Components that are considered as “Passive” means that they do not rely on power and such component are the resistor, capacitor, and inductors. There’s more other type of passive components but the focus of this discussion is all about resistors.
Circuit designing is a complicated task where you are puzzled on defining the right value of resistors that are to be used.
Resistors are available on the market with a cheap price and there are thousand of them with different characteristics and specification.
The function of a resistor on the circuit is to provide resistance where it limits the flow of electrons depending on the specification of the component. For this reason, it can be used through different applications. Other than its ability to provide resistance, it is can also limit the flow of current, adjust voltage levels and etc…
The following are the properties of resistors: Tolerance, voltage rating, power rating, temperature rating, frequency response, and temperature coefficient.
Let’s explain the properties of a resistor one at a time starting from the tolerance. This is the value of the resistor or the range on where it can vary. The common parameters are 1%, 5% and 10%. You may find that there are other resistors that their tolerance falls below the one percent value and they are categorized as Precision type of resistors.
The voltage rating of a certain circuit can be safely adjusted or drop through the application of a resistance. Power rating is simply the amount of power consumed by the resistor. It is highly suggested to use a resistor with a power rating value over than what is exactly required.
Temperature rating is the range of the device where it can operates normally. Exceeding the limit will cause the resistor to be damaged or burnt. Finally, the frequency response is simply the change in impedance. The changes on the value of impedance depend on the function of the circuit.
Buying a resistor on the market will require you to provide them the exact amount of value as discussed on the previous paragraphs. However, before even trying to purchase them you need to make sure that they are particularly needed on your project.
Summary of the Characteristics of Resistors
Here are the following list of basic characteristics of resistors;
3. Temperature Coefficient


The Evolis Zenius ID card system features quick print speeds, small batch printing with a 50 card hopper, and Mac and Linux compatibility.
This Evolis Zenius ID card system comes with everything you need to set up an ID card program:
- Single-sided Evolis Zenius printer
- AlphaCard ID Suite Light software
- Blank cards - pack of 500
- YMCKO printer ribbon - print yield 200
- Logitech C270 digital ID camera
- Printer power cord & USB cord
User-friendly ID Card Printing
Evolis is redefining entry level printers with Zenius. This innovative printer is light, quick and quiet, making it ideal for printing cards on location. With the option to upgrade to magnetic stripe encoding, Zenius is an all-in-one solution to creating multifunctional identification cards, transit passes and more.
Zenius boasts an ingenious design that makes card printing and printer upkeep exceptionally simple. It features a manual card feed for one-off printing, and it is also equipped with a 50-card feeder and 20-card output tray to streamline batch printing. Cards enter and exit from the front, so this small printer offers easy access even when placed in cramped corners.
In addition to ease of use, Zenius offers high quality card printing. This single-sided printer creates color-dye sublimination color cards or thermal transfer monochrome cards with 300 dpi, edge to edge printing. Zenius features a built-in microchip that automatically detects Evolis High Trust ribbon cassettes. Especially easy to install, these ribbons enhance print quality and support print head durability.
Evolis Zenius Features
- Single-sided dye sublimation printing
- 30 seconds per side for full color cards
- 50 card input hopper, 20 card output hopper
- 2 year manufacture warranty
AlphaCard ID Suite Software
Your Evolis Zenius ID card system also includes powerful AlphaCard ID Suite card design and database management software. This user-friendly software makes it easy to design custom cards, build your database, and manage cardholder information with just a few clicks.
AlphaCard ID Suite Light edition gives you access to basic card design features including text, graphics, cardholder photos, and barcodes. The built-in database can hold up to 200 records, so your cardholder information is always available.


November 18, 2013
NASA’s Mars Atmosphere and Volatile Evolution (MAVEN) mission began with a smooth countdown and flawless launch from Cape Canaveral Air Force Station’s Space Launch Complex 41. The United Launch Alliance Atlas V rocket carrying the 5,400-pound spacecraft lifted off at 1:28 p.m. EST, the mission’s first opportunity. MAVEN’s solar arrays deployed and are producing power.
“We’re currently about 14,000 miles away from Earth and heading out to the Red Planet right now,” said MAVEN Project Manager David Mitchell of NASA’s Goddard Space Flight Center.


Welcome to the Skelton research group website
We are a theory group based in the School of Chemistry at the University of Manchester, UK.
We use a wide variety of theoretical modelling techniques to study materials ranging from inorganic semiconductors to molecular crystals and “hybrid” inorganic/organic systems.
We are particularly interested in the structural dynamics of solids and their effect on material properties. Our work in this area includes understanding the fundamentals of heat transport, devising new engineering strategies to control it, and predicting the structural, mechanical and electrical properties of materials at elevated temperature. We have a long-standing interest in improving materials for energy applications, including thermoelectric power generation and, more recently, photovoltaics and battery materials.
Our work applies and extends established theories to address new problems, with strong focus on making useful methods available to the community through open-source software and on strengthening links between theory and experiment. We regularly work with experimental groups to validate theoretical models and to help get the best insight from measurements.
More information about current research projects and the team behind them can be found on the Research and People pages. We also have a list of the group Publications and the open-source Software we maintain.


Installation: These LED Night light has a self-adhesive back to connect to any flat surface. No wiring or drilling is required which makes it very easy to use anywhere you want.
Brightness: Each light holds 4 Super Bright LED Night Bulbs
Power Supply: 3AAA Batteries (NOT INCLUDED). It can be used as emergency light too. You just need to touch the LED light to turn it on.
Changing Batteries: If you want to change the batteries after sticking your LED night bulb to a flat surface, you can very easily twist it and take it off and the adhesive tape will stay on the surface and you’ll get the lightning part where you can change the batteries very easily so battery replacement will not risk losing the adhesive tape.
|1.5MM THIN FILM CUTTER HEAD||Suitable for making fruit skin thin film, homemade thin-film mask.|
|3MM MEDIUM SILK CUTTER||Uniform thickness, The cut food is suitable for coloring or frying.|
|4MM THICK KNIFE HEAD||Uniform silk is more delicious, suitable for stir-frying or steaming.|
|GRATED KNIFE HEAD||Grated ginger grated without chopping, easy and labor-saving.|
|2.5MM THICK KNIFE HEAD||Easy to slice, save time and labor a good helper.|
|2MM CUTTING KNIFE HEAD||Dense and delicate, suitable for coleslaw.|
|SLICING KNIFE||Make delicious potato chips at home with ease.|


Year 6 have been programming physical systems. They have explored programming an emulator of CodeBug and then the real external device itself.
Below are images of the CodeBug Emulator and CodeBug External Device
CodeBug provides a fun and engaging way to build interactive devices. It is the perfect starting point to the world of electronics and computing.
They first programmed a scrolling name badge, followed by a sequence of animated pictures and then used Code Bug to investigate which objects conducted heat. Here are some screen shots of their programming.
Here are a few more examples of pupils work.
Here is a clip showing an example of an animated sequence.


Well I could visualize 3 element here:
1. Bigger processor and RAM
2. Bigger battery capacity
3. Bigger Screen
These factors are important to let us experience better on our new phone.
Bigger Processor and RAM (Memory)
For me, this the most crucial for us the run multiple applications at the same time. If you a mobile gamers, this is even more important to run the 2k/4k display continously ( off course the Nvidia video processor is much better ). Running so many apps simultanously with lagging is the requirement to have such a bigger processor and RAM . Let say 2.4Ghz Octacore with 8gb RAM is the minimum requirement for todays smartphone?
Bigger battery capacity
Most of the smartphones come with range of 4000mAH to 4500mAH battery. Though it seems big enough , but it is actually not enough to run bigger processing on smartphone, like playing games, watching 4K/8K video, taking 4k/8K videos, or even video editing.
I would say the minimum battery requirement should be at least 5500 mAH. Then we would not have headache to find huge power bank capacity due to frequent battery drain on our smartphone.
I do believe today smartphone is not only for phone call or video calls or even video chat, but it is already beyond boundary. We now edit document with smartphone, video editing with smartphone, access cloud server via smartphone, and start to getting everything via smartphone. So, how is the screen we need to perform all this task? With 6 to 6.5 inch diagonal screen size, I would say it is balance between acceptably holding the smartphone and clearly working on the job assignment. bigger than that wont be called as smartphone anymore and smaller than that is quiet difficult to view the job on the screen
Well I do not opt for design but we still look into stylish smartphone rather than a bulky boxy one. But for me, the above two are the most important criteria.
This is very particular if you are a vlogger or photographer or those like to show off their new smart phone ( with superb design ). Bigger camera capacity could optimize your video and photo shot quality aspecially for traveller.
At the end, it is up to you what smartphone is your best choice, I could say most of the users buy expensive smartphone but utilize less than 50% of smatphone capacity. Is it a waste? well it is up to you again.


