Artificial Intelligence is a very wide term that includes all concepts and algorithms, which may simulate, partially replace or boost human thinking and behavior. Everything from smart lights, internet card payments, smart cars, chatbots, predictions and pattern detections in data can be considered part of the artificial intelligence phenomena. Most algorithms work on analyzing long series of data, including encoded speech and images. In this article, I would like to show you some nice examples.
Mythological note: Because of the syntax simplicity, many AI libraries utilize Python programming language as an interface to the programmer or the data scientist. Python was originally a serpent living under the Greek sanctuary of Delphi, who was killed by Apollo, the god of prophecy. The gases from the serpent’s decaying body gave inspiration to Pythia, the high priestess of Apollo.
Cyber Security and Time Window
In cyber security, you need to analyze a long series of data in real-time, such as logs from network components, user activity in all kinds of applications and so on. The analysis should detect defined suspicious patterns such as port scan, multiple failed user logins, brute force attacks to create alerts and thus make system administrators quickly react to discover the security incidents and prevent data loss or denial of service. And the way how the patterns are detected is usually through the use of a time window.
The time window looks at parts of the data series, such as one minute, five minutes, one hour, one day etc. and splits the data series in this way. Then it aggregates them and observes what kinds of and how many events match the defined security pattern. The time windows are created in real-time and there is a pressure to spare as much memory and performance as possible. The time window is thus an example of an artificial intelligence algorithm applied in the area of cyber security.
User Behavior Analysis in Telecommunications
In all kinds of situations you need to monitor the activity of entities such as users and devices to know whether they behave or work as expected. In telecommunications, the monitored devices are transmitters that also provide information about the users or SMS cards connected to them. Next to the time window, the so-called session windows are used to alert administrators, when one of the transmitters does not send events and thus requires to be repaired or replaced. The activity of users or SMS cards can be monitored as well, and even the geographic location of them can be approximated simply by the history of their connections to different transmitters.
In cyber security, this kind of analysis is called UEBA, that is user and entity behavior analysis. It is also based on detection of predefined patterns as the time window, but instead of time dimension it focuses on a specific entity.
Genetic Programming and Approximation of Complex Tasks
Genetic programming is based on evolutionary algorithms, which approximate a solution to a (mathematical) problem that by using deterministic algorithms would be hard or impossible to solve in an acceptable amount of time. Evolutionary algorithms are based on an initial population size, which is created using some idea on how the final solution may look. Then the algorithm creates multiple generations one by one, while applying reproduction/crossover of genes and mutation. In every iteration through every generation the fitness of each individual is evaluated using the assignment of the task/problem and only a certain number of individuals with highest fitness is selected for reproduction. It is necessary to escape only locally optimal solutions, meaning the ones that look like the final solution only from the perspective of similar solutions. That is why random mutation is applied as well as the possibility that some of the individuals with lower fitness or their offspring may also make it to the next generations. The evolutionary algorithms are thus very sensitive to initial parametrization and often require multiple runs with different settings.
The genetic programming goes even further to create programs or, more precisely, a tree of function calls. Each individual represents one possible tree and its fitness is higher, if the result of the function calls represent the expected output of the program/application. Thus with every generation the tree can grow to create the final program representation. Genetic programming can be used to find a solution to parsing long and non-standard messages from cyber security systems or to parametrize neural networks. If you need a quick approximation of a program, that you will later evaluate and rewrite to be more optimal and complex, you can definitely use genetic programming.
For Python, there is a nice comprehensive library for evolutionary algorithms and genetic programming called DEAP.
Finding the Shortest Path on the Map using Contraction Hierarchies
Contraction hierarchies is an algorithm for preprocessing shortcuts in map data using edges (roads) and nodes (junctions). When the preprocessing is done, people can query the program and find the shortest way between any two points on the map in a fraction of a second. The algorithm tries to remove each node from the graph and checks if a shortcut between neighboring nodes can be created based on the length of the edges previously leading to the removed node. If there is no other shortest shortcut, the algorithm continues to contract other nodes.
Customized contraction hierarchies add a customization phase between the preprocessing and the query, that allow to quickly include information about the current traffic and so on. It is all about the priority each shortcut has for the final query.
For C++, there is a library for route planning utilizing contraction hierarchies called RoutingKit.
Probabilistic Models and Weather Forecast
Probabilistic and statistical models are algorithms, which usually detect so-called seasonal patterns in data and try to make predictions on how the data series should probably continue. The season in this case is not only a yearly season, but it can represent a compound of hour, day, week, month or several years period. The probabilistic models are especially relevant when trying to predict future possible anomalies in the data, activities of users or seasonal cycles of weather.
Statistical models can predict trends in data and can be based on simple statistical approaches such as linear or polynomial regression. When you have a representative number of data, you can try different types or regression models to find the one that most likely matches the trends contained in your dataset.
Machine Learning, Deep Learning and Neural Networks
Machine learning is the most exposed part of artificial intelligence, which offers promising results. It is based on models periodically trained and tested to produce expected outputs. It may include simple decision trees built from the training dataset, such as if conditions on some extracted features, the color of a fruit for instance, which then produce results, like “the red fruit is an apple”. However, the core part of machine learning today is deep learning (layered models partly based on human brains’ structure) with its neural networks, which have different architectures based on their type and areas of their usage.
Neural networks are composed of layers of connected nodes, where each node consists of inputs, an activation function and outputs. The neural network model is trained to minimize or maximize a predefined loss function and is optimized using optimizers. Let me mention some of the types of neural networks. There are convolutional neural networks (CNN), that extract features from data and are today used mainly for processing of images and classification tasks.
Then there are recurrent neural networks (RNN) with feedback connections between layers. They are used mainly for regression tasks such as predicting data series such as text or speech. One of the most useful recurrent neural networks is long short-term memory network (LSTM), where the nodes include memory and are able to skip long gaps in data series, which is especially useful in cyber security.
Neural networks work with tensors, which are multidimensional representations of the data with given size and data type. I do not want to go much into details, instead I would like to provide some more examples from this area.
Plant Disease Detection
Plant disease detection is based on datasets of pictures taken from healthy and ill plants. Thus the convolutional neural networks are used, which extract features from the pictures to detect patterns, which may signify that the plant is ill. Each picture is transformed to a tensor, that is a numeric representation with pixels as its elements, and passed to the neural network model for training and testing. However, the model can be extended by processing not only images, but also descriptions of the plants given by the researchers or farmers.
The descriptions can be processed by more complex CNN networks such as graph convolutional neural networks (GCN), if the keywords from the descriptions are organized into a graph showing relation between features such as “brown leaves” connected with “fungi”.
Malware detection is a cyber security task, where all kinds of neural networks such as RNN, LSTM and CNN can be used. Malware is a software designed to infiltrate a system or an application to spy on the user or damage the device. What I want to mention here is that malware in a computer can be compared to illness in a plant, thus we can translate the malware detection task into plant disease detection.
We can get datasets of normal and infiltrated files and transform them to “pictures”, or, more precisely, to the same tensors that would be obtained from decoding a picture. We can read the file byte by byte and transform every one of them to a number similar to a pixel in a picture. We would have the same data type (integer number) and a fixed “height” and “width” of the tensor. Then we define multiple CNN layers with the output being a numeric classification result, which is the probability that the file is infected by malware.
Transformers, Speech Recognition and Painting Pictures
Transformers are more complicated neural networks that utilize encoder-decoder architecture and the self-attention mechanism. Basically it means that the neural networks in the transformer are aware of the location of a word in a sentence or a pixel in the image. The encoder first transforms the original pictures or texts to a pool of features or tokens, while the decoder part creates an image or the text from the already prepared tokens.
In this way, you can instruct the encoder part to expect a picture as the input and the decoder part to produce a text output – or vice versa. You can even instruct the encoder to encode a text from one language into tokens and the decoder part to transform these tokens to text of another language. Using transformers, you can paint pictures from text or transform human audio speech into text. Transformers simply transform.
For inspiration, look at VitModel transforming images to text: https://huggingface.co/docs/transformers/model_doc/vit or the famous DALL-E mini transforming text to images: https://huggingface.co/spaces/dalle-mini/dalle-mini
There are many ways on how to build chatbots, which reply to messages of a user. Chatbots need to detect patterns in the user’s question, discover their intent and form a reply that would make sense. Chatbots can be based on the transformer architecture or simpler embedding or tokenization, that detects words in a sentence and creates numeric representations of them.
For more information, see the following articles:
Prediction of Chaos and Nuclear Fusion
The promising use case for artificial intelligence is the prediction of chaos. In mathematics, chaotic systems are represented by non-linear functions that are very sensitive to initial conditions. They include the spreading of forest fires, the climatic system of the Earth, trends in society or the control of nuclear fusion, which would deliver cheap energy to everyone.
The control of the plasma, where nuclear fusion is happening, is done using large magnets. The state of the plasma changes rapidly, so that is why the reinforcement learning, or the learning through feedbacks must be used. The solution to this problem can utilize neural networks, but it is not mandatory. DeepMind open sourced a part of their simulation to the nuclear fusion control problem, which is available here: https://github.com/deepmind/deepmind-research/tree/master/fusion_tcv


