pre-processor integrated into AutoCAD.
Using the pre-processor, the user specifies external and internal parameters of simulated physical phenomena (finite element mesh, boundary conditions, materials, etc.) and transmits the “Study” to an AutoFEM Analysis processor.
The AutoFEM Analysis processor creates and solves systems of algebraic equations in accordance with the finite element method. With the help of an AutoFEM Analysis post-processor, the user performs analysis of results and develops the accompanying documents, i.e. reports, video, avi, etc.
Users of AutoCAD become able to perform the finite element analysis in the usual and familiar software environment.
There is the FREE finite element analysis software - AutoFEM Analysis Lite - which is available for use to each user of AutoCAD 2007-2010.
Theoretical background of AutoFEM Analysis
AutoFEM Analysis – is the finite element analysis software, based on the finite element method.
The Finite element method (FEM) is the leading way of predicting the behavior of structures under real-life conditions.
The general principle of the finite element method is as follows.
The design, which is, generally speaking, a system with an infinite number of degrees of freedom, is divided into a finite number of elementary volumes, or the so-called finite elements. Since the form of the finite element is known in advance (bar, beam, triangle, wedge, prism, etc.), it is possible to write down the relations that establish a mathematical relationship between variations of a physical quantity within single element.
For example, in the problem of static stress analysis, the dependence of a geometric shape of the finite element (strain) is determined for the element influenced by external forces. The geometric shape of the finite element is defined by spatial coordinates of points on its boundaries that are called nodes. Application of forces to finite elements causes a shift of nodes (the strain). This shift can be expressed in the form of algebraic equations. In case of thermal analysis, regularities of temperature distribution in terms of finite elements are determined.
For each finite element, the system of algebraic equations is constructed as a mathematical formulation of the physical problem. For instance, for the problem related to static strength, the system of equations can be written in a matrix form:
[Kel] * [Xel] = [Pel], where
[Kel] - means the stiffness matrix of finite element
[Pel] - means the vector of forces applied to the finite element; and
[Xel] - means - an unknown vector of displacement at topical points of the finite element, called nodes. It is this vector which is to be determined.
In the first version AutoFEM Analysis as a finite element used tetrahedron. Tetrahedron can approximate arbitrarily complex geometry of the simulated real object. A special generator of finite element mesh creates a tetrahedral finite element mesh for three-dimensional solid model of a product, made in AutoCAD.
After building the finite element mesh and the computation of local stiffness matrices of each finite element it is possible to algebraically and topologically sum up all the local stiffness matrix elements and to construct the global stiffness matrix of the assembly. The result (for example, stress static analysis) is a system of equations of the form
[KGl] * [XGL] = [PGl], where
[KGl] - global stiffness matrix of construction.
[PGl] - the global vector of external forces.
[XG] - to be determined the vector of unknown nodal displacements.
Processor of AutoFEM Analysis performs the generation of the global stiffness matrix and solution of algebraic equations. There are some methods for solving algebraic equations. One of the most famous and used is Gauss method (or its modifications such as Cholesky method). These methods usually are called as Direct methods of algebraic equations solving. The second big group of linear algebra methods for solving algebraic equations is Iterative methods of algebraic equations solving such as Conjugate gradient method.
Processor of AutoFEM Analysis uses both of these groups methods for solvinglinear and non-linear algebraic equations which are considered in finite element modeling.
After solving the equations at each node of the finite element mesh is known displacement and stress (for statics), or other physical quantities such as temperature for the thermal analysis. These data are transmitted into Postprocessor of AutoFEM Analysis, which has been fully integrated into the interface of AutoCAD.
The theory of finite element method is described in many books and articles. It is not easy to recommend any of them, because there quantities is about hundred of thousands. Possibly one of the most famous author about FEM theme is O.C. Zienkiewicz. His books have been translated into all European languages. For example, one of the last edition of his book is Zienkiewicz O.C., Taylor R.L. Vol. 1-3. The finite element method. (2000)(T).
AutoFEM Analysis uses various finite element algorithms which are described in scientific articles and special books on FEA and FEM thematic.


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Narendra Singh Negi's career, spanning 29 years, is a testament to his extensive expertise in product innovation, design, and development. As the Head of R&D at V-Guard Industries Ltd. since June 2016, his visionary leadership has made a lasting impact. He began his journey at Luminous Power Technologies Pvt. Ltd., a Schneider Electric Group Company, where he dedicated 7 productive years, followed by 8 years at Su-Kam Power Systems Ltd., Gurgaon. Negi's notable accomplishments include seven Indian patents in Power Backup Solutions, along with one in IoT for the United States. His innovative contributions encompass DSP-based sine wave inverters, online UPS, and smart products with advanced IoT capabilities. Focusing on resilience, frugal innovation, and R&D transformation, he remains an idea generator, driving futuristic product development and smart IoT solutions.