A new complete vehicle intelligence system and health monitoring solution developed by an IIT-Delhi incubated startup for electric vehicles (EVs) can ensure safe and high EV performance, which will occupy a major part of the next-generation transportation system.
Delhi-based Vecmocon Technologies developed the vehicle intelligence system with critical battery data collection and monitoring, such as cell voltages, temperature, and the current health of the battery.
Vecmocon, incubated at FITT-IIT Delhi, with seed support from the Department of Science and Technology, also provides solutions for intelligent vehicles, including keyless entry, preventive and predictive maintenance, user-adaptive algorithms, remote diagnostics, fleet management, and so on, according to a Science and Technology Ministry release.
The system can help in estimating the accurate state of health and state of charge of the battery pack, and also assist fleet operators in their control and facilitate seamless communication.
The unavailability of such vehicle intelligent modules for the different components of EVs serves as a roadblock in their efficiency.
The system can cater to the entire ecosystem of EVs, such as motor power controllers, battery management systems, vehicle intelligence modules, cloud connectivity, etc., with specialised components for high-performance vehicles.
The patented technology at Technology Readiness Level 9 costs around Rs 20,000 to Rs 22,000 for the entire kit (Battery Management System - Rs 4,000 to Rs 5,000 , vehicle Intelligence Module - Rs 6,000 to Rs 8,000, fast chargers - Rs 4,000 to Rs 5,000, instrument cluster - Rs 2,000 to Rs 3,000, motor controller - Rs 4,000 to Rs 5,000) and is being used by more than 15 EV manufacturers as well as Original Equipment Manufacturers (OEMs).
“While others are focused on two-wheelers, three-wheelers as a product in the market, we at Vecmocon are building the ecosystem for electric vehicles to happen in India at a very faster pace," said Peeyush Asati, one of the founders of the company.
"We design and develop core components for electric vehicles like Battery Management System, Motor Controller, Vehicle Intelligence Module, Chargers, and the whole of the cloud architecture for Data Analysis, Machine Learning, and Artificial Intelligence,” Peeyush added.
Vecmocon provides battery packs with all thermal and structural considerations, battery management systems, and Machine Learning (ML) algorithms for battery management design of computationally in-expensive system-local ML algorithms, which run on Rs 100 micro-controller.
As you are no doubt aware, Swarajya is a media product that is directly dependent on support from its readers in the form of subscriptions. We do not have the muscle and backing of a large media conglomerate nor are we playing for the large advertisement sweep-stake.
Our business model is you and your subscription. And in challenging times like these, we need your support now more than ever.
We deliver over 10 - 15 high quality articles with expert insights and views. From 7AM in the morning to 10PM late night we operate to ensure you, the reader, get to see what is just right.
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Project Final Report
1 - Introduction and Background
Our project focuses primarily on the use of neural-network-based generative modeling for the rendering of realistic looking artwork.
Recent advancements in deep learning, largely a result of modern computing architectures, have led to the creation of models that can learn to generate realistic looking data. Models like Generative Adversarial Networks (GANs), which we utilize in this project, learn a mapping from a latent vector space that encodes the features necessary to generate data to synthetic data in the domain of an input dataset. GANs do this using a game theoretic approach of pitting two agents, a generator and a discriminator, against each other to help each other learn.
Other approaches like Variational Autoencoders attempt to construct generative models of data by attempting to compress data and learn a reconstruction of the data. Our project focuses on using both GANs and VAEs to learn representations of paintings that allow for the generation of synthetic paintings.
Further, we experiment with Style Transfer to generate interesting representations of existing images with new styles.
1.1 - Generative Adversarial Networks (GANs)
Generative Adversarial Networks (GANs) are a neural network architecture composed of two parts:
A Generator that attempts to map a latent vector space, pulled from a set of random distributions such as Gaussians, to the space in which data lives.
A Discriminator, which maps from a vector space of the data distribution to a binary classification of whether or not the data given to the network is real or counterfeit.
The purpose of this architecture is to learn a Generator that can create data that looks like it is from the distribution of real data. The Generator and Discriminator play a min-max game in which they make each other better over time. The Generator tries to outsmart the Discriminator and vice versa. These models are trained in an unsupervised manner using the above described min-max game optimization.
1.2 - Variational Autoencoders (VAEs)
A Variational Autoencoder (VAE) is a machine learning framework that takes a set of data and forms a compressed (latent) representation of data. An encoder function maps data from an input domain (i.e. images, sounds, etc.), to a lower-dimensional latent space that encodes the features necessary to reconstruct the original data.
Additionally, VAEs encode inputs to distributions over latent space, as opposed to individual points. The decoder function reverses the compression by reconstructing the original data from the latent representation. Typically these decoder and encoder functions are parameterized by neural networks, but it is a flexible framework that can be used with other methods. The VAEs are trained by jointly optimizing for reconstruction of the input data from the compressed representation, and having the latent space fit a predetermined prior distribution (typically Gaussian). This is done by jointly optimizing via gradient descent the reconstruction error (how well the input was reconstructed from a latent form), and a KL divergence term between the learned posterior distribution and a prior distribution.
This has the effect of both learning how to reconstruct input items, and also having the latent space have the shape of a Gaussian. In contrast to traditional Autoencoders, which don’t have the variational aspect, VAEs are capable of generating realistic looking data from latent space that did not exist in the initial training set. This is because when training, the encoder maps to the parameters of a distribution (i.e. mean and standard deviation in the Gaussian case), and that distribution is randomly sampled from. This sampled latent vector is then mapped out to the input space using the decoder. This causes the latent space of the VAE to be smoother, which is conducive to better representations.
Typical autoencoders are capable of memorizing training data, but are not as good at generating convincing looking data.
More formally, VAEs attempt to learn a probability function p(z|x), which maps input data x to a latent space z, as well as a function p(x|z), which does the opposite mapping from a latent space z to the input domain x. VAEs have two parts:
- They have an Encoder that maps data from an input domain x (such as images, songs, etc.) to a typically smaller vector, z, which encodes the parameters of a probability distribution, typically Gaussian (in this case mean and standard deviation)
- They have a Decoder that maps the compressed vector space z back to the input domain x using only the information from the vector.
The above figure shows the typical VAE architecture. Both the encoder and decoder are trained using a combination of two optimization functions. One of the constraints encourages the minimization of reconstruction error, which is loosely how the input x differs from its reconstructed counterpart x’. The second term is a KL divergence term that encourages the mapping p(z|x) that the encoder learns to fit the same probability distribution p(z), which is typically Gaussian. The variational component of VAEs encourages the learning of robust representations that fit the initial data distribution.
1.3 - Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are deep learning models that employ “convolutional” filters that scan across the domain of an input distribution to learn a desired output distribution. The key component of CNNs is the convolutional filter that moves across the X and Y spatial dimensions of images, computing a dot product at each location. These filters learn features that are equivariant (change independent) to translation. Images have many features, like eyes or ears in a face dataset, that can be present at any location in an image.
CNNs allow the sharing of parameters across different spatial dimensions of data thus lowering the size of the network necessary to learn certain patterns and avoiding all of the problems with having a larger network like slower convergence, overfitting, and slower training time. We employ convolutional layers in our GANs as well as VAEs to more easily learn representations of the image data.
1.4 - CycleGAN
We use a neural network architecture called CycleGAN that enables the learning of image to image translation. CycleGAN is largely based on an architecture called pix2pix that outlines what is called a conditional GAN. Typical GANs learn mapping from a latent vector z to the input distribution x. The novelty of pix2pix was the addition of conditioning the mapping z to x on an input image p. This takes into account additional information from an input image when rendering the output image x. This could be thought of as learning a mapping from p to x through the intermediate representation z that is learned in an adversarial fashion. CycleGAN builds on top of pix2pix by both learning the mapping p to x and x to p. This has been shown to lead to better representations and generated data. This architecture is useful for the application of image to image translation. We use CycleGAN to learn mappings between art data and regular images.
1.5 - Style Transfer