Later microprocessors such as the Motorola and the Zilog Z placed the MMU together with the CPU on the same integrated circuit, as did the Intel and later x86 microprocessors. If the pbit is zero, an interrupt is generated for the MCP operating system to make the block present. The linker then searches through the archive to find the specific object modules that contain the symbols that need to be resolved for example, the definition of printf.
During a context switch, the operating system has to inform the processor's memory management unit that it has to use a different page table. A PFN stores the physical address without the page mask bits.
But because programs do actually exhibit strong locality, your operating system can do relatively few swaps per reference. In doing this, the operating system is responsible for keeping track that certain page frames belong to multiple processes. All assume a full, position independent executable base with full Executable Space Protections and full Address Space Layout Randomization.
A hardware register also has to be added to the processor that will allow the operating system to set the ASID during a context switch. No macro is available for converting struct pages to physical addresses but at this stage, it should be obvious to see how it could be calculated.
The functional interface of memory is: We can only do two things: This was the first time that making CES became a near possibility. If the address field is zero, this is the first access to this block, and it is allocated an init pbit. With a paging system that uses direct mapping, the page table contains an entry for every page page table entry, or PTE in the process' virtual address space.
There are many parts of the VM which are littered with page table walk code and it is important to recognise it. The permissions determine what a userspace process can and cannot do with a particular page.
Now we have two of those. The default value is Everything below this area is still handled as before.Recap: Virtual Memory • Memory Management Unit (MMU) • It is set when a write to the page occurs • Note: when you do exercises in exams or hw, we’ll oen tell you to ignore counng M,R,V,Prot.
Every memory access is translated from a page to a page frame by the memory management unit. A page may be placed in any available page frame. A page may be placed in any available page frame.
The memory management unit maps a page to the page frame in which that page resides. Memory-Management Unit (MMU)! Hardware device that maps virtual to physical address In MMU scheme, the value in the relocation register is added to.
The Memory Management Unit. Even when you have enough physical core to avoid swapping, the part of the operating system called the memory manager still has important work to do.
It has to make sure that programs can only alter their own data segments — that is, prevent erroneous or malicious code in one program from garbaging the data in.
A memory management unit (MMU), sometimes called paged memory management unit (PMMU), is a computer hardware unit having all memory references passed through itself, primarily performing the translation of virtual memory addresses to physical addresses. Article does not focus on any one architecture, but seeks to model a generic CPU with an MMU.
A general discourse on Virtual Memory systems. As a rule, a chipset (motherboard) would tend to have N bytes of physical memory.
Physical memory is "real" memory which .Download


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15 December 2023
At the Solar Energy Sector Forum, hosted by the Basque Energy Cluster (ACE) at the Bilbao Exhibition Centre (BEC), Asier Sanz from Tecnalia showcased pioneering concepts for floating photovoltaic plants in marine environments.
The event, which brought together key stakeholders in the solar energy sector, featured presentations on various projects and initiatives aimed at advancing solar energy technology.
Asier’s presentation highlighted the potential of floating photovoltaic plants to harness solar energy in marine environments, contributing to the development of sustainable energy solutions.
Stay tuned for more updates from the NATURSEA-PV project.


A doppler ultrasound is a noninvasive test that can be used to estimate the blood flow through your blood vessels by bouncing high-frequency sound waves (ultrasound) off circulating red blood cells a regular ultrasound uses sound waves to produce images, but can't show blood flow. The doppler effect is a phenomenon which relates the frequency of the harmonic waves generated by a moving source with the frequency measured by an observer moving with a different velocity from that of the source. Even if the aircraft's crash position could not be determined, doppler effect analysis on satcom pings enabled inmarsat to determine mh370's final route over south indian ocean until a final. A detailed spectral analysis of the signal received during the second stage reveals a central frequency of 3977 khz, ie, a doppler shift of 023 khz that corresponds to a emitter speed of 198 m/s if a sound speed of 343 m/s is considered.
Matthew schwartz lecture 21: the doppler eﬀect 1 moving sources we'd like to understand what happens when waves are produced from a moving source. This focuses on the analysis of doppler effect (de) effect on vehicular netwo rk performances several several contributions hav e been propo sed in to enhance t he vanet pe rformance. An analysis of the big bang theory, a theory of the creation of the universe the life of christian johann doppler and his discovery of the doppler effect 676 words.
Roughly speaking, the doppler effect depends only on the relative motion of the source and the observer, not on their absolute state of motion (which is not a well-defined notion in physics) or on their velocity relative to the medium. Perform similar analysis to determine the effect of a moving source on these quantities determine the shifted frequency an observer would detect as the source approaches or recedes derive an expression relating the shifted frequency to the speed of the object and of the wave in the medium. The variation of the doppler factor with the order number of the received wave crest, in the case of a longitudinal doppler effect experiment, involving a stationary source and uniformly accelerating receiver.
Results of these tests indicated that if more time is dedicated to completing a full analysis of all data, this device could indeed be used as an exciting new way to demonstrate the doppler effect. In 1842 an austrian physicist, hans christian doppler, observed and analyzed the same phenomenon for sound emitted by a passing train hence the phenomenon is known as the doppler effect a similar effect is found for the propagation of light and other electromagnetic waves from moving sources. Redshift and blueshift this sound effect was first described by christian andreas doppler in the 1800s and is called the doppler effect since light also emanates in wavelengths, this means. Doppler radar uses the doppler effect to measure the radial velocity of targets in the antenna's directional beam the doppler effect shifts the received frequency up or down based on the radial. The doppler effect doppler effect objectives measure the detector frequency for waves emitted from a slowly moving source as that source is approaching the detector (exploration 1) calculate the detector frequency for waves emitted from a slowly moving source as that source is moving away from the detector.
2 weeks this includes the basic research, recruitment of subjects, experimentation, collection, recording and analysis of data, summary of results and completion of bibliography on the information level, this experiment serves to acquaint students with current information on the doppler effect or. The doppler effect can be described as the effect produced by a moving source of waves in which there is an apparent upward shift in frequency for observers towards whom the source is approaching and an apparent downward shift in frequency for observers from whom the source is receding. A doppler radar is specialized radar that uses the doppler effect to produce data about an objects velocity at a given distance doppler radar works by. Analysis while preserving the micro-doppler effect as shown in fig 1, the radar is stationary and located at the origin q of the radar co-ordinate system (u, v, w.
The doppler effect (or the doppler shift) is the change in frequency or wavelength of a wave in relation to an observer who is moving relative to the wave source it is named after the austrian physicist christian doppler, who described the phenomenon in 1842. This focuses on the analysis of doppler effect (de) effect on vehicular network performances several contributions have been proposed in to enhance the vanet performance in , a new and effective doppler effect compensation scheme for ofdm systems based on constellation estimation is presented. A doppler ultrasound is a quick, painless way to check for problems with blood flow such as deep vein thrombosis (dvt) find out what it is, when you need one, and how it's done.
Effect and explains an everyday occurance involving light or sound waves through an application of the doppler effect support your discussion with evidence from your research. The doppler effect, named for physicist christian doppler, is the apparent change in frequency of a wave through a medium with respect to an observer. Answer: (2) the doppler effect an exciting application of the doppler effect involves the analysis of radiation from distant stars and galaxies in the universe based on the basic elements that compose stars, we know what frequencies of radiation to look for.
The doppler effect is a phenomenon of intrinsic kinematic character this allowed kapoulitsas  to treat in a simple way a generalized doppler effect by supposing that the. Calculations from the doppler effect accurately determine the observer's velocity weather analysis or prediction: -doppler radar uses the doppler effect for electromagnetic waves to predict the weather in astronomy:-the doppler shift for light is used to help astronomers discover new planets and binary stars. The doppler effect is the effect of the velocity of the observer (a) or the wave source (b) on the perceived wavelength the basic fact is that the velocity of a wave, c , is constant in a given medium, and equal to the number of oscillations per second, times the wavelength (length of one oscillation).


This Red LED Pilot Pen and Tablet Stylus has a stylus on one side and the other is a pen that can be opened and pushed in to activate the light. It includes a metal case, 3 replacement batteries, 2 ink refills and a lanyard that connects from your pen to a tablet audio jack to prevent your pen from rolling around the cockpit if it’s dropped.
- PILOT PEN: one side stylus for use with your tablet, other side is pen with red LED light for preseving your night vision
- ACCESSORIES INCLUDED: pilot pen includes the red LED pen, metal carrying case, 2 ink refills, 3 button cell battery refills, and lanyard to attach to tablet audio jack
- VERSATILE: pen can be used as a tablet stylus and lights up with red LED light
- NIGHT VISION: the red LED is perfect for preserving your night vision. Great for pilots, medical personnel, camping, hunting, and military. Deep red color of 670 nanometers wavelength.
- WARRANTY: backed by a 90 day manufacturer warranty