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Unlock the potential of AI-powered image detection! Explore its applications in biology, medicine, and environmental sciences. Learn how it accelerates research, aids early disease diagnosis, and enhances safety in autonomous vehicles. Discover the transformative impact of AI image recognition beyond academia.
The usefulness of AI-generated image detection extends far beyond the academic world. Artificial intelligence (AI)-powered picture recognition is increasingly important in various academic disciplines, including biology, medicine, and the environmental sciences. By automating the analysis of large datasets, we can learn more about complex phenomena quickly. Using AI-driven image detection to diagnose diseases early improves patient outcomes while reducing healthcare providers' workloads. Autonomous vehicles can better detect and avoid hazards in real-time with this technology.
Image detection aids in crime prevention and public safety because of its applications in surveillance and security. In the creative industry, AI-generated picture detection can speed up content regulation and provide safety from harmful or inappropriate content. Artificial intelligence-generated image identification has numerous expanding applications, including research, security, and efficiency.
While artificial intelligence-generated picture identification systems have made great strides in various academic and commercial applications, they still face several challenges. The lack of transparency and interpretability in AI algorithms is a big issue in the academic community since it hinders researchers' ability to comprehend how these systems arrive at their conclusions. Due to the importance of trust and understanding in research, this lack of transparency may encourage researchers to use these methods. These algorithms can be unfair because they take on the biases of their training data, making issues of fairness and objectivity more difficult to address.
False positives and negatives can have serious consequences in some fields, such as medicine, where incorrect diagnosis based on AI-generated image analysis could have devastating effects. In addition to the already significant data privacy concerns, using personal photographs poses safety and consent considerations.
This field is rapidly evolving because we must always adapt to new developments and update our artificial intelligence (AI) detection technologies to account for emerging threats. Weighing these challenges against the immense promise of AI-generated picture identification tools is a continuous and critical task for academic institutions and other sectors of society. So, there is a need to compare different AI image detection tools to get the best tool to be used in the market. This guide was created by Originality to address the issue, "What artificial intelligence content detector is the most accurate?" We also propose an open-source tool to promote transparency and accountability in all AI content detectors, and we provide a standard for evaluating the performance of AI picture detectors.
Following are the contributions by which research goals can be achieved.
Conducting a comparative analysis using state-of the art evaluation parameters which are commonly used to check performance of AI image detection models.
Providing detailed instructions and including the calculation in the tool to help identify the most important AI vs Original Human classifier efficacy metrics.
Certainly, the following is a collection of research questions in AI-generated image identification technologies for a variety of contexts:
What privacy and ethical concerns must be considered when creating AI image-detecting tools?
Identifying and avoiding cyberbullying and harassment based on images: how might artificial intelligence help?
In the context of national security and disinformation, how can deepfakes be detected?
How can artificial intelligence image detection tools be improved for quality assurance and manufacturing inspection?
What methods work best to detect improper content in user-generated photographs and films uploaded to online platforms?
How might artificial intelligence (AI)-based image identification be used to improve accessibility for people with visual impairments?
Forensic picture analysis and evidence processing are two areas where artificial intelligence (AI) could greatly aid law enforcement.
How can we ensure that AI image detection algorithms are fair and free of bias?
The primary goal of this article is to verify and validate the results acquired by the tools presented in this part by testing them on a self-developed dataset that is freely available to all academics. First, a collection of photos has been assembled. The tools were then conducted a series of manual tests using their web interface.
The database consists of 110 pictures created by the DALLE-3 AI model and 100 pictures captured by humans. These photographs are perfect for research because they depict a wide range of subjects. The database's particular complexity stems from the wide range of image sizes that it contains. Human-recorded photographs offer a genuine glimpse into the world, while DALLE-3's AI-generated images showcase the potential of generative AI to produce novel visual content. Having both types of images in the same database provides a rare opportunity to study the disparities between human and artificial creativity and the challenges given by images of varying dimensions in image processing and analysis.
Tools used for Comparison.
AI or Not
AI or Not's API and documentation explain mass photo analysis integration into many platforms. The tool supports JPEG and PNG, but unsupported formats must be converted. Upload or link an image to analyze. AI or Not offers premium API services for bulk image analysis and commercial applications with API documentation detailing price and usage. Single-image analysis is free.
AI or Not recognizes AI-generated content using advanced image analysis and machine learning. The program properly detects content origin by comparing input photos to AI models and human-made visual patterns, artifacts, and characteristics. AI or Not is a web-based tool that rapidly and accurately separates AI-generated photographs from human-generated ones. It even names the AI model—mid-journey, stable diffusion, or DALL-E.