We employ style transfer to recompose the content of an image in the style of another. It takes two images—a content image and a style reference image—and blends them together so that the resulting output image retains the core elements of the content image, but appears to be “painted” in the style of the style reference image. This can be used to generate artistic versions of ordinary images, in the target style of an artist, such as creating a Van Gogh styled version of one’s own portrait. Using a pre-trained deep Convolutional Network, like VGG or SqueezeNet, we compute three loss functions - content loss, that describes how different the content of two images are, and style loss, that describes the difference between the two images in terms of their style, and total-variation regularization to encourage smoothness in the image. Then, using a style image and a content image, we try to transform the content image to minimize the content loss with the content image and style loss with the style image.
2 - Problem Description
We want to leverage novel machine learning methods to generate realistic looking and aesthetically pleasing art from a dataset of examples. We would also like to be able to render artwork that encompasses certain parameters of a painting like the year, artist, color content, and style. We want to employ the methods described in section 1 to learn generative models based on art datasets.
3 - Data Collection
We primarily used a Kaggle dataset of the Best Artworks of All Time . This dataset included mostly paintings from artists like Monet, Da Vinci, and Warhol. We prepared the data by fitting it to a 150x150 grid that shows the central part of the paintings. A secondary dataset that was used was the monet2photo dataset that shows mappings between monet paintings and photos of the scenes that those paintings depict. We also used the CMP Facade Dataset briefly, which included rectified images of facades from various sources and their source images.
4 - Methods and Results
Over the course of this project, we have conducted multiple experiments. First, we attempted to use both traditional autoencoders and variational autoencoders (VAEs) on just the images of the paintings from the monet2photo dataset.
Next, we trained basic GAN architectures on the Best Artworks of All Time  dataset. In another, we used the CycleGAN architecture to learn a mapping from Monet paintings to real life images depicting their scenes.
Lastly, we performed a neural style transfer experiment on the Best Artworks of All Time  dataset to create images based on the appearance and visual style of other images.
4.1 - Autoencoder Experiments
Traditional Autoencoders are similar to VAEs, except they do not learn to map a distribution over the latent space, but instead map directly to latent vectors. We trained an autoencoder over a dataset of Monet paintings.
We learn an encoding mapping from the input space to a latent vector. The values of the neurons at the center latent layer are constrained between 0 and 1 by a Sigmoid activation function. The trained decoder is used as a generative model. A set of latent variables generated randomly is taken as an input by the decoder and the output is the generated result – a fake Monet’s drawing. To train the model more effectively, we used convolutional layers as a part of the encoder and deconvolutional layers in the decoder. Convolutional layers help to learn translationally equivariant features (features that are the same no matter where in an image they are) in the input domain. Also, different sizes of the latent layer are experimented and dropout is used in training. In the following image, the first row are several images from the original dataset. The second row are the reconstructed images resulting from the decoder.
Although the reconstructed results match closely to the original drawing, the randomly generated drawing by this model deviates far away from the original data set – the following are the generated results by sending a set of random data to the trained decoder:
The cause of the deviation could be an uneven distribution of the learned latent space. In the autoencoder model, the neural network is trained solely to compress the data into a latent space. However, there are no constraints on the distribution of the trained latent space. There might be dimension in the latent space that is much less influential than that others. Also, the trained latent space is not necessarily smooth and continuous. Variational Autoencoders could be used to tackle this problem.
The following shows the corresponding results by using a variational autoencoder model. The reconstrued results are better than the previous trained models. Although the latent space now is smooth, the generated images are blurry and lacking details. On the one hand, data are compressed to a smaller space and details are lost. On the other hand, a detailed image might have a similar cost value as a blurry image. The blurriness is in fact a limitation of auto encoders as generative models. To enhance the quality and resolution of the generated drawing, the following section discusses adversarial generative models.
4.2 - Vanilla GAN experiment
We trained a GAN that uses sequences of convolutional layers to map from the latent vector z to the input distribution of images from the Best Artworks of All Time. This was a preliminary experiment that had the outputs outlined below.
The figure above shows what is commonly referred to as mode collapse. This is a typical problem with GANs as they generate images that have texture similar to the most common data in the training set, and not realistic looking images. In order to overcome the limitations of these traditional GANs we used a modified architecture known as CycleGAN.
4.3 - CycleGAN experiment
The second experiment we did was utilize the CycleGAN architecture outlined in section 1.4 to perform image to image mapping on images of monet paintings to lifelike images. The results for this are shown below.
These results show a decrease in the vibrancy of the original monet paintings (left) and the mapped paintings (right). This makes sense as we were trying to make images look more realistic. The real world is less vibrantly colored then Monet’s imagination.
Another experiment using pix2pix modeling using CycleGAN is shown below. Using the CMP Facade Database as our dataset, we attempted to train a mapping from images of buildings, to artistic renderings of their facades based on object detection. The left side shows fake images, rendered based on the ground truth images to the right.
4.4 - Style Transfer Experiments
For this experiment, we used a SqueezeNet model, since it’s less complex computationally (can be run on a CPU) compared to other pre-trained models. To generate our style transfer images, a few hyperparameters needed to be tweaked to stylize the content image to a desired level.
Our first set of hyperparameters were for the style and content layers. We selected intermediate layers of our CNN model to define the representation of content and style from our images. Intermediate layers represent feature maps that become increasingly higher-ordered as their depth increases. For an input image, we tried to match the corresponding style and content target representations at these intermediate layers. Layers (1, 4, 6, 7) were selected as style layers and layer (3) for content layer. Each of the style layers needed to be assigned a weight for computing the style loss. Higher style weights for initial convolutional layers yielded much better results, since these layers captured simple abstractions of images, such as, edges, color gradients etc., while later layers learned features such as more complex textures, objects and patterns.
The second set of hyperparameters contained Total Variation (TV) and content weights. These were for weighing content and total-variation losses for retaining a desired level of style-content mixture. Decreasing the weight for content loss applies a stronger style effect, and the content image starts to exhibit features of the style image more and more, such as color composition, edges/curves, etc. TV loss helps control the smoothness in the output image. Here, we have used tv_weight = 2 and content_weight = 0.03.
Equal weights (1, 1, 1, 1) for all style layers:
Higher weights (200000, 800, 12, 1) for initial style layers:
Having higher weights for initial layers generates a more stylized image, while assigning greater weights to later layers seems to affect characteristics of complex patterns captured by those layers. With these hyperparameters, we generate another composition using a different style and content image set.
5 - Discussion and Conclusion
This project explores many recent advancements in machine learning and generative modeling. It has many supervised and unsupervised components as our main machine learning framework: GANs apply supervised learning through its discriminator labeling real and fake generated images and the main architecture is applied to unsupervised learning problems like generating images as the input is unlabeled real data (images). Additionally, the Autoencoders and Variational Autoencoders are unsupervised learning methods as they learned representations of input images without labeled data. Neural Style Transfer also applies supervised learning as it builds off a pre-trained CNN.
We feel confident that our final results accomplished our outlined goals. We had successful results for the Autoencoder and Variational Autoencoder experiments as seen by the reconstructed images being smoother, but blurrier than their originals. Although we only had somewhat successful results with our Vanilla GAN experiments in generating images, we had great results in our CycleGAN experiments, achieving near photorealistic results from our inputs of Monet paintings and accurate object detection from input architecture images. We also feel pleased with the results from our work with style transfer, since with our approach, we were able to generate a variety of images that successfully transferred a style from a source image to a destination image.
Generative Modeling is an exciting and fast-growing field within machine learning and deep learning. The ability to generate realistic examples and images is applicable in many fields including art and computer vision. The various models explored in this project with GANs, CycleGANs, Autoencoders, Variational Autoencoders, and Neural Style Transfer not only gave us a better understanding on how they work and apply to generative modeling, but also produced amazing and aesthetically pleasing visual results. Our project gave us great insight in applying the classic machine learning concepts and fundamentals utilized in this course to modern advancements in this field.
- Goodfellow, Ian, et al. “Generative adversarial nets.” Advances in neural information processing systems. 2014.
- Outlines general GAN approach and gives theoretical background
- GANGogh: Creating Art with GANs. Introduction
- Describes a novel project similar to ours
Kaggle Dataset
- CMP Facade Database