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Alfredo Milani Comparetti
SpeedFan is the popular utility meant for accurately monitoring the status of your computer’s...
...disks, read and monitor
and fan speeds, or...
HWMonitor is a hardware monitoring program that reads PC systems' main health sensors, like CPU temperature...
...sensors, like CPU temperature,
, power consumption, and utilization...
Solve Elec 2.5 is a free educational program to draw and analyze electrical circuits. The program can...
...for current intensities and
defined in the circuit...
SensorsView Pro is intended to provide you with important information about your...
...data about fans and
as well as CPU...
Simplified Office Software - Voltage Drop Calculator
Simplified Office Software Systems
Calculate Amperage, Distance, Wire Size or Voltage Drop. American & Metric measurements & wire sizes...
...Distance, Wire Size or
Drop. American & Metric measurements...
Voltage Drop Calculator
MC Group Inc.
This application could also be called "Feeder Sizer" as it provides all information required...
...the correct wire size.
drop values are updated...
PowerWorld Simulator GSO Education Edition
PowerWorld Simulator GSO Education Edition is a program that can simulate power systems. By using...
...management of interactive high
power systems on any...
New York Mysteries High Voltage Collectors Edition
When a string of strange murders strikes New York City, you are called in to investigate...
When a string of strange murders strikes New York City, you are called in to investigate. Witness...
Electrical Safety Sim Low Voltage Demo
ESSLV gives trainees a place to practice electrical safety through a combination...
Every day, the most serious electrical hazards - arc flash, arc blast and shock - result in...
University of Colorado, Department of Physics
Battery Voltage is an interactive physics simulation. It was written in Java, so it can run both on Windows...
is an interactive physics...
Murata Chip NTC Thermistor Output Voltage Simulator
Murata Manufacturing. Co., Ltd.
This Murata software calculates and simulates the temperature characteristics...
...characteristics of the output
of Murata's Chip NTC...
WireWorld 3D Screensaver
Digital Minds Software
WireWorld 3D Screensaver will electrify your desktop. This unique screensaver will...
...continuous sound of high
electricity running through the...
New York Mysteries: High Voltage Collector's Edition by FIVE-BN GAMES
New York Mysteries: High Voltage Collector's Edition is a point and click, hidden object adventure game...
New York Mysteries: High
Collector's Edition is a point...
EVGA GPU Voltage Tuner
EVGA GPU Voltage Tuner allows you to set a custom voltage level for your GTX 295, 280 or 260 graphics card...
...to set a custom
level for your GTX ...possibly increase your GPU
allowing for higher...
Voltage SecureMail employs proven encryption technologies and innovations that enable global scale deployments...
SecureMail employ ...standard email communication.
SecureMail helps organizations...
We are in CryptoPicture!


Many of us wouldn’t be aware of the fact that there is a legit difference between CCTV and security cameras. This difference varies as per the system, technology, and usage. As these cameras provide us with a sense of safety and security, not only in public places but also in private spaces, the demand for them is increasing day by day. With the help of these cameras, we can keep a check on our surroundings and be aware of unwanted activities. Whether you are running a business or wish to protect your house from burglars, security cameras have become a necessity in today’s world.
However, there is some misunderstanding between CCTVs and security cameras as they are often used interchangeably. So, we are here to clear your doubts and confusion. In this article, we would be learning about CCTV cameras, security cameras, and the major differences between them.
What is a CCTV Camera?
A CCTV camera (Closed Circuit Television) is a type of video surveillance system that uses a closed circuit to transmit video signals from a camera to a designated monitor. This type of camera is usually used for surveillance in public places, commercial and industrial properties, and also, in private homes. CCTV cameras can be wired or wireless and can be used to record footage for future reference. So, if you are looking forward to protecting your house from thieves, trespassers, etc. get the best CCTV cameras for home security right away!
What is a Security Camera?
A security camera is a type of video camera that is used to monitor and record activity in a specific area, such as a home, office, or public space. Cameras such as the Airtel Xsafe 360 Degree Camera can be used for both indoor and outdoor surveillance and are also designed to be discreet. They can be wired or wireless and can be connected to a recording device, such as a DVR or NVR, to capture and store footage for later viewing. Security cameras are commonly used as part of a larger security system, which may include alarms, motion sensors, and other security measures.
Major Differences Between CCTV Cameras and Security Cameras
System: CCTV cameras are part of a closed system that only authorised people can access, while security cameras can be part of an open or closed system.
Recording: CCTV cameras record and store footage on a local device, such as a DVR, while security cameras can store footage locally or remotely, such as on a cloud-based platform.
Installation: CCTV cameras are usually hardwired into a closed system, while security cameras can be wireless or hardwired and can be installed by homeowners, business owners, etc.
Cost: CCTV systems are generally more expensive than standalone security cameras, due to the additional infrastructure required to set up the closed system.
Maintenance: CCTV cameras require regular maintenance, including cleaning and testing, while security cameras may require less maintenance. However, it all depends on the type of camera system.
Analytics: CCTV systems often include analytics software, such as facial recognition or object tracking, while standalone security cameras may not have these features.


Hi, I'm Leon!
I'm a PhD student in Computer Science at Princeton University. I build software. Sometimes hardware. And occasionally other things.
Here are some things I've worked on:
In my free time, I like to contribute to the Tock embedded operating system. It features quite a few interesting concepts and targets microcontrollers with upwards of 64kB RAM. It works on ARM Cortex-M and RISC-V platforms. You should go check it out!
To develop FPGA designs I'm using LiteX, a free and open system-on-chip framework. Over the course of previous projects, I helped integrate a 10 Gigabit Ethernet datapath in the LiteEth IP core and added support for XGMII-interfaced PHYs.
My Linux distribution of choice is NixOS. It's a great fit for desktop and server systems alike! When I see that things are missing or don't work, I occasionally send a pull request.
Whenever there's time, I like to tinker with electronics, networking hardware and servers. I'm especially interested in applications of the Rust programming language, for example in embedded systems. My main area of interest is developing secure, interconnected embedded systems.
Here are some things I've written:
- As part of my master's studies, I've analyzed the synchronization precision achievable through the IEEE 1588 Precision Time Protocol, specifically the impact of embedded operating system design decisions on software-timestamping based implementations. This project used hardware-software co-design, the Tock embedded OS as well as the LiteX SoC framework. The results are presented in a paper.


24) NASA launched the TETR-A satellite just months before the first lunar mission. The proclaimed purpose was to simulate transmissions coming from the moon so that the Houston ground crews (all those employees sitting behind computer screens at Mission Control) could "rehearse" the first moon landing. In other words, though NASA claimed that the satellite crashed shortly before the first lunar mission (a misinformation lie), its real purpose was to relay voice, fuel consumption, altitude, and telemetry data as if the transmissions were coming from an Apollo spacecraft as it neared the moon. Very few NASA employees knew the truth because they believed that the computer and television data they were receiving was the genuine article. Merely a hundred or so knew what was really going on; not tens of thousands as it might first appear.


Solar Damasque Lantern, 23cm
Add a touch of Middle-Eastern style to your garden décor with this unique Damasque LED lantern. With an intricate cut-out pattern covering this charming feature lantern, it also makes a beautiful ornament during the day, when unlit.
Of course, this solar light really comes into its own once darkness falls and the light sensor illuminates the bright white LED housed inside. In direct sunlight, the integrated solar panel effortlessly and efficiently charges the rechargeable battery, which then powers the light. Once illuminated, the intricate patterns cast beautiful shadows into the surrounding area.
Boasting a minimum operating time of 6+ hours when fully charged, this charming solar lantern is made from weather resistant materials and features a strong metal handle, meaning it can be displayed either hanging or freestanding.
Dimensions: 23cm (H) x 22cm (W).


5 Coolest Products From This Year's Consumer Electronics Show
Leaders in the business world tuned in to watch Tom Donohue, President and CEO of the U.S. Chamber of Commerce, deliver his annual State of American Business address on the morning of January 8. The day before however, another important speech was made. President and CEO of the Consumer Electronics Association Gary Shapiro gave the State of the Consumer Electronics Industry address at the 2014 International Consumer Electronics Show (CES) in Las Vegas.
Shapiro’s speech opened this year’s show and highlighted the bright future ahead for the consumer technology industry. He believes the world is “at the forefront of a momentous wave of innovation,” and has high hopes for the industry in 2014. Consumer technology revenues in the United State alone are expected to be $208 billion this year, a 2.4% growth since last year.
For over 40 years, CES has brought together the people and the companies who shape the future of the electronic and technology industries, giving them the opportunity to debut their newest innovations. Among the 150,000 attendees of the four-day convention are over 14,000 CEOs, presidents, and owners of companies big and small—from start-ups to industry leaders like Sony and Cisco. 2014’s International CES is the largest ever, with 3,200 exhibitors covering 2 million square feet of exhibit space.
Some groundbreaking technologies that have been unveiled at CES in the past include:
- 1970 – Video Cassette Recorder (VCR)
- 1981 – Compact Disc Player
- 1994 – Digital Satellite System
- 2001 – Microsoft Xbox
- 2010 – Tablets, Netbooks, and Android Devices
- 2013 – Driverless Car Technology
What will the next big thing be? Will it be Samsung’s bendable TV; Intel’s smart earbuds that track speed, location, and heart rate; or the TouchJet PTE that transforms a blank wall into an interactive tablet? Or will the biggest technology from this year’s show be in the automotive industry, such as Audi’s 90 mpg hybrid car with laser headlight capacity of 1/3 of a mile or Formula E’s electric racing car?
Here are five of the 20,000 products introduced at this year’s show that particularly stood out:
- AT&T and GM’s 4G LTE in cars: There will be Wi-Fi connectivity and access to vehicle-specific apps right in the car’s dashboard in select Chevrolet 2015 models; other auto manufacturers are close behind GM in adding this feature to their models.
- Sugar Lab’s 3D printer: This device makes custom cakes that are entirely edible and don’t have to be baked.
- Sony’s web-based TV service: With live-streamed, pay-TV online included on Sony TVs and PlayStatione game consoles, this service could be a disruptive opportunity in the market for cable and satellite TV providers.
- Ford’s solar-powered car: We’ve seen electric and hybrid cars, but Ford’s C-MAX Solar Energy concept car is something different. Its rooftop solar panels glean enough of the sun’s energy to effectively make it a mobile recharging station, enabling the car to run for short trips without any other power source. For longer rides, the car’s conventional engine will extend the C-MAX’s range to 620 miles.
- Clearview’s invisible speaker: The days of big, bulky speakers may be numbered with the introduction of this clear, wireless, paper-thin speaker.
During his keynote address, Cisco’s Chairman and CEO, John Chambers, specifically predicted 2014 will be a pivotal year for the Internet of Things. Everything—people, processes, data, and objects—will soon be connected. He said, “The Internet of Things will be five to ten times more impactful in the next decade than the entire internet has been to date.”
The world will for sure see big advances in technology this year.
Photo credit: David Berkowitz, 2012. License.