Advanced AI image-detecting tool Illuminarty leads to image analysis technology. Its main goal is to illuminate digital imagery's complexities and determine its authenticity, integrity, and provenance. Illuminarty uses advanced machine-learning techniques to detect image alteration, forgeries, and AI-generated material. Its comprehensive capabilities enable image assessment transparency and accuracy by detecting AI-generated features.
Illuminarty can also evaluate photos of multiple formats, giving it a versatile option for many applications. Illuminarty is a reliable resource for verifying digital photos' validity for legal, journalistic, or scholarly purposes. Professionals and people use its straightforward interface and fast analysis to maintain digital media integrity in an era where image authenticity is crucial.
May Be AI Art Detector (Hugging Face)
To demonstrate how effective a Vision Transformer (ViT) model may be in determining whether or not an artistic image has been made using AI Maybe has developed a proof-of-concept application called AI Art Detector. The goal of this tool, which uses cutting-edge AI technology, is to recognize and differentiate between human-generated and AI-generated art, shedding light on the dynamic junction of creativity and automation in the art world. It is an exploratory effort that adds to the current dialogue between AI researchers and artists about the utility of machine learning for categorizing artistic works.
Effective and ethical machine learning and deep learning model evaluation policies are essential to their advancement. This comprehensive strategy contains several crucial features. First, select task assessment metrics like classification, regression, natural language processing, or computer vision. In addition, the policy should address robust cross-validation, dataset splitting, and imbalanced data handling. Fairness, transparency, and prejudice reduction in appraisal are needed to avoid stereotypes and discrimination.
The policy should involve rigorous testing against real-world scenarios and user feedback loops to improve models and react to changing demands and challenges. A thorough review procedure is needed to ensure machine learning and deep learning models responsibly address complicated problems.
A confusion matrix is a crucial machine learning and statistics tool for assessing classification model performance. Tabulating true positive, true negative, false positive, and false negative numbers simplifies categorization task summaries. True positives and negatives are correctly predicted outcomes. A false positive or false negative occurs when the model predicts a good outcome when it should have predicted a negative outcome. Data scientists and machine learning practitioners need this matrix to evaluate accuracy, precision, recall, and other parameters to improve model performance and predictiveness.
Accuracy is important in machine learning and statistics because it measures model prediction. Accuracy is a percentage of accurately predicted cases to the dataset's total occurrences. The term "accuracy" could mean:
In this formula, the "Total Number of Predictions" represents the size of the dataset, while the "Number of Correct Predictions" is the number of predictions made by the model that corresponds to the actual values. A quick and dirty metric to gauge a model's efficacy is accuracy, but when one class greatly outnumbers the other in unbalanced datasets, this may produce misleading results.
Precision is the degree to which a model correctly predicts the outcome. In the areas of statistics and machine learning, it is a common metric. The number of correct positive forecasts equals the ratio of true positive predictions to all positive predictions. The accuracy equation can be described as follows:
The avoidance of false positives and negatives in practical use is what precision quantifies. A high accuracy score indicates that when the model predicts a positive outcome, it is more likely to be true, which is especially important in applications where false positives could have major consequences, such as medical diagnosis or fraud detection.
Recall (true positive rate or sensitivity) is an important performance metric in machine learning and classification applications. It measures a model's ability to discover and label every instance of interest in a given dataset. To recall information, follow this formula:
In this formula, TP represents the total number of true positives, whereas FN represents the total number of false negatives. Medical diagnosis and fraud detection are two examples of areas where missing a positive instance can have serious effects; applications with a high recall, which indicates the model effectively catches a large proportion of the true positive cases, could profit greatly from such a model.
The F1 score is a popular metric in machine learning that combines precision and recall into a single value, offering a fairer evaluation of a model's efficacy, especially when working with unbalanced datasets. The formula for its determination is as follows:
Significance of parameters
Precision is the proportion of correct predictions relative to the total number of correct predictions made by the model, whereas recall measures the same proportion relative to the number of genuine positive cases in the dataset. The F1 score excels when a compromise between reducing false positives and false negatives is required, such as medical diagnosis, information retrieval, and anomaly detection. By factoring in precision and recall, F1 is a well-rounded measure of a classification model's efficacy.
A machine learning classification model's accuracy can be evaluated using the ROC curve and the Confusion Matrix. The ROC curve compares the True Positive Rate (Sensitivity) to the False Positive Rate (1-Specificity) at different cutoffs to understand a model's discriminatory ability. The Confusion Matrix provides a more detailed assessment of model accuracy, precision, recall, and F1-score, which meticulously tabulates model predictions into True Positives, True Negatives, False Positives, and False Negatives. Data scientists and analysts can use these tools to learn everything they need to know about model performance, threshold selection, and striking a balance between sensitivity and specificity in classification jobs.