Sometimes, money tells you what to buy. Samsung has provided various phone with various price.
2. Choose Operating System (OS)
Fact has shown that Android and iOS has become the primary OS in every smartphone. It is better if you made careful observation and research about all the OS in the market in terms of functionality and its capability.
You are advised to choose smartphone that has at least dual core processor. Research has shown dual core processor is better than single core in term of life expectancy.
Try holding the phone. It is the best way to feel it. If you are confident enough, try putting it in your pocket but make sure you did not walk out from the shop with the phone inside your pocket.I mean, don't steal it.
Most of the smartphone has large battery capacity but cannot hold longer because it is not suitable with the phone itself. The best way is to ask the sellers.
The best screen technology is from AMOLED or LCD. Take note with the screen resolution. Choose at least 800 x 480px screen for better experience.
It depend on you. Take some picture using the smartphone that you want to buy. Don't just listen from the sellers.


Artificial Intelligence (AI) is all the rage these days. As a young discipline, it developed into a powerful tool that enables machines to act and think like humans.
The idea of Artificial Intelligence can be traced back to classical philosophers and even antiquity. Nevertheless, it heavily progressed during the 20th century, with several major breakthroughs marked by computer scientists like John Von Neumann, Alan Turing, John McCarthy and Marvin Minsky, but especially with the Deep Blue computer – the IBM developed supercomputer that beat world’s best chess player Garry Kasparov in his own game
Since 2010, this discipline has experienced a new boom and it continues in that manner. If you’ve been wondering where Artificial Intelligence is mostly applied these days, you are in the right place. As it is expected for the AI software market to reach a size of 22.6 billion U.S dollars in 2021, here’s analysis of different industries that AI is impacting right now:
- AI in Robotics – robots that plan their own journey by recognizing various obstacles and are applied in carrying goods in hospitals, cleaning offices and large equipment.
- AI in E-Commerce – personalized shopping, fraud prevention and AI-powered assistants are part of this domain. Basically, by browsing your history and interests, these robots create recommendations for you and improve your shopping experience.
- AI in Marketing – by using pattern recognition, marketers can create personalized ads and AI chatbots can follow the user’s language and respond just as humans do. It can be also used to handle routine tasks like campaign reports and much more.
- AI in Social Media – the impact of AI in this domain removes hateful content and propaganda, understands conversations so they could be translated and by considering your likes determines what will be shown on your feed or explore section.
- AI in Navigation – the usage of Graph Neural Network and Convolutional Neural Network, the GPS technology can provide users detailed and timely information to increase safety.
- AI in Gaming – in this sector AI is used to predict human behavior using which game design can be improved and to create human-like NPCs to interact with players.
- AI in Automobiles – by using the vehicle’s camera, GPS, cloud services, radar and control signals self-driving vehicles can be built.
- AI in Agriculture – here AI is used to detect nutrient deficiencies in the soil by applying machine learning, robotics and computer vision.
- AI in Healthcare – AI is helpful in healthcare with building sophisticated machines that detect cancer cells and various diseases. Also, it is analyzing chronic conditions by using medical data .
- AI in Human Resources – using machine learning software, AI helps with blind hiring, by examining applications on specific parameters.
Although there is a big debate whether the technologies which we call AI now are actually artificial intelligence, computer scientists and developers are not discouraged from reaching the goal of creating Artificial Intelligence that is a self-learning and independently “thinking” machine.
With that being said, we can make predictions of how AI will influence our lives in the future. By the year 2030, with the usage of Artificial Intelligence we will be able to determine how things look, feel and smell without us seeing, feeling or being surrounded by it. We will also be able to understand people who live on the other side of the planet, without the loss in translation part. What is fascinating too, AI will be everywhere on a consumer and business level and our cars won’t even need a driver.
And most interestingly AI will be embedded in our brains. Virtual reality meetings have become more frequent during the pandemic and a class contact lens to our brains doesn’t seem too unlikely. Or as Monte Zweben, the co-founder of Splice Machine, said “ Being able to embed virtual reality directly into your brain would make virtual meetings feel real, so you could simulate the feeling of being hugged when FaceTiming a friend”.
While science fiction writers have expected more from AI, the rest of the world is generally satisfied with the progress of AI. After all, not everyone is ready for self-learning spaceships or humanoid robots.
So what do you think, what is in store for our future?
And in the meanwhile if you are curious what types of technological advancements can help your company flourish in the 21st century, do not hesitate to contact us!


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Illuminative LED Snowfall Projector Light
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The light comes with a handy remote making it easy for you to change the settings at the touch of a button, without even going outside. On the remote you can select whether to have a white or coloured light display, choose a run time between 1-6 hours, and change the speed of the lights.
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Specifications Dimensions: L15 x W19 x H22cm Weight: 545g Power cord length: 276cm 5V DC 5W IP44 G3472
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|UK (Mainland)||From £4.95|
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Right now, doctors and neurologists alike are using standard brain maps to pinpoint where epileptic seizures come from. However, some experts say that could be dangerous, especially for children.
That's why some doctors have decided to use a military targeting program designed for the medical practitioner. It samples parts of the brain the same way radar detects little blips.
The computer software looks for electrical impulses from the brain, excluding the ones coming from the seizure center. Those parts are seen in yellow.
Doctors say it's about two to three times more accurate than standards tests.


One source of loss with a solar power system is the conversion of the DC power produced by the panels to the AC power used by the electric grid. This is done by a piece of equipment called an inverter, in my case an Eltek THEIA 3.8 HE-t UL. The manufacturer claims it is "up to 97.3% efficient," meaning that I'll lose at least 2.7% of the power produced by the panels. The specification for the inverter includes an efficiency curve showing how the efficiency varies depending on the amount of power being produced.
I was curious to see how my setup compared to the spec, so I pulled data for December 2013 through October 2014. I don't have the instantaneous numbers that are used in the spec (it would be quite a lot of work to collect and process all of that) and I don't have access to the direct data on the inverter, so I compared the DC power output from the Tigo power optimizers on the panels to the inverter output measure by my eGauge. I used daily totals for both numbers, then created a scatter plot of the efficiency versus the total power output for the day.
- Minimum: 58.45%
- Maximum: 95.08%
- Mean: 91.76%
- Median: 93.90%
The numbers are generally in line with with the spec though they tend to be a few percent lower. The low efficiency for low production days is one of the reasons that the winter is such a tough time for solar, since anywhere from 15 - 40% of the power coming from the panels can be lost due to conversion. Luckily that only works out to a handful of kilowatt-hours, and isn't a problem in the summer.


Most people are not as excited about smartphones as they used to be because every smartphone company tries to keep the customers satisfied with the same monotonous updates year after year but the dress a surprise smartphone has been able to create a lot of excitement among its fans lately with only amazing specifications. But no, it has its own ecosystem technology.
Exciting those old days the night of the release of Apple’s new model phone, people will rush to your showroom with bed blankets to get lost so that they can buy the phone as soon as it starts selling in stores, but now online booking is out of the question. There is no such thing as excitement around smartphones, but Tesla Pifone is going to be completely different from all other smartphones in today’s world of electricity. Press Club is now about to enter the smartphone market after exerting its monopoly on the cable market. Musk-led Islam iPhone has already dropped out of the smartphone market. We hope Elon Musk is working behind the scenes to add the leader’s iPhone to the latest technology from all the world’s leading companies.
The effort will allow fierce competition with major competitors in the smartphone market. These specs are a very small part of the ecosystem announced by Kali Kachina. However, we will discuss in detail later how they are going to build the most powerful smartphone in the world. Some of the features are already being used by many phone companies on their phones but they don’t know much about how to present them in a much more attractive way. Tesla is going to use different lenses for the same type of work for the first time. A mens will be used for capturing video of the phone and again different lenses will be used for taking near and far pictures. Speaking of which, with a company’s screen camera Still could not achieve a very satisfactory result in any direction.
Let’s talk about the Tesla ecosystem. The ecosystem used in the phone has been created with the help of the company. In addition to this work, many well-known companies in the electric vehicle trade have worked together, for example, Milon. Bisex, the world-renowned space, and Neuralincom company is researching the first-second purchase and launching rockets regularly. We will now discuss why this phone is being touted as being so different from other phones.
The Solar Energy Industry has given Test Live the best of all. Tania has nothing new to say. They have the latest solar panel technology in their hands so they can easily connect the iPhone’s solar charging technology. You can use the light effortlessly. This feature has not been introduced in any other phone yet. They also use very advanced technology batteries. They will use the battery of their electron G technology and the same battery will be used in the iPhone. It is hoped that despite the many sophisticated features of this phone, it will be possible to use the 4G phone again for several days. Teesta Electric Khan’s first year has contributed a lot more to the development of a smartphone that is far better than the handicapped.
The system is much more advanced than other electric cars. Their super-charged network is spread all over the world. They have now built small and medium-sized electric trucks. This will enable the phone to be charged at a much faster speed. In addition to using the same technology used to build their electric cars, users are learning about it. The two products will benefit in the future. Tesla is different for Android and iOS. As it is a third-party app, its usage is very limited. On the other hand, they get thirsty. They can easily control their Tesla car by using the app on the phone. You can even have the camera on one end and always be able to keep an eye on it. Suppose you leave your area and go somewhere far away if you want…
Then with the help of your phone, you can see what’s going on around your car from so far away and if your car is stolen then you can easily take control of the car through this app. It’s a lot of fun not to be able to run away even if you want to, so let’s talk about their semiconductor plant from e-business. Since then Elon Musk has not focused on making their own chips. Now it has gained worldwide fame by making very modern and efficient chips. Can handle Teknaf phone processor speed will be much higher than 5089 also gets thirsty font…
Many more technologies will be added to the company. Tesla now makes advanced solar panels for roof use, which we discussed a little while ago. Using these panels you can make your own for free. You can turn it off at will when your home generates more electricity than you need. If you want, you can store that extra power in your Tesla battery solar system called Power Power. When the charge is over, your phone will receive notification alerts. The space company is going to make a significant contribution to the ecosystem of the space station. Used in the Mars journey of Human Made for.
The 1st is also being used for more purposes and has contributed significantly to the creation of the fastest car Road 42 project system. Their Sterling Satellite is going to be connected to the Tesla Auto System. Sterling’s Ultra High-Speed Satellite will be able to connect directly to the Internet over the telephone. This phone will have extremely fast download and upload speeds that are unmatched by any other phone. Link Internet Service The link will allow you to connect to any remote area of the world with the help of the internet. Another advantage of satellite internet is that you can use Fatik without a SIM card. If you don’t have a cellular network you will be able to exchange messages very easily.
They will be happy to know that SpaceX is also thinking of setting up a start line on Mars. Mukul explorers can easily communicate with the earth if they have only one phone. iPhone Neuralin contributes Tesla claims that the monkeys were able to reach out and reach the client without any health risks and that the Achiever could be easily removed. He said that many volunteers and Jubilee League are ready for this experiment and it is known that this technology will also have 5 minutes of various signals from the brain of the customer. Tesla also claims that five customers using this technology.
The phones are so powerful that they can take signals from the human brain and translate them into intelligible language by looking at them without touching them. There is no phone in the world today that can do exactly the same thing. Soon smartphones will dominate the world. Do you think Best Pie Phone can really dominate the world?