USB Rechargeable Power Bank with Cord for Portable Power for Fontanini StablesHouse of Fontanini
USB Rechargeable Power Bank with Cord for Portable Power for Fontanini Stables.
USB RECHARGEABLE POWER BANK
W/BATTERY and CORD
|To be used with Stables from year 2020 and newer
|to connect to USB rice light connection.
Not included with stable. Optional Accessory. This allows
for portable power when a plug-in is not near the stable.
|LI-ION BATTERY/ IRON/ALUMINUM
|USB CORD WITH LOW VOLTAGE ADAPTOR


NASA wants to build a "Cloud City"
The High Altitude Venus Operational Concept -- HAVOC -- is a conceptual spacecraft designed by a team at the Systems Analysis and Concepts Directorate at NASA Langley Research Center for the purposes of Venusian exploration. This lighter-than-air rocket would be designed to sit above the acidic clouds for a period of around 30 days, allowing a team of astronauts to collect data about the planet's atmosphere.
O.M.G., this is bad. Little did I know that the slowly dwindling stockpile of Halloween candy in my pantry could be the last we see of . . . CHOCOLATE! NO!!!!!


Developer with a twist of data scientist at Ubiquisense
You will be part of a unique team of dedicated, intelligent, and creative develop engineers who work with UbiqiSense's state of the art of Internet of Things (IoT) sensing solutions for smart Buildings. UbiqiSense’s proprietary architecture delivers rich data to the cloud about what goes on in a building, not least about how many, when, where etc. The use cases for the sensor data are endless, and today the company is involved with lots of very different customers, who demand a solution, which is more and more customized.
In a short time, you are expected to become one of the best within the development in Python.
The UbiqiSense office is right in the heart of downtown Copenhagen, and you will be surrounded by a team of smart people on a mission to create something disruptive. In this job you will have the opportunity to influence the future developments both regarding your own work day but also the success of the Company.


Glucovation’s CGM sensor detects glucose electrochemically via a proprietary non-enzymatic sensing technology. The sensor is painlessly inserted transcutaneously via a simplified “place and go” applicator and measures glucose in the interstitial fluid; the signal will be converted and then transmitted wirelessly to an existing commercial display device (phone, pad, or watch). Glucovation is focused on developing a system that requires no calibration yet is highly accurate for use in the medical and consumer markets. Glucovation is considering several strategic relationships with international manufacturing, development and distribution partners that are best of class. We will use these relationships to scale very quickly and deliver a solution that is unmatched in the market. With the nearly epidemic growth in diabetes, we are committed to delivering a solution that is easy to use, highest quality, best accuracy, and at a cost structure that will be very disruptive to the market.


It is quite frustrating when I need proper equipment to get certain things going, and am willing to pay a fair price, but sometimes solutions seem to be missing.
I checked all the game capture devices (for recording gameplay footage as video) that I could find, but – as so often – it’s a mix of up- and downsides, and generally they’re all primarily designed for gaming consoles, for standard entertainment.
Here’s what I am willing to pay for:
Playing games on my PC, in the native resolution of my monitor, which is 2560×1440. The screen data being grabbed hardware-side, latency free, so basically via the standard video cable. I chose a monitor that doesn’t have an HDMI input, only DVI and DisplayPort, so that would have to work, too. And then the device saves the video data via USB onto an external storage – harddisk or flash card or even USB stick.
And here are all the problems:
1) All devices I could find are capped at 1920×1080. One can at least record this in 60p, but resolution is still limited. Apparently they also don’t support higher input resolution and downscaling for the video compression. So I’d have to play games I want to record in 1920×1080.
2) They all operate based on HDMI as digital interface. I suspect this is some kind of legal mandate so that people cannot use such devices to record HDCP-protected content – because if you use DVI or DisplayPort, if copy protection is there, it cannot be obeyed. I guess we have to thank that whole movie and music industry lobbying for this technical limitation.
3) You can adapt DisplayPort down to HDMI and HDMI down to DVI. But I’d have to first figure out whether this is also handled well by the recording devices. And even if that works, then the next problem arises…
4) I have connected my monitor using DVI because that interface causes Windows to reserve active desktop space for it, to always keep the device registered as present. When I initially connected my monitor using DP, I noticed that whenever I turned it off – only with the button on the front, not with the power switch, the display would immediately get removed as system component, and because I am also using a digitizer display and have arranged both a certain way, this will (and it’s a Windows fault) eventually lead to mixup of the numbering and the alignment of the two displays. It would be even more hassle than what I already have anyway.
(If I have the nerve, I might eventually experiment some more and see whether I can find a compromise.)
5) So even if all that works: It seems people using game capture devices are typically the invested gamers with a very powerful gaming PC. Mine isn’t weak, but it’s also not super-powered, and what bothers me is that while the CPU load for the video compression is then taken off by the capture device (or in some cases just most of it), based on past experience I would almost bet that transferring several MB/s of data via USB and then burdening the CPU with the I/O interrupt load of saving that stream onto local harddisk will cause noticeable interference in my games. Because it has always appalled me how even today, harddisk work can have such an interfering influence on unrelated processes.
To give you a comparative example: Remember how when you used an optical disc drive and every time you put in a CD or DVD, the whole frickin system would pause until the media had spun up? This is the kind of crap one still has to expect to happen.
6) And then you’d think that the immensely valuable feature of having a hardware button on the device for starting and stopping recording would be mandatory, but only some devices have it. More generally, even if all the previous problems were resolved, then there would be the whole pile of the usual potential issues with electronic products: bugs in software, inconvenient handling etc..
This is really a crappy situation, but I don’t take fault with my end just because I like to use modern technologies that don’t fit the bread&butter mainstream.
Even equipping my old PC with a video recording card would not be a good solution, because then I’d have to have that one running all the time so that the video signal can be passed through.
I now figured out that apparently harddisk I/O is not or only a minor problem. The issue is that the hardware encoding, at least when performed with Open Broadcaster Software, is optimized for 1080p. 1440p is larger, but not extremely so, yet a demanding game like Planetside 2 runs really unplayably when recording it in 1440p, but when in 1080p and recording, you rarely notice any interference. That distinct difference doesn’t seems to be just the computing load difference. Encoding bitrate doesn’t affect the results. I even recorded in 720p and had worse results. It’s all a bit confuse, but that only further underlines the point I’m making about the lack of proper hardware solutions.
I was willing to give nVidia Shadowplay a try, since it supports the (fullscreen only – which is fine) high performance mode with low system impact. But for that, I’d have had to install geForce Experience, which turned out to be a Big Brother total data collecting and activity tracing software, and I’m not willing to pay that price for a software that might not even be better than OBS in game capture mode, for example.
For recording 1440p I probably simply would need a more powerful PC that can run a recorded game in around 60 fps all the time. This of course could save the investment in a game capture device, but I’m not willing/able to experiment with money like that.
I now tested recording to replay buffer, meaning that there’s no harddisk writes involved during the recording. It just captures and encoded and stores it in memory. And even there, the same happens as with conventional game recording with any codec in OBS: Jaggy motion. Interuptions in video fludity. The game itself is not affected except showing a slight framerate reduction and less-than-perfect fluidity based on framerate fluctuation. But it’s nowhere as bad as the video output, which studders and sometimes even hangs, having dropouts. I’m tiring of this lack of a proper solution. I’d love to just connect a hardware device to one of my free graphics card outputs, connect a USB harddisk to that one, and then record 1440p 60 fps just as it looks in the game, without any interference or hassle.
I’m beginning to suspect that the hardware encoding assistance gets overloaded and then doesn’t share the burden software-side. Because when I play a game in 1080p and get constant 60 fps, I can record nearly flawless 30 fps video from that. But once I record to 60 fps, it is mostly fluid with some nasty dropouts during fast movements. And this even happens in old and unburdening games like Half-Life 2, despite the CPU load for recording 1440p 60 fps being a mere 38%, which should not be a problem in combination with such an old game.