Results and Discussions
The results and discussion surrounding these tools reveal intriguing insights into the usefulness and feasibility of three AI image detection approaches for differentiating AI-generated images from human-captured images. Detection technologies, including Ai or Not, Illuminarty, and Maybe AI Art Detector were ranked based on several factors, including accuracy, precision, recall, and f1-score. Table 2 compares different AI image detection approaches that can be used to tell the difference between AI-generated and captured images.
Table 2 shows how well different AI picture detection tools did on a test set of images. The tools are judged on how well they can tell the difference between pictures made by AI and those taken by humans. The results of Ai or Not are great; it gets a high precision, recall, and F1 score of 97 for both AI-generated and human-captured pictures. Another tool, Illuminarty, does well with pictures taken by humans (with scores of 66 for precision, 79 for recall, and 72 for F1) but could be better with images made by AI. It's worse at everything, but the MayBe AI Art Detector has a very low recall for AI-generated pictures, meaning it misses many of them. These results show what these AI picture detection tools do well and could be better when it comes to telling the difference between images made by AI and images taken by humans.
There is a comparison of how well three AI picture detection tools did on a test dataset in Figure 4. Some of the tools are "AI or Not," "Illuminarty," and "Maybe AI Art Detector." The heights of these bars show how accurate each one is. This comparison showed that "AI or Not" was the most correct tool, scoring 97.14%. "Illuminarty" came in second with a score of 70.95%, and "Maybe AI Art Detector" came in third with a score of 53.81%. Based on how well each tool finds images, this graph makes it easy to see which one is the most accurate.
Figure 5 shows confusion matrices that can be used to test how well pictures created by AI and images taken by humans can be distinguished. These grids make it easy to see how well different technologies can tell the difference between images made by AI and images taken by humans. The blue color used in these grids makes them clearer. The real labels are shown in the rows of the matrix, and the predicted labels are shown in the columns. In the matrix, each cell shows the number of instances that fit that category.
These matrices are useful for checking how well different text detection methods work generally, how accurate they are, and how well they remember images. This visual guide is very helpful for people using, researching, or making decisions who want to judge and compare how well different AI image detection technologies work.
Figure 6 displays the Testing Receiver Operating Curves (ROCs) for selecting AI image detection tools, visually comparing their relative strengths and weaknesses. These ROC curves, one for each tool, are essential for judging how well they can tell the difference between AI-generated and human-captured images. Values for "AI or Not," "Illuminarty," and "Maybe AI Art Detector" in terms of Area Under the Curve (AUC) are 0.97, 0.71, and 0.56, respectively. The Area under the curve (AUC) is a crucial parameter for gauging the precision and efficiency of such programs. A bigger area under the curve (AUC) suggests that the two text types can be distinguished with more accuracy. To help users, researchers, and decision-makers choose the best AI text recognition tool for their needs, Figure 6 provides a visual summary of how these tools rank regarding their discriminative strength.
This study tests how well three AI picture detection tools can tell the difference between images made by AI and images taken by humans. Different measures, like accuracy, precision, memory, and F1 score, were used to judge AI or Not, Illuminarty, and Maybe AI Art Detector tools.
Table 2 shows the results. It shows that AI or Not got high scores (97) for both AI-generated pictures and images taken by humans. Illuminating did a good job with pictures taken by humans, but it could do a better job of finding images made by AI. The MayBe AI Art Detector had a low recall for images made by AI, which means it missed a lot of them.
Figure 4 shows a visual comparison of how accurate the tools are. With a score of 97.14%, Ai or Not comes out on top.
Figure 5 shows confusion matrices that can be used to rate the tools, and Figure 6 shows Receiver Operating Curves that show what they can do. This study helps users, researchers, and decision-makers choose the best AI picture detection tool for their needs by focusing on how well it can tell the difference between images created by AI and images taken by humans. Notably, Originality.ai does not have an AI picture detector right now.
Founder / CEO of Originality.AI I have been involved in the SEO and Content Marketing world for over a decade. My career started with a portfolio of content sites, recently I sold 2 content marketing agencies and I am the Co-Founder of MotionInvest.com, the leading place to buy and sell content websites. Through these experiences I understand what web publishers need when it comes to verifying content is original. I am not For or Against AI content, I think it has a place in everyones content strategy. However, I believe you as the publisher should be the one making the decision on when to use AI content. Our Originality checking tool has been built with serious web publishers in mind!


Harvard Computer Science Technical Reports
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Last update: June 25, 2010 2:53:35 pm.