This new section entitled Scientific watch and summaries can be found in the tab Scientific watch. This new section as the goal of valorizing scientific research on mistreat of older adults leaded by Québec researchers.
In this section, you will find summaries of scientific articles made by Québec researchers. To this day, the Chair identified more than 80 articles published by Québec researchers since the year 1980. Each of this article will be the object of an analysis and a synthesis presented as a summary. To this day, 32 summaries were made, 10 were translated in English and progress is still being made.


We're over the moon to share the fantastic news that our Founder and CEO, Adam Roney, has joined forces with AI Tech UK as an AI and Web3 expert and Chief Tech Advisor for their Open Ethics social innovation initiative!
Adam has been an entrepreneur and technologist for over 20 years, helping businesses launch, scale, and build groundbreaking digital products and services. His passion for digital transformation, the tech ecosystem, and the community is unparalleled, and his expertise in AI, Web3, and other emerging technologies will be invaluable to AI Tech UK.
As Sherin Mathew, Founder & CEO of AI Tech UK, puts it
As a leader, Adam is brilliant in putting ideas in front of people. He is passionate and well aware of all things digital and also works with cutting-edge technologies. He is so aligned with what we do and our mission. There's a great synergy, and it's an honour to have him on board.
As a collaborative platform, AI Tech UK aims to democratise AI, Intelligent systems, Data, and Advanced Innovation across the UK for individuals, SMEs, and enterprises alike. Adam will be able to contribute to AI Tech UK initiatives and help businesses succeed in their AI journey, with a strong focus on ethics and putting people first.
AI Tech UK is working on delivering a National AI strategy, empowering everyone with advanced technology skills and helping businesses build AI solutions that contribute to the digital economy. We're delighted that Adam will contribute his diverse knowledge and skills to this mission.
At Calls9, our mission is to ensure that every business has access to the technology and expertise they need to realise their vision and full potential, with no barriers, no limits, and no exceptions. This partnership with AI Tech UK exemplifies our commitment to revolutionising the world of digital innovation.
Please join us in celebrating Adam Roney's exciting new role, and let's look forward to an amazing collaboration with AI Tech UK! 🎉


For quite a few years’ people have been talking about STEM. If you have not heard of it yet STEM stands for the integration of Science, Technology, Engineering and Math. Then the A was added a few years ago to make it STEAM with the “A” being the Arts. There has been a lot of talk about how to make this work in the classroom as well as finding ways it can be integrated into the curriculum. For some teachers the hard part is finding a project, unit or material that has all those elements in a unit. You might do well to have two or three of the STEAM components touching on a project but not them all. The search to find that right project is daunting If you Google STEAM units you will will come up with many. Where to start you might ask? Well I am here to tell you that I have one solution. I have a little electronics board that might hold the key to a STEAM program that could be used not with one unit, project or PBL but one that might follow with a student from mid elementary school right up to high school.
What am I talking about is an electronics board called an Arduino. A silly name yes but an extremely powerful electronic device that can be used in an infinite number of projects. A basic Arduino board has 14 inputs and outputs that you can connect hundreds of things to it. Your choice of add-ons ranges from many different kinds of motors to move things like robots. you can also add sensors that can detect motion, lights, sound, or a button to name just a few of the many sensors you could choose from. As well you can connect your computer to an Arduino that will accept input from your computer to the Arduino and from the Arduino back to the computer. The simple Arduino can even connect to the internet, Wi-Fi, and Bluetooth. Allowing your control your Arduino with many portable devices. I can even control my Arduino from my computer without having to be in the same room with it.
But wait how do you get it to understand all of this? Built into the Arduino is a programming language that would do us all good to learn. You write the program on your computer and then send it to the Arduino to run. I know I said that even elementary students could build things using the Arduino and they can. The folks at Scratch have created easy to use block type programming that makes programming the Arduino simple and quick. Others have picked up on the block type programing language and now there is about 4 easy to use programing environments for young students to use.
The best part about an Arduino is the cost. A basic board can cost as little as 50 RMB and a kit with ten or so parts including sensors electronics parts wires and more. This kit will get you going and the price is about 250 RMB. That is cheep enough that every student in your class could have one of there very own. As well that basic kit could get any willing teacher or team a start at looking at ways to build a new STEAM unit or using it to integrate into an existing unit.
The Arduino is all about programming, building circuits, learning about electronics, building the things that go with or around the Arduino and its components, sensors, motors and much more. That looks like all a great STEAM program needs I would say. Wait what about that A in STEAM how does it fit into this? Well believe it or not the Arduino got it start by and for artists. As a mater of fact when you write a program for the Arduino it is called a sketch. The are now whole programs in University teaching art students how to use the Arduino. The courses are called Physical Computing and artists all over the world are using them in amazing art shows. Look up Physical Computing and you will be amazing what this little board can do in the hands of a talented artist.
The Arduino can be made to control many different things. I myself have used them in my robotics projects in Grade 4 unit on systems. Besides that, I have made many other personal projects using sensors, LEDs, making noise, and telling me when my plants needed watering. I have used them in projects that interfaced with my iPad and Android Phone as well. The possibilities are endless where you could use an Arduino. I myself have just scratched the surface of the many projects available. Some of the first personal 3D printers used an Arduino to control it.
Ok by now your thinking you might try this thing out but wait what about the common core standards or the new Science Standard. I will admit there is not much out there as of yet but I know you are a teacher that likes to be on the cutting edge and this is just the place for you. I am happy to sit down with teachers and talk where this mighty device will fit in. I am happy to tell you all I know about the many different ways an Arduino can be used in the classroom.
If this has perked your interest in STEAM integration Let’s Talk!
Main Arduino web site
Different ways to program using Block code:
Tutorials on YouTube