Giving light a new experience with this LED design lamp
A sophisticated design by day with inviting light by night. This gorgeous dimmable white Philips Ledino wall spot light provides powerful warm white LED light. Direct the light where you need it with the rotatable spot head.
Elegant design meets innovative technology
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Sustainable light solutions
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Light and design
This design lamp has light with a minimalist essence that defies traditional boundaries, creating light and lightforms of inspiring purity and beauty.
Warm white light
This light uses the very latest lighting technology by Philips with the new warm white state-of-the-art high power LEDs providing a glow of light with a colour temperature of 2700 Kelvin.
High light quality
An LED lighting module of 7.5 W produces a light output equivalent to a 40-W incandescent bulb (350 Lumen). Save energy with strong light output.
Adjust the light intensity of the Philips LED lights with a dimmer switch (not included). This makes this light ideal for creating an ambience for any occasion, whether a cosy meal à deux or chilling out with family and friends in your living room. Philips tested a number of wall dimmers that have proved to be compliant with our LED lights. A list of compatible dimmers is available in the downloads and support section.
Extremely long operating life
A light source you can trust. Philips LED lights offer an extremely long life of at least 20,000 hours (which equals 20 years on the basis of an average use of 3 hours/day with at least 13,000 on/off switching cycles). With Philips LED lights you won't have to worry about maintenance or lamp replacement while having the perfect light ambience in your home.
Saves up to 80% energy
The LED lighting technology used in Philips lighting fixtures is highly energy-efficient (7.5 W module produces 350 Lumen). As a result, every lighting fixture conserves energy, helping consumers to save money on their electricity bills and contribute to preserving the environment. For home lighting that's energy-efficient and provides great light in a range of contemporary designs, look for Philips LED products.
|Suitable for indoor use||Y|
|Product type||Surfaced lighting spot|
|Suitable for rooms||Bedroom,Living room|
|International Protection (IP) code||IP20|
|Included bulb power||7.5 W|
|Number of bulbs||2 bulb(s)|
|Light colour||Warm white|
|Colour temperature (max)||2700 K|
|Bulb lifetime||20000 h|
|Replacement bulb power (max)||7.5 W|
|Extra low voltage||Y|
|Wall dimmer compatibility||Y|
|Power source type||AC|
|Input voltage||220-240 V|
|AC input frequency||50/60 Hz|
|Weight & dimensions|
|Package height||138 mm|
|Package length||19.3 cm|
|Package width||103 mm|
|Package weight||1.5 kg|


|Country of Origin
|Made in India
DD Copper Wire in Coil is a high-quality electrical conductor designed for various applications. Crafted from durable copper, it comes in a coil form for easy handling and deployment. The Double-D (DD) design ensures efficient conductivity, making it suitable for electrical wiring in diverse settings. Copper's excellent conductivity and thermal performance make this wire ideal for power transmission and distribution systems. The coil form allows for convenient storage and unwinding during installation. Whether used in residential wiring or industrial applications, DD Copper Wire in Coil offers reliability, longevity, and efficient electrical conductivity, ensuring optimal performance in diverse electrical setups.


Reaching The Singularity May Be Humanitys Greatest And Last Accomplishment
More problematically for the singularity, these kinds of extrapolations derive much of their overall exponential shape from supposing that there will be a constant supply of increasingly more powerful computing capabilities. To achieve the singularity, it isn’t enough to just run today’s software faster. We would also need to build smarter and more capable software programs.
If the singularity is going to occur on anything like Kurzweil’s timeline, though, then we absolutely require a massive acceleration of our scientific progress in understanding every facet of the human brain. Spectre is the first commercially available case with both water-cooling and full cable management integration. For over a decade Singularity Computers has been building high end custom water-cooled PCs, Spectre is the result of our experience.
Kurzweil’s reasoning rests on the Law of Accelerating Returns and its siblings, but these are not physical laws. They are assertions about how past rates of scientific and technical progress can predict the future rate. Therefore, like other attempts to forecast the future from the past, these “laws” will work until they don’t.
On top of that, robots have made automation a reality for jobs ranging from building automobiles to constructing computer chips. It’s a common theme in science fiction — mankind struggles to survive in a dystopian futuristic society. Scientists discover too late that their machines are too powerful to control.
Throughout his career, he served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. During his secondment, he led the technology strategy of a regional telco while reporting to the CEO. He has also led commercial growth of AI companies that reached from 0 to 7 figure revenues within months. Cem regularly speaks at international conferences on artificial intelligence and machine learning.
Some of them are technically necessary , others help us improve our website and to offer you a better user experience. Beyond merely extending the operational life of the physical body, Jaron Lanier argues for a form of immortality called “Digital Ascension” that involves “people dying in the flesh and being uploaded into a computer and remaining conscious.” K. Eric Drexler, one of the founders of nanotechnology, postulated cell repair devices, including ones operating within cells and utilizing as yet hypothetical biological machines, in his 1986 book Engines of Creation. In a hard takeoff scenario, an AGI rapidly self-improves, “taking control” of the world , too quickly for significant human-initiated error correction or for a gradual tuning of the AGI’s goals. In a soft takeoff scenario, AGI still becomes far more powerful than humanity, but at a human-like pace , on a timescale where ongoing human interaction and correction can effectively steer the AGI’s development. In addition, some argue that we are already in the midst of a major evolutionary transition that merges technology, biology, and society.