|Min. Order:||1 Piece/Pieces|
|Payment Terms:||Paypal, L/C, T/T, WU|
|Place of Origin:||Jiangsu, China (Mainland)|
|Means of Transport:||Ocean, Air, Land|
|Production Capacity:||300 piece/Month|
|Delivery Date:||4 weeks||Brand Name:||Norman|
|Methodology:||Chemiluminescence immunoassay||Quality system certificate:||ISO13485|
Automated Chemiluminescence Immunoassay System (CLIA)
Self-developed antigens and self-manufactured antibodies
that ensures minimized intra and inter batch difference
Upgraded version, independent research and development.
Accurate testing result, more than 99% correlation with main stream Europe-Amefican products.
Testing speed: 100 samples/ hour
Sample capacity: 36
Reagent capacity: 9
Refrigeration function for samples and reagents
Testing Mode: Batch, STAT, special samples
Light emitting principle
Non-enzymatic chemiluminescence, long reagent stable time
Acridinium ester as the marker, stable performance, without any light source,
eliminating the influence of other factors.
Sodium hydroxide (NaOH) and hydrogen peroxide(H2O2 ) are excitation substrate
Structure of NORMAN Automated CLIA System
01 Cuvette loading zone
252cuvettes can be loaded one time and replaced at any time during testing
Memorize numbers and location of cuvettes
02. Reagent zone and sample zone
Power supply independent, magnetic beads levitation systems, refrigeration system is loaded in reagent area to keep reagent stable, the radio frequency identification technology is adopted in kit information (calibration curve, time of validity, sample type)
Sample information can be entered manually or scanning recognition
Three testing mode:
Batch, STAT, special sample test
Sample editing mode:
Hospital LIS System
Automatically software generating
03. Sampling needle
Automatic level detection, stirring mixing system, sampling needle made of titanium alloy material has good anti-collision function, single needle loads reagents, samples and magnetic beads. Inside and outside wall cleaning, on outer wall of needle is coated
by Teflon, high polish, ensure cross-infection does not exceed 10-5
36.5±0.5ºC constant temperature incubation, i
Incubation abnormity warning, magnetic separation components (independent magnetic separation),
05.Manipulator (exclusive design)
Mechanical grip: grab sample tube, avoid empty or partial catch.
Detection rod: automatic detection of sample tube, evaluate whether sample tube is located accurately
Automatic identification of reagent Kit (type, curve, reagent position), no need manual code scanning
07.Magnetic separation components
magnetic separation device closely combines with sample tube,
Nanjing Norman patented technology
linear correlation coefficient (r)≥0.99
Specification of Main reagents
Automated chemiluminescence assay consists of two parts, automatic reaction system and chemiluminescent assay system. Automated reaction system is the process to indirect specifically bind the luminescent markers to the solid phase carrier through incubation and magnetic separation method. Chemiluminescence assay system is the process that when luminescent markers move from the acidic environment suddenly to the alkaline environment, oxidized by the hydrogen peroxide then it emits photons with maximum wavelength 430nm, which is then captured by the photomultiplier.
The system utilizes acridinium ester and its derivatives as luminescent markers, luminescent through injecting excimer, and complete within a few seconds, belonging to flash type chemiluminescence. Acridine ester and its derivatives as luminescent markers for measuring analysis has advantages including simple, fast, no necessary catalyst, good stability, low non-specific binding and high sensitivity in the reaction, which is a new-type and efficient compound.
Installation environment requirements
1. Only for indoor installation and use. The installation environment shall be free of dust, mechanical vibration, or heavy noise, or power interference, with good ventilation.
2. Place the instrument on a solid and level table, the table carrying capacity shall be no less than 150kg (weight of the instrument);
3. For easy maintenance, leave some space around the instrument, which is easy to connect a variety of other components, also good for instrument cooling;
4. The instrument shall be far away from strong magnetic fields, strong electric field, water source, corrosive fluids; do not expose to strong direct light, do not place near heat source. It is prohibited to use the instrument near strong radiation source; otherwise it may interfere with normal operation of the instrument.
1. Power supply: AC220 ± 22V, frequency 50 ± 1Hz;
2. Rated power: 500VA;
3. Fuse sizes: F6A 250V, 5 * 20mm;
4. The instrument requires a properly grounded electrical outlet to provide the required power, do not use non-own power line;
5. The power outlet location shall allow sufficient space to facilitate plugging and unplugging the power line, do not put the analyzer in a location difficult to disconnect power.
Temperature, humidity and atmospheric pressure requirements
1. Work Ambient temperature: 10~30℃, it is recommended to install air-conditioning;
2. Relative humidity ≤70%.
3. Atmospheric pressure: 85~106kpa
Nanjing Norman Biological Technology Co., Ltd is dedicated to R&D and manufacturing of Immunofluorescence and automated chemiluminescence system. Founded in 2008, Norman biological has been upholding the idea that R&D shapes future ,concentration determines success.Now there are over 100 R&D engineers, 40% of which hold a PhD or master's degree. An over 30,000m2 global R&D center is in construction, and will hold more than 1,000 R&D engineers in the future.
We are looking for partners from all over the world, we can provide professional IVD prodcuts with top quality, excellent performance,best price and service, join us as a partner, enjoy win-win business!
Related Category: automated chemiluminescence immunoassay analyzer NRM411-S7


NewsNovember 14, 2018
Ladybirds mark Science Week by doing new STEM badge!
Hundreds of Ladybirds are working on the new Ladybird STEM badge to mark Science Week (November 11-18).
The badge aims to encourage girls from as young as five to develop an interest in Science, Technology, Engineering and Maths (STEM) through a series of fun science experiments and engineering projects.
By building towers, making telephones using string, using magnets and experimenting with playdough and slime, the girls learn about balance, stability and planning, how sound travels, magnetism etc. It is hoped that doing this will spark an interest in STEM subjects that they will pursue inside and outside of school.
IGG Programme and Training Commissioner Jenny Gannon says: “We are delighted to launch our new STEM badge for Ladybirds during Science Week. It complements the Science Investigator and Engineering badges we already have for Brownies (aged seven to 10) and Guides (aged 10-14).
“Girls aren’t always encouraged to pursue STEM subjects in school and we want to rectify that by introducing girls from a young age to STEM activities. Women are under-represented in STEM careers but we believe that, by encouraging an interest in these areas in a non-formal setting, girls will be more likely to pursue these subjects as they get older. In doing this, we hope to help address the gender imbalance in these fields.
“Taking part in STEM activities, like doing all Guiding projects and challenges, is also a great way for girls to develop problem-solving, teamwork and other life-skills while also growing in confidence,” Jenny added.
Some girls, including Bray Ladybirds, have been so keen to earn the new badge that they have already completed all the activities!
Sinead Bayliss, a Leader with Bray Ladybirds, says: “The STEM badge is a unique opportunity to cover a wide range of topics in a fun, creative and informative way. Doing the STEM activities is a great excuse for girls to get messy with slime or oobleck, investigate with magnets and slopes, experiment with water and food colouring, play with numbers and stack or build with anything.
“There was a great excitement in the air as they set about the tasks, fascination as girls stuck pencils into bags of water and they didn’t leak everywhere and infectious laughter as they mixed various concoctions from cornflour and made a terrible mess. This is the most fun badge we have ever worked on because the girls were so enthusiastic and the possibilities were endless!”


01-30-2005, 04:19 PM #1
Anyone know anything about these faster then light experiments?
have the experiments ever been succesfully repeated?
Faster than the speed of light?
Current research will provide the basis for further expanding man's understanding of the universe.
By Peter Symonds
MODERN physics rests on two basic pillars--the general theory of relativity as elaborated by Albert Einstein and quantum mechanics as developed by a line of brilliant physicists, including Neils Bohr, Werner Heisenberg, Louis De Broglie, Max Planck and Erwin Schrodinger.
Both theories have provided remarkable and often startling insights into the nature of matter and its laws. Relativity deals with fast objects traveling with velocities approaching that of light and provides a theory of gravitational forces. Quantum mechanics emerged from investigations into the realm of subatomic particles.
Relativity and quantum mechanics have been applied to investigations into a range of phenomena-- from the intricacies of the atom to the evolution of the universe itself--and have been confirmed by a host of experimental observations.
Yet scientists have long noted certain limits to, and conflicts between, these two theories. The noted theoretical physicist Stephen Hawking states in his book A Brief History of Time: "Unfortunately ... these two theories are known to be inconsistent with each other--they cannot both be correct."
A unified theory providing a description of all four fundamental physical forces--electromagnetic, gravity and the weak and strong nuclear forces--has so far evaded the efforts of theoretical physicists.
A series of extraordinary experiments conducted by teams of physicists in the US and Europe over the last five years has once again highlighted the lack of a unified theory. For the first time, physicists have measured photons--particles of electromagnetic radiation--traveling faster than the speed of light.
One of the consequences of Einstein's special theory of relativity is that nothing can travel at superluminal velocities, that is, faster than the speed of light. Any particle with a mass would require an infinite amount of energy to accelerate to the speed of light. Only light itself or other forms of electromagnetic waves can travel at such a velocity.
Yet through one of the quirks of quantum mechanics, physicists have predicted and now measured photons of light and microwave radiation moving at superluminal speeds. Thus we are confronted with the riddle of light traveling faster than the speed of light!
Exploring the "tunnel effect"
At the core of quantum mechanics, and of its many apparent paradoxes, is the uncertainty principle, first elaborated by Werner Heisenberg in 1927. According to this principle, no observer, regardless of the subtlety of his methods, can determine precisely both the speed and the momentum of a particle at one point in time.
Quantum mechanics does not predict outcomes with certainty, but calculates the probabilities of different eventualities.
The observation of everyday events--the motion of a car or the firing of a gun--remain virtually unaffected by the limits imposed by the Heisenberg uncertainty principle. But at the subatomic level, it has some extraordinary consequences. Matter itself takes on a dual character, able to act in differing circumstances both as waves and as particles.
The possibility of particles traveling faster than the speed of light depends upon an outcome of quantum mechanics known as the tunnel effect. If one bounces a tennis ball against a brick wall, one expects the ball to bounce back, not reappear on the other side of the wall--no matter how many times one throws the ball.
However, in the case of particles such as electrons fired at a subatomic barrier, quantum mechanics predicts that not all will be reflected. Some electrons will literally pass through the "wall" and appear on the other side. Not only is the tunnel effect experimentally observable, but it forms the basis for an electronic device known as the tunnel diode.
In 1955, the American physicist Eugene Wigner and his student L. Eisenbud at Princeton University analyzed the phenomenon of quantum tunneling and concluded that under certain circumstances particles could pass through a barrier at faster than the speed of light.
This conclusion has been the subject of continuing debate among theoretical physicists because of the difficulties it raises. But up until recently scientists' ability to test the various predictions has been limited by the technology available.
Light travels in a vacuum at a velocity close to 300,000 kilometers a second. To measure particles moving at a speed faster than light over extremely small distances requires a capacity to determine time more accurately than the most sensitive atomic clocks.
Steven Chu and Stephen Wong at AT&T Bell Labs in the US first measured superluminal speeds for light pulses traveling through an absorbing material 10 years ago, but their results were largely ignored.
In 1991, an Italian team of scientists at the National Institute for Research into Electromagnetic Waves examined a phenomenon closely related to quantum tunneling. Under certain conditions, microwaves can be transmitted through a "forbidden zone" of a wave guide, contrary to the prediction of classical physics that they will be reflected.
While the Italian scientists were unsuccessful, the following year GUnter Nimtz and his colleagues at the University of Cologne in Germany reported measuring microwaves passing through the forbidden zone at speeds greater than that of light.
A breakthrough in measurement
In 1993, an American team headed by Raymond Chiao at the University of California in Berkeley provided further confirmation of superluminal speeds by measuring the tunneling times of photons of visible light.
The experiment required considerable ingenuity, as the time intervals involved were extremely short--a few femtoseconds (a femtosecond is a thousandth of a trillionth of a second).
Chiao's team began by establishing an optical "race track" for two photons by shining a laser beam on a special crystal known as a down-converter, which absorbs a high energy photon and emits a pair of photons of lower energy. Each photon of the pair was then directed along a different path using mirrors and directed into a device known as a co-incidence counter, which registers whether the two photons arrive simultaneously.
The difficulty with the co-incidence counter is that it is only able to measure to within a billionth of a second, making it far too inaccurate for the experiment being considered.
To overcome the deficiency, the Berkeley scientists utilized a another quantum property of matter. The two beams of photons were directed at a half-silvered mirror. Ordinarily a photon has a 50-50 chance of passing through or being reflected by the mirror, and thus there is also a 50-50 chance that the two photons will travel along separate paths and will be registered by the co-incidence counter.
If however, the pair of photons arrive at the mirror within 20 femtoseconds of each other, quantum mechanics predicts that the pair will travel on the same path and thus will not be detected by the counter. By fine-tuning the apparatus, Chiao and his colleagues were able to achieve the remarkable accuracy of a quarter of a femtosecond. They demonstrated that when a thin optical barrier was placed in the path of one of the photons, it tunneled through the obstacle at a velocity 1.7 times that of light.
Can signals exceed the speed of light?
How such speeds can be achieved without breaching the laws of physics is not well understood. One way of viewing the problem is to regard the tunneling particle as "borrowing" energy to overcome the barrier. This would mean that other particles would acquire a negative kinetic energy. This notion of negative kinetic energy makes no sense in classical physics, according to which an object at rest has no kinetic energy and one which is moving has a positive kinetic energy.
Chiao states that his discovery does not violate Einstein's laws of relativity. While individual particles may travel faster than the speed of light, he maintains that it is not possible to transmit a message at superluminal speeds.
"These experiments do not mean that you can send a signal faster than light. Only a few photons get through the barrier. Because tunneling is probabilistic, we've no way of knowing which ones they will be. So it would not be possible to send any useful information," Chiao told the New Scientist magazine.
Other scientists dispute Chiao's conclusions.
Several European teams have been experimenting with more intense photon sources and thicker barriers. Their results indicate that the tunneling time for a particle becomes "saturated" or reaches an upper limit. If a particle can "borrow" energy, quantum mechanics does not permit it to do so indefinitely.
Once the limit is reached, the particle will tunnel through the barrier in the same time, regardless of whether its thickness is two meters, two kilometers or 2,000 kilometers--if, of course, such an experiment could ever be carried out!
Last year, New Scientist reported the extraordinary findings of a German research team headed by Nimtz, who was attending a conference organized in Snowbird, Utah:
"Attending the meeting were some of the leading researchers in this field of faster-than-light quantum phenomena. To an astonished audience, Nimtz announced that his team in Cologne had not only measured superluminal speeds for their microwaves, but had actually sent a signal faster than light. The signal in question was Mozart's 40th Symphony....
"According to Nimtz, Mozart's 40th Symphony hopped across 12 centimeters of space at 4.7 times the speed of light. What's more, Nimtz actually had a recording to prove it. To his now bemused audience, he played a tape in which among the background hiss strains of Mozart could be heard. This was the 'signal' that had traveled faster than light."
A vigorous debate ensued as to whether or not a piece of music could be considered a signal. According to Einstein, a signal traveling faster than light would effectively be traveling back in time. The ability to send information back in time would violate the scientific conceptions of cause and effect: the results of an experiment could be influenced after it had happened!
Few scientists accept Nimtz's claim that a signal can be propagated faster than the speed of light. However, the experiments by Nimtz, Chiao and others point to the limitations of the existing theories of physics and add a further spur to the quest for a unified theory embracing quantum mechanics and the theory of general relativity.
01-30-2005, 05:06 PM #2Anabolic Member
- Join Date
- Jan 2003
- under some plywood sheets
great read!! i love those kind of article!!!
01-30-2005, 05:16 PM #3
Very interesting! I love that type of stuff.
01-30-2005, 05:39 PM #4
you really need to read The Elegant Universe it will really blow your skirt up. Or if you would like, I may be able to copy a dvd version of it and send it to you. Anywho there is some great info on quantum tunneling. all mathematically proven, but as of the date when the book was written, no conclusive experimental evidence had been documented or conceived. If I recall there is in the works a new particle accelerator in Geneva which they hope to use to confirm the existance of other messenger particles and what not.
I love physics. I doubt we'll ever know it all for sure, but it is a hell of a lot of fun to try and figure it out
01-30-2005, 05:47 PM #5Originally Posted by symatech
cant wait for the new particel accelerator to be completed
01-30-2005, 05:49 PM #6
It's slated to be finished this year
edit: i hear ya on book on computers bro, I never read e-books. I cant do it
01-30-2005, 11:31 PM #7
it is impossible to travel faster than the speed of light. check out this book
Despite the explosion of knowledge in the last few decades, much of physics still remains a mystery. We know little of how the universe really works, or how it came into existence. Fundamentals escape us -- such as the actual cause of gravity. Even the behavior of light leaves us perplexed. For example, why does light maintain a constant speed? What regulates it? Why does it slow down as it passes through a crystal and then speed u on the other side? What energizes it? These are only a few of the exciting mysteries which Roy Masters brilliantly tackles in "Finding God in Physics."