What is 5G technology and what will its impact be like in our everyday life?
5G technology, or the fifth generation of mobile connections, will play a key role in Robotics and the Internet of Things (IoT) and the development of smart cities, and it is closer than ever.
Consumers and businesses consider mobile connectivity essential. 5G, the next generation of mobile wireless network technology, which is expected to commence rollout in some countries from 2020, will improve consumer experiences and business utility through faster data transmission and more reliable connectivity.
5G also represents a step-change from previous generations of mobile technology by enabling lower latency—the time it takes for signals to travel through the network. This gives it a wider range of applications by providing the responsive digital technology required to support innovations such as robotics and the Internet of Things (IoT).
5G—faster, better and different
As the next generation of mobile wireless network technology, 5G will provide a better consumer experience and improve business utility through faster data transmission and more reliable connectivity. For example, 4G technology allows download speeds of 100 megabits per second (Mbps), while 5G could potentially enable speeds of more than 1,000 Mbps. It currently takes about eight minutes to download a feature movie using 4G; people could be able to do this in seconds with 5G.
These features, combined with its lower latency—the time it takes for signals to travel through the network—meaning that 5G represents a substantial step change compared to previous generations, with the promise of a vastly increased range of applications. This reduced latency will, for example, allow the responsive digital technology—particularly for spatial applications—required to support robotics and the Internet of Things (IoT).
While 5G will be an advance on previous mobile technology, the wide array of potential uses means that it may develop as a ‘general-purpose technology’ (GPT)—such as electricity or the internet—that becomes ubiquitous in its own right. In any event, 5G is likely to:
- Support the introduction of new goods and services, with higher data rates and lower latency expected to enable greater use of IoT devices.
- Improve business efficiency in producing and delivering goods and services and enable scope for greater innovation and the development of new products. For example, faster download speeds and lower latency will make cloud computing more effective and allow for better collection and analysis of big data that can lead to more real-time decision making.
- Improve health and social outcomes. For example, wearable technology and IoT devices will help people better access health and education services in a more timely and personalized fashion— the gains from which will have a flow-on effect and will largely accrue to individuals.
Ways 5G Will Impact Marketing and Advertising
NEW ADVERTISING ARCHITECTURE
Advertising infrastructures will need to be re-invented
“5G will blow up the architectures we have.”
Ad exchange OpenX Chief Product Officer Todd Parsons said, since
Present-day programmatic technologies aren’t built for the demands of a system that delivers ads up to a hundred times faster.
David Zapletal, EVP of Media Operations at media holding company Digital Remedy, points out that “the industry needs to prepare” for 5G in other ways as well, such as updating creative specs on ad formats and file sizes.
And those are only some of the “first-order effects.” Greenblatt expects the biggest surprises will be in the “second-order effects,” the way 4G led to the crash in the price of taxicab medallions because of the rise of wireless-managed fleets from Uber and Lyft.
FATTER PIPES MEAN MORE DYNAMIC CREATIVE
Over the past few years, an avalanche of exciting new technologies and formats have hit the market, but these have often been met with very little uptake from advertisers, mostly due to issues relating to speed.
However, with 5G set to upturn how advertisers think about creativity, users’ experience of these engaging formats could all be about to change.
5G could boost device speeds twenty-two fold from 45Mbps, up to a maximum of one gigabit. That means response times of a couple of milliseconds, and minimal latency, even in much more demanding rich-media formats. That opens the door for exciting, buffer-free content and much more space for new tech – whether that’s more and better video content creation or deeper exploration of augmented and virtual reality.
REACH ACROSS CHANNELS
5G won’t just help with ad creative – it’ll also help advertisers better reach audiences, creating a growing swatch of channels available to advertisers to connect directly with consumers.
A lack of connectivity and sluggish speeds have previously limited the extent of targeting across devices – and a knock-on effect was no doubt the rather glacial pace of IoT adoption in recent years.
But cloud-based processing enabled by 5G networks will boost speeds and connectivity massively, pushing IoT past its break-even point. Mobile networks will move from the back of the pack in speed terms to right at the front, way ahead of traditional wired connections.
Because 5G boasts much faster connection speeds, it allows devices to offload processing into the cloud. In doing so, power-hungry processors will no longer drain device batteries, meaning that more devices (particularly remote, inaccessible, or mobile devices) will become connected.
And, beyond just bettering existing devices, faster speeds and improved connectivity will open the door for a panoply of new ones. That means connected fridges, cars, DOOH displays – you name it. With 5G, anything can become a channel to reach consumers.
Perhaps the largest impact 5G will have is on the quantity and quality of data circulating around the ecosystem which, with appropriate permissions, will be usable by advertisers to better target more scalable audiences than ever before. That’s a fantastic opportunity to look at audiences in a much more detailed and granular way.
But to really harness all that new data flying around, it’s crucial to make sure all these various points are connected and used in an optimal way – that means the right infrastructure, the right technology partners, and the right kind of privacy measures. So, in the run-up to ‘5G Day’, marketers should make sure they’re having conversations with all the various stakeholders to adopt processes that allow them to be able to use that valuable data in a privacy-by-design way.
Mobile video ad spending jumped 80.6% in 2015, according to eMarketer and from 2015 to 2019 it skyrocketed. That occurred with so-so 4G connections. With 5G, consumers will be able to download a 4K movie in a few minutes or at one-twentieth of the time it takes to do so with 4G. For advertisers, this means that video will become a much more targeted medium. Freed from the relative sluggishness of 4G connections, marketers will be able to offer audiences rich video experiences on mobile that they cannot today.
5G will also make it possible to push personalized video content delivered through programmatic. True personalization requires data and content that can be delivered in a 5G world. Marketing will become more about engineering wins during the micro-moments of decision and influence. Marketing is beginning to embrace this change, but 5G will turbocharge it.
OOH (Out of Home) WILL GROW AND BECOME MORE INTERACTIVE
5G is geared up to bring outdoor display units into interactive ad screens, just like mobile phones — only larger.
It’s important for businesses to evaluate what technology can do for them. Outdoor display asset owners, for example, need to think about replacing their units to capitalize on the digital era.
As soon as 5G makes a commercial entry into the marketplace, it’s going to create new and exciting opportunities for companies to reach consumers — via interactive and engaging advertisements. Planning ahead will help industry participants across the board.
Those that are able to leverage that opportunity will delight customers and wow them with innovative advertising that makes an immediate impact on revenues.
5 ways 5G will impact retail
It is the ideal time for retailers to start planning how their stores and interfaces will look when 5G becomes widely available.
Connectivity in our physical stores means devices that can constantly exchange data with each other – also known as those under the header of the Internet of Things (IoT). To do so, they need a fast, reliable network that doesn’t require too much power. 5G networks will achieve a 90% reduction in power consumption, guaranteeing up to 10 years of battery life for low power IoT devices.
This means, for example, that more retailers will have access to smart shelves like the ones Amazon implemented in its Amazon Go stores. This technology uses dozens of sensors to provide real-time inventory visibility and update pricing according to demand.
Key tech involved: dynamic pricing, automated checkouts, connected fitting rooms, automatic replenishment.
Augmented and virtual realities use a lot of processing power and cellular data. With the increased capacity of 5G networks, retailers will be able to create richer, more detailed experiences when integrating their physical and digital worlds. This will make technologies that we’re already experimenting with, and seeing consumer adoption of, only more of a possibility. The result will mean shoppers are able to immediately check product materials or ingredients through the use of smart glasses or their smartphones, for instance. Those same apps will also guide customers to the products they want by projecting directions into their field of view in real-time as they navigate the store space.
Key tech involved: immersive interfaces, gamification, wayfinding
Artificial intelligence will also thrive on IoT devices via 5G. That’s not to say the AI algorithms themselves will change, but that the higher network will enable more accurate real-time data to flow, ultimately facilitating smarter systems. In retail, for instance, managers will be able to delegate more operational and inventory decisions to automation. This means greater efficiencies as well as accuracies on things like forecasting inventory quantities so as to optimize stock levels, leaving sales associates to spend more time on customer care. Having stock in the right place at the right time will also decrease the risk of losing customers to competitors, as product availability will be more accurate.
Key tech involved: retail analytics, inventory visibility, demand forecasting, endless aisle
With lower latency, retailers will also be able to respond to purchasing patterns and behaviors with immersive, tailored content in real-time. Implementing 5G in-store will allow for greater interactions and data collections between sales associates and customers. Real-time data could be tracked to create personalized adverts or offers based on the preferences of individual customers, helping to increase the incentive to buy.
Key tech involved: marketing automation, personalized promotions, AI recommendations, product search tools, clienteling.
The implementation of 5G will also revolutionize logistics by improving efficiency in fulfillment tasks and increasing the speed of transportation. Greater connectivity and improved reliability will help communications between brands, couriers, and consumers. The full capacity of 5G will eventually also enable the rollout of automation in transport and warehouses, thanks to improved processing of the vast amounts of data required in real-time.
Key tech involved: smart warehousing, robotics, automated vehicles
Seamless, personalized customer journeys will reach the next level
Some of the terms and technology relevant to 5G
The Internet of Things (IoT) is a generic term describing the practice of adding internet-connected sensors and controllers to objects, infrastructure or locations and using the data to provide an improved service or capability. The deployment of IoT sensors is already well-advanced in some sectors but 5G is expected to accelerate the uptake of IoT.
Massive machine type communications (mMTC) is the automatic and real-time communications between IoT-enabled devices. The ability for these devices to communicate with each other is expected to drive productivity growth through the automation of business processes.
Network slicing refers to the partition of 5G networks to provide dedicated capacity for particular technologies. For example, network slicing of 5G could provide dedicated resources to IoT devices to ensure that they work effectively in particular areas or for particular industries. Network slicing may also allow for the sharing of a capital-intensive 5G network between many operators.
Impacts of 5G on productivity and economic growth – Bureau of Communications and Arts Research, Department of Communications and Arts, Australia
Mark Collins, Arnab Das, Alexandre Ménard, and Dev Patel – Mckinsey & Company
Don Rosenberg, Executive Vice-President, General Counsel and Corporate Secretary, Qualcomm
World Economic Forum


Mobile, dependable, clean off-grid clean power solutions
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With a nominal power of 600 W and a maximum speed of 130 mph, the Nemoi S offers reliable, affordable clean energy generation for low-consumption applications.
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Heating and Air Conditioning
Part of home automation is the heating and air conditioning. Thermostats are common home automation products, and they do much for the system. And yet, they are often lacking in some way. Some thermostats do not have any programming ability, so you cannot preset them. Others are better and allow you to set them to certain temperatures at certain times of day, but they still must always be monitored. To improve your home automation system, replace your thermostat with a smart thermostat. A smart thermostat can not only be programmed, it can actually learn from your daily behaviors. It can also sense when there’s nobody in the room and reduce the heat to conserve energy, or turn up the heat when people walk in unexpectedly. With a better thermostat, your home automation system will already be better as a whole.


The measurement postulate is crucial for quantum mechanics. If we measure a quantum system, we can only get one of the eigenvalues ââof the measured observable, like position, energy, etc., with a probability. Immediately after the measurement, the system will instantly collapse into the corresponding clean state, called collapse state. It is argued that the non-cloning theorem is in fact the result of the measurement postulate, since the non-cloning theorem would also be valid in classical physics. The possibility of cloning in classical physics is in fact the ability to fully measure a classical system, so that a classical state can be measured and prepared. .
To clearly explain the measurement in quantum mechanics, it is better to use the following example. Suppose a photon passes through three identical slits and we place an ideal and non-demolition detector after each of the slits. According to the measurement postulate, one of the detectors will detect the photon and therefore the entire wave function will collapse in that slit.
What will happen if we only place one detector after the top slit? It is natural to think that it will have a one-third probability of detecting the photon and reduce the entire wave function in slit-1, as shown in Figure 2. However, what if the upper slit detector does not measure the photon? This is a partial measure. This was encountered in the formalism of duality quantum computing, where the linear combination of units (LCU) was proposed to perform quantum computing .
In Ref. , using the LCU formalism [2,4,5], Long proposed that when measuring a partial wave, something will surely happen: (1) collapse: it will collapse into one of the eigenvalues ââwith a certain probability. After the measurement, the whole wave function will instantly change to the corresponding eigenstate; (2) collapse: the measured wave function will disappear and switch to the unmeasured part. As shown in Figure 2, the detector will measure the photon with a probability of 1/3, and the entire wave function of the photon will collapse in the supper slit. As shown in Fig. 3 for the collapse, the part measured in the upper slit disappears and the unmeasured part, namely the wave function in the middle slit and the lower slit, increases.
In reality, partial measurement is more common than full measurement. It should be noted that the collapse and collapse of a partial measure occurs randomly not only in space, but also in time. For example, the detection of photons by a detector is naturally apprehended from this postulate of partial measurement. When the wave function of a photon goes to a detector, it is not fully measured at the same time, i.e. it is not a full measurement. Its front end first arrives at the detector, hitting an area of ââthe detector. It either collapses at any point of the intersection zone in the detector or collapses and the corresponding probability will be shifted to another part of the wave function. This process continues until the photon is detected. If the photon was not detected before the last part of the wave function reaches the detector, then the amplitude of this remaining wave function increases to 1 in order to detect the photon with certainty at the final step.
This explanation is given from the point of view that the wave function is only the entity of the quantum system itself, the WISE interpretation [2,6]. In the WISE interpretation, there is NO relationship between the wave function and the quantum system, the wave function IS just the quantum system. The interpretation of WISE is supported by the experience of delayed choice of encounter , which was reported in various media a few years ago .
 Shen, Y., Hao, L. and Long Gui-Lu. (2011). Why can we copy classic information? Chinese letters of physics, 28 (1), 010306.
 Long, Gui-Lu. (2006). General principle of quantum interference and duality computer. Communications in Theoretical Physics, 45 (5), 825.
 Long, GL, (2021) Collapse-in and Collapse-out in partial measurement in quantum mechanics and its WISE interpretation, SCIENCE CHINA Physics, Mechanics & Astronomy, https: /
 Long, Gui-Lu. & Liu, Y. (2008). Duality calculus in quantum computers. Communications in Theoretical Physics, 50 (6), 1303.
 Long, Gui-Lu, Liu, Y., & Wang, C. (2009). Admissible generalized quantum gates. Communications in Theoretical Physics, 51 (1), 65.
 Long, G., Qin, W., Yang, Z. and Li, JL (2018). Realistic interpretation of quantum mechanics and a delayed encounter-choice experiment. SCIENCE CHINA Physics, Mechanics & Astronomy, 61 (3), 030311.
 https: /
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Artificial intelligence (AI) is increasingly being built for and deployed in high-stakes domains such as detecting cancer from medical imagery
With explainability and interpretability of AI becoming increasingly important, ML researchers designed a wide range of techniques from visualizing what the model has learned from an entire dataset, known as feature visualizations
Our primary research questions are:
We address these two research questions through two studies. First conduct a small, empirical study to understand how current state-of-the-art object detection models compare to human attention. In the second study, we evaluate the impact of novel human-centered, data augmentations on DNNs saliency maps. Our novel contributions include:
Several explainable artificial intelligence (AI) techniques have been proposed as new ways to provide insights into the AI’s prediction. Such techniques for computer vision tasks traditionally are presented as a heat map, highlighting the regions that most contributed to the model’s prediction. However, several empirical studies in human-computer interaction literature have evaluated the interpretability of different techniques and their impact on decision-making. We present different saliency map techniques and perform empirical studies on different saliency map techniques.
With novel interpretability techniques increasingly being developed, some researchers are taking a cognitive science approach to interpretability to understand how human attention compares to deep learning models. One study investigates if DNNs look at the same regions humans do in a visual question answering task
Recently, papers have proposed various routes to make saliency maps more human-centered and semantically meaningful to humans. For example, Boyd et al., propose a novel loss function that uses human annotations
Instead of continuously having to collect human annotations, the MIT/Tuebingen Saliency Benchmark has designed a challenge for saliency prediction models. This benchmark has yielded several techniques that can avoid the need for human subjects to obtain approximate ground truth human attention maps
We conducted two studies to address our research questions. Below we describe each study and how the second study uses results from the first study.
We conducted an empirical study to gain an understanding of which state-of-the-art object detection models currently generate saliency maps similar to human attention. We evaluated and compared saliency maps generated by seven different object detection models available on PyTorch to human attention maps and predicted human eye-fixations. To obtain the human attention maps, we used the human attention maps for PASCAL2012 from the ML-Interpretability-Evaluation-Benchmark
We generated a saliency map for every single image that had an associated human attention map (ground truth saliency) from the ML-Interpretability-Evaluation-Benchmark
Each image was resized to \(512\) x \(512\)
before being evaluated on by the model. The saliency map for the object detection model is generated using the EigenCAM method (
While the MAE to some extent can reveal how similar the saliency maps are, we also calculate Intersection over Union (IoU) between the top \(90\%\) salient pixels of the generated saliency map and the top \(90\%\) salient pixels from the human attention map/predicted human eye-fixation. Calculating the IoU will help reveal if the most salient region identified by the model and the humans align
Data augmentation for object detection is slightly more complex than data augmentation for image classification tasks because of the associated bounding boxes for each object
We designed three different data augmentation techniques: selective erasing, selective inpainting, and non-trivial transformations. Below, we define and provide examples of each of these data augmentations.
The goal of selective erasing is to get rid of potential spurious patterns, patterns that the model has learned to associate with a label even though it does not represent that label. In order to augment images using selective erasing, we send the image through Faster R-CNN and use EigenCAM to generate the saliency map from layer 4 in the backbone. We then send the image through the DeepGazeIIE model to generated the predicted eye-fixations map. We calculate the intersection over union (IoU) between the two saliency maps. If the IoU is below 0.1, meaning the two saliency maps are significantly different from one another, then we erase the top 2.5% salient pixels identified from the Faster R-CNN saliency map from the original image. We identified 6476 images that met this criteria. An example of this process and the outcomes from each step are shown in Figure 4. We chose the top 2.5% because these pixels would most likely make up the core region of a potentially spurious region.
The selective inpainting augmentation process follows the same steps as selective erasing and then inpaints the erased image. To inpaint the top 2.5% salient pixels as denoted by Faster R-CNN, we send the selective erased image and mask into an untrained neural network and optimize on learning the pixels that minimize the chosen loss function. This idea is presented in the Deep Image Prior Paper
Data augmentation can improve performance and outcomes of models as it can add new and different examples to the training dataset. If the dataset in a model can be more rich and sufficient with the augmentation techniques, the model can perform better. To improve the model generalization, we apply the following augmentation techniques seen in Figure 5. In our experiment, we do experiments of bounding box geometric augmentation, color augmentation, and geometric augmentation. Augmentations considered in this experiment are from the PIL.ImageOps as well as torchvision.transforms libraries. The source codes are from the following repos: imgaug and AutoAugment for Detection Implementation with Pytorch. Each image in the dataset was augmented only once with a random augmentation selected from Figure 5. This was to ensure we had the same amount of data to fine-tune on as the other augmentation techniques.
We gather a baseline to compare our three different data augmentations against. In Figure 6, we show the pipeline we used for the baseline. We fine-tuned Faster R-CNN on our PASCAL2012VOC training set and save the model to later evaluate it on our PASCALVOC2012 test set. During evaluation we calculate the mean average precision (mAP) at IoU of 0.5. We also calculate the MAE and IoU between the saliency maps generated by the saved model and the predicted eye-fixations. We again calculate those metrics for the saliency maps generated by the model and the human attention masks.
For evaluating the impact of data augmentation, we created three different augmented PASCALVOC2012 training sets, one for each augmentation. Then we separately fine-tuned the pre-trained Faster R-CNN on each augmented dataset (shown in Figure 7). We do the same metric calculations as we did for the baseline model (mAP, IoU, and MAE).
For all fine-tuning, we used the following training parameters: 5 epochs, learning rate of 0.005, SGD optimizer with momentum set to 0.9 and weight decay set to 5e-4, and the StepLR learning rate scheduler with a step size of 2 and a gamma of 0.1.
We present results from our empirical study and our main experiment which evaluates the impact of different data augmentation techniques. The empirical study was done to get a glimpse at how current saliency maps from state-of-the-art models compare to predicted and ground truth human attention. The main experiment extends the empirical study by evaluating the impact of different data augmentation techniques on the saliency maps.
Results for comparing the saliency maps generated by object detection models to the DeepGazeIIE’s predicted eye-fixations on the MIT1003 dataset
We observed that the SSD with a VGG backbone generated saliency maps most similar to predicted eye-fixations in terms of the IoU metric with a value of $0.2379$. DETR, a transformer-based architecture, generated saliency maps most similar to the predicted eye-fixations in terms of the MAE metric with a value of $0.1275$.
Table 1: Object Detection Models compared to DeepGazeIIE Predicted Eye-Fixations for MIT1003
Example Saliency Map Results
We also conducted the same study between the saliency maps from the models and the predicted eye-fixations as well as ground truth for a subset of PASCALVOC2012. This subset was determined based on the PASCALVOC2012 images that had a ground truth human attention map in the ML Interpretability Evaluation Benchmark. We observed that Faster R-CNN with a ResNet50 backbone generated saliency maps most similar to the predicted eye-fixations and the human attention masks in terms of MAE with values of $0.1700$ and $0.1145$ respectively. In terms of IoU, the SSD with a VGG backbone generated saliency maps most similar to the predicted eye-fixations and human attention masks with values of $0.2474$ and $0.3225$ respectively.
Table 2: Object Detection Models compared to DeepGazeIIE Predicted Eye-Fixations for PASCALVOC2012
Example Saliency Map Results
Table 3: Object Detection Models compared to Human Attention Masks for PASCALVOC2012
Example Saliency Map Results
We identify a top preforming model in terms of MAE because this metric is not variable based on a threshold like IoU. We selected the top performing model for our main experiment to focus on the impact of the augmentations for one model instead of comparing the impact of augmentations across different models. Since Faster R-CNN performed the best for MAE on PASCALVOC2012, we use this model in our main experiment.
We separately fine-tune a pre-trained Faster R-CNN on each data augmentation technique and with no data augmentation and then evaluate that model on the test images. We calculate mean average precision to understand the performance of each model and we calculate mean absolute error and intersection over union between the saliency maps generated by the model and the predicted eye-fixations or human attention masks.
The Faster R-CNN generated saliency maps that were more similar to predicted eye-fixations in terms of MAE when using selective inpainting augmentation and in terms of IoU when using selective erasing. These augmentations impacted the mAP by at most 3%.
Table 4: Pre-trained Faster R-CNN Fine-tuned on PASCALVOC2012 Compared to Predicted Eye-Fixations
Table 5: Pre-trained Faster R-CNN Fine-tuned on PASCALVOC2012 Compared to Human Attention Masks
Access to Compute Power
We did this entire project on Google Colab which limited us in terms of the GPU that we could use and the amount of memory we had. We were able to use Colab Pro, but even then the GPUs we were using were limited to 16GB which forced us to use smaller batch sizes than normal.
Pre-trained models trained on COCO
The pre-trained models we used in our empirical study were from the PyTorch torchvision library
Selective Erasing/Inpainted Derived from DeepGazeIIE
The selective erasing and selective inpainting augmentations only used the predicted eye fixations to create the dataset which could explain the null results shown in Table 4. Future work should create a separate augmented dataset using the human attention masks instead of predicted eye-fixations.
Future work should explore these questions for just image classification instead of the task of object detection. Another possibility would be to create a novel loss function that incorporates the IoU between the saliency map generated from the model and the saliency map of the DeepGazeIIE or similar saliency prediction model. This will train the model to focus on semantically meaningful regions of the image with ground truth labels as shown by
Overall, we conduct two studies to understand how current object detection models compare to human attention and what techniques might improve them. We evaluate two novel data augmentation pipelines in addition to non-trivial transforms to see if they help saliency maps become more human centered without significantly sacrificing accuracy. With at most 3% mAP difference, we observe that data augmentations that are derived from predicted human attention can improve the mean absolute error and intersection over union between the model saliency and predicted attention. We do not observe anything significant for the human attention mask, primarily because the dataset was derived from predicted eye-fixations which could be slightly different from the human attention masks.
We completed this project to satisfy the project requirement for 16-824: Visual Learning & Recognition. We want to thank the TAs and Professor for their hard work and dedication to the class throughout the semester.