01-31-2005, 03:01 AM #8Originally Posted by trailrider38
01-31-2005, 05:31 AM #9
the elegant universe is out now..ive had it for a LONG time. it is a good read. or is there a new revision coming out? Same with "a brief history in time" another good read. Got it for christmas. Hawkins revised it though so if you had it before, go to borders and read the new chapters...
01-31-2005, 01:57 PM #10Originally Posted by johan
Yes I read the article, and found it to be lacking in a definate answer to the question. when measured, a single photon is assumed to have tunneled through a mirror? and how on earth with todays technology are these people measuring a thousandth of a trillionth of a second in order to time a photon . this is purely speculation and theory.
01-31-2005, 02:04 PM #11Originally Posted by max2extreme
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1 edition of U.S. non telecommunications fiber optic component market in the U.S. found in the catalog.
U.S. non telecommunications fiber optic component market in the U.S.
|Other titles||US non telecommunications fiber optic component market in the US.|
|Contributions||Frost & Sullivan.|
|LC Classifications||HD9696.F523 U557 1982|
|The Physical Object|
|Pagination||vi, 255 leaves :|
|Number of Pages||255|
|LC Control Number||87143641|
For instance, advanced optics are used in number of products that reach the medical optics market from optical fiber to full detection systems., The global optical communications market is segmented into component, technology, application, end users, and region. | Complete United Fiber Optic Communication Inc. stock news by MarketWatch. View real-time stock prices and stock quotes for a full financial overview.
The global fiber optic cable market is set to touch a valuation of approximately USD billion at a % CAGR from to , Fiber Optic Cable Market, Type (Single-mode, Multi-mode), Application (Long Distance Communication, Submarine Cable, CATV), Region — Forecast till The Top Tower Companies in the U.S. list is from a database maintained and updated by Wireless Estimator. If you are a representative of a tower company and have additional updates to your total tower count, or if you are not listed and have 10 towers or more, please contact [email protected] cannot republish this information without obtaining permission from WirelessEstimator.
Defined by ITU-T G as “extended” for wavelengths between and nm This band includes the high OH peak in single-mode fibers G D fiber is designed for transmission within the extended band In FTTx systems, the term can be confused with the enhancement band, which the ITU-T G and G PON FTTx standards define as the wavelengths between and nm for RF . Optical Fiber Telecommunications VI (A&B) is the sixth in a series that has chronicled the progress in the R&D of lightwave communications since the early s. Written by active authorities from academia and industry, this edition brings a fresh look to many essential 2/5(1).
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U.S. fiber optics market size accounted for USD billion in and is expected to grow at a steady pace through Fiber optic cables are replacing metal wires owing to their higher efficiency and reliability.
These cables are majorly used for da. Telecommunications. Mobile phone market share held by vendors in Poland Number of fiber optic access lines in New Zealand Fiber optics market size in the U.
This statistic represents the actual and projected size of the U.S. fiber optic cable market in and It is predicted that the U.S. fiber optic cable market will grow to some billion.
The New York based glass and ceramic manufacturer - Corning is leading the optic fiber market. They invented the thin fiber threads, transmitting the data at light speed. It registered USD million revenue. Corning leads the market, with Lucent Technologies following it at the number two position and Alcatel at number three.
Over the period under review, fiber optic cable production reached its peak figure level in and is expected to retain its growth in the near future. Fiber Optic Cable Exports Exports from the U.S. Inthe amount of fiber optic cables exported from the U.S. totaled X tonnes, coming down by -X% against the previous year.
Product coverage: Fiber optic cable The report provides on an in-depth analysis of the U.S. fiber optic cable market. It indicates the latest data of the market size and volume, domestic production, exports and imports, price dynamics and turnover in the industry.
The structure of the U.S. telecommunications industry has changed dramatically over recent decades, with consequences for research. Major changes over the past several decades have included the breakup of the Bell System, especially the divestiture, the creation of Lucent Technologies, and the advent of long-haul competitors such as MCI and Sprint; the transformation of cable system.
Together, these trends will increase the demand for fiber optic cable in the medium term. U.S. growth in fiber optic cable consumption is expected to accelerate to. In North America, the U.S. is set to represent the domain share in the fiber optic connectors market.
Hardened fiber optic connectors (HFOCs) are passive telecommunication components that are used widely in the U.S. to withstand climatic conditions such as snow, high winds, ice storms, and sleet/5(20).
Optical Fiber Telecommunications VI (A&B) is the sixth in a series that has chronicled the progress in the R&D of lightwave communications since the early s. Written by active authorities from academia and industry, this edition brings a fresh look to many essential.
The global fiber optics market size was valued at USD billion in and is projected to exhibit a CAGR of % from to The technology is one of the modern-day innovations, which has evolved with time, owing to rigorous studies carried out by researchers and scientists across the globe through extensive research and development.
DUBLIN--(BUSINESS WIRE)--The "U.S. Fiber Optic Cable Market - Analysis And Forecast to " report has been added to 's report provides an. DUBLIN, Ap /PRNewswire/ -- Research and Markets has announced the addition of the "Fiber Optics Market by Cable - Global Forecast to " report to their offering.
The fiber optics. Based on application, the fiber optics market has been segmented into communication (telecom, premises, utility, CATV, military, industrial) and non-communication (sensors and fiber optic lighting). The communication segment is estimated to be the largest application of the global fiber optics market.
United Fiber Optic Communication Inc. advanced stock charts by MarketWatch. View historial stock data and compare to other stocks and exchanges. North America Fiber Optics. Fiber Optics and Carbon Electrical Equipment & Component Manufacturing Industry (U.S.): Analytics, Extensive Financial Benchmarks, Metrics and Revenue Forecasts toNAIC U.S.
Fiber Optic Cable Market. Analysis And Forecast to | USD 2, The global fiber-optic connector market to grow at a CAGR of % during the period The report covers the present scenario and the growth prospects of the global fiber-optic connector.
Global Fiber Optic Cable Industry Market Research Report 1 Fiber Optic Cable Introduction and Market Overview Objectives of the Study Definition of Fiber Optic Cable Fiber Optic Cable Market Scope and Market Size Estimation Market Concentration Ratio and Market Maturity Analysis Global Fiber Optic Cable Value ($) and Growth Rate from Market Segmentation By JuneCiena's stock had soared to $ per share, giving it a market capitalization exceeding $30 billion.
Sales of the company's new line of products prompted the investor optimism, though some analysts were beginning to wonder whether the U.S.
fiber optic network had been ry: Telecommunications equipment. Communications infrastructure upgrade | The need for deep fiber Wireless networks were at an inflection point as 4G services launched early in the decade.
“More spectrum and faster networks” became the rallying cries of consumers, carriers and governments alike in the global competition to lead in wireless Internet speeds.
The world. For gigabits and beyond gigabits transmission of data, the fiber optic communication is the ideal choice.
This type of communication is used to transmit voice, video, telemetry and data over long distances and local area networks or computer networks.A fiber Optic Communication System uses light wave technology to transmit the data over a fiber by changing electronic signals into light.Volume II focuses on fiber optic technology and long distance fiber optic networks.
Among the volume's conclusions are: fiber optic technology is sti_l a young technology, with improvements yet to be realized in performance and cost; fiber optics is the preferred medium for many long distanceFile Size: 6MB.This report provides an extensive analysis of the current and emerging market trends and dynamics in the global fiber optics cable market.
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The Winter Workshop on Complex Systems is a one-week workshop where young researchers from all over the world gather together for discussing about complexity science and engaging into novel research projects.
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Year 2021 has been the year of 5G- as a lot of smartphones including budget phones are being featured with 5G technology.
With the upgrades in midrange processors and abilities, midrange smartphones like the Galaxy A71 are acquiring fame and are turning into a good option for many consumers. Samsung is currently working on the successor of Galaxy A71, the Galaxy A72 5G, that will apparently come quite soon to the market – both in the US and in different nations. In case you’re interested or getting excited about the coming mid-range smartphones, you are in the right place.
In this article, we will tell you everything about upcoming 5G phones, which are based in the reliable leaksters.
Samsung Galaxy A72 5G Release date:
- March 2021 (rumored)
The latest rumour concerning the Galaxy A72 5G release date guides us toward a possible March 2021 announcement and launch date. We have additionally heard that there will also be a Galaxy A72 4G variation too, which may be delivered around similar time as its 5G-empowered kin.
Samsung Galaxy A72 5G Price
This year, it appears Samsung will keep the cost of the Galaxy A72 5G like the Galaxy A71’s value, which was $599, at the time of launch. It’s very conceivable that the Galaxy A72 5G will likewise begin at $599 for its 128GB variation.
A new leak by the German portal Idealo tells that the possible European cost for the Galaxy A72 4G-just: €449 for the 128GB variant and €509 for the 256GB variant. For the US, these costs generally sum to individually $544 and $617. The German site didn’t give us the costs for the Galaxy A72 5G, and they may be somewhat higher than this, most probably it will match the Galaxy A71 5G price.
Keep in mind that the official prices have not been announced yet and surprises are still possible.
Samsung Galaxy A72 5G Specifications:
Here are the Galaxy 72 5G expected specifications, based on rumours and leaks:
- 6.70-inch Super AMOLED display with Full HD+
- Quad-camera system with a 64MP main sensor
- Plastic back, aluminium frame
- Android 11 and One UI 3.0
- 5G support
- Snapdragon 750G (4G-only variant will reportedly feature Snapdragon 720 processor)
- 128GB base storage, expandable
- 6GB/8GB RAM
- USB Type-C, 3.5mm headphone jack
- 25W fast charging
These are the specifications that we expect the Galaxy A72 5G to sport, based on rumors and leaks. Additionally, certain rumors state that the A72 will also feature OIS (Optical Image Stabilization) for its camera, which would be a great addition to the photo-taking capabilities of the midranger.


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Mule Lighting now has their LEDison series of LED lamps which are meant to replace standard incandescent lights for decorative applications. Unlike most other LED lights, these fit into standard Edison-base sockets (hence the name LEDison.) These can be used just like compact flourescents with no special fixtures required.


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