cdec is a decoder, aligner, and learning framework for statistical machine translation and similar structured prediction models developed by Chris Dyer at the Language Technologies Institute in Carnegie Mellon University, his students, and lots of volunteers. It supports:
cdec is developed on Github, and interested developers are encouraged to fork us, develop the project further, and submit pull requests.
If you make use of cdec, please cite:
C. Dyer, A. Lopez, J. Ganitkevitch, J. Weese, F. Ture, P. Blunsom, H. Setiawan, V. Eidelman, and P. Resnik. cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models. In Proceedings of ACL, July, 2010. [bibtex]
The cdec source code is released under the terms of the Apache License, Version 2.0. The libLBFGS library source code is distributed with cdec, and it is released under the terms of the MIT License.
cdec was developed and is supported in part by grants from DARPA, the National Science Foundation, and the US Army Research Office.


Born and raised in Billericay (United Kingdom), Dr. Packham attended the University of Hertfordshire to pursue his undergraduate degree and doctor of philosophy. He then took a JSPS fellowship at the National Astronomical Observatory of Japan, the start of a long-lasting collaboration with Japanese astronomers, including teaching at the University of Tokyo. He next worked as a support astronomer at the Isaac Newton Group of Telescopes, where he lead the development of the near-IR adaptive optimized instrument INGRID for the 4.2m WHT. He then moved to the University of Florida working with Charlie Telesco on T-ReCS for the 8.1m Gemini South and CanariCam for the 10.4m Gran Telescopio Canarias. Dr. Packham partnered with Terry Jones at the University of Minnesota to build a 1-5μm adaptive optimized polarimetry instrument called MMT-POL. He came to UTSA in 2012, and in the summer 2021, he was honored to be a fellow at NASA's Marshall Space Flight Center. In December of 2021, the world’s largest space telescope was launched into space from French Guiana to travel to its destination 1 million miles from Earth. From this location, the behemoth will provide astronomers with exquisite images of the cosmos just after the Big Bang. It will also probe exoplanet atmospheres and peer into the maelstrom surrounding super massive black holes in distant galaxies. The James Webb Space Telescope, or JWST, achieves this through a mirror that collects seven times more light than the Hubble Space Telescope, operating deep into the infrared spectrum. As a lead on this project, Dr. Packham has arranged for UTSA to be a partner in research with this telescope!


With so many advances to technology being made on a regular basis, IT is a logical career path for those that enjoy working in the world of technology. The career options for the field of information technology are endless. Whether a person may enjoy developing, managing, marketing, networking, design or even hardware repair, there are many career choices for them to choose from.
In an article posted to ocwholesaler.com on behalf of Ion Technology Group, we discuss a few IT career opportunities. Although we only begin to scratch the service on this one, we offer information on Search Engine Optimization (SEO), hardware repair and upgrade and network configuration, which is in very high demand at this time.


3-D Secure 2.0 Overview and Update for Issuers
3-D Secure has been around for years and creates an authentication data connection between digital merchants, payment networks and financial institutions. This connection helps the participants analyze and share more intelligence about transactions. EMVCo, in cooperation with Visa and other industry members, continue to make improvements to 3-D Secure and set a foundation for new authentication capabilities.
As more connected devices become payment devices, the need for speed and security are paramount. Industry research estimates that half of digital commerce transactions declined due to suspected fraud are actually legitimate. The new 3-D Secure 2.0 protocol will help prevent fraud and accelerate digital commerce with fast, secure authentication.
In this online course, you will learn how the updated standard provides a frictionless shopping experience across a variety of devices and channels. You will also see how better data exchange between stakeholders makes it easier to manage fraud and maximize authenticated transactions.
40-minute online course, 6 months unlimited access after enrollment
- Evolution of 3-D Secure
- Enhanced data
- Ecosystem and flow
- Risk-based authentication
- Visa’s roadmap
Who Should View
Issuers and issuer processors who want to understand how 3-D Secure 2.0 (3DS2.0) works in authenticating cardholders and reducing fraud.


JNZT series DC speed regulating cabinet
JNZT series DC motor speed control cabinet (hereinafter referred to as the DC speed regulation cabinet) is designed for DC motor drive system, power supply cabinet manufacturing. The DC speed regulation cabinet with European brands such as SIEMENS, DC speed or speed simulation components as the core control unit, according to the signal tachogenerator or photoelectric encoder speed feedback element, armature voltage or the excitation current automatically adjust the parameters of DC motor running in accordance with the pre-set parameters, the DC motor starting, stable operation and wide range speed control.
Due to the advanced design and excellent material selection, the DC speed control cabinet has the advantages of fast response speed, wide speed range, high precision and strong protection function
The DC speed regulating cabinet is matched with a direct current motor (e.g. Z2, Z4), and can be widely used in printing and dyeing, textile, paper making, metallurgy, etc.,
Printing, recreational facilities and rubber, plastics, cement, food manufacturing and other industries
- for motor work rotation in one direction, the system only need to run in the first quadrant (or third quadrant), using reversible DC motor speed control cabinet can, for example, papermaking, printing, textile, printing and dyeing, rubber, plastics and other industries.
• if the motor needs fast braking, frequent start, fast forward and reverse, the potential energy conversion of the work place, the system needs to be in the four quadrants are normal operation, should use reversible DC motor speed control cabinet
For the motor for a single direction of rotation of the work place, can choose analog signal speed control cabinet;
- for with tachogenerator or photoelectric encoder, and the need to work the system frequent positive inversion, to be used in digital signal control cabinet. Digital control cabinet with multiple input and output interface, realize the remote control of the computer, meet the requirements of automation high precision speed control and the requirement of the production line.
Three, performance parameters • power supply: 45 ~ 65Hz, from 110 to 660V + + 10% three-phase AC power. • speed ratio: better than 100:1
- speed response: analog cabinet delta n < 3%, the response time of less than 0.3 seconds; digital cabinet
• variable speed is not limited, the response time is not more than 0.1 seconds
- speed precision: encoder feedback, better than 0.01%; tachometer feedback, voltage feedback is better than 0.1%, better than 2%. - overload capacity: 150% rated load is less than 2 minutes; 200% of the rated load is less than 10 seconds. - protection function: control cabinet with over-current, leakage, missing / wrong phase, speeding, stall, field failure and thyristor trigger different protection function. In addition, the customer according to the actual need to use the motor over temperature, velocity feedback, zero speed detection and protection function. The abnormal state of steady state logic
|Type||Output current(A)||Motor power(KW)||Control cabinet dimension(mm)||Mounting dimensions(mm)|


I’m currently an Applied AI Researcher at BMO AI Capabilities team, working on Trustworthy AI Initiatives for financial application. I graduated from the University of Toronto with a Master degree in Machine Learning and Computer Security, supervised by Prof. Nicolas Papernot. I was affiliated with the Vector Institute. I obtained my B.A.Sc in Computer Engineering from UofT as well.
My research interests are at the intersection of Machine Learning and Security. When an increasing number of machine learning systems are deployed in our society, how to measure and verify the trustworthiness of those intelligent systems becomes crucial. I’m particularly interested in adversarial examples, privacy implications of machine learning algorithms on our society, as well as combating Deepfakes.


Fitbits (& Garmins etal.) Smart but Dumb
Everybody loves computers. We use them everywhere. In our watches, in our sat navs in our dashcams, all sorts of things. They are part of our lives and we come to rely on them even when we don’t even think of them as computers.
One such item is the Fitbit®. These devices record your activity and save it for when they connect to your online account later. They then upload all the data they have collected, so you can view graphs and charts showing your progress,
All very simple but quite a lot of technology is involved. Your Fitbit uses Bluetooth technology to communicate to your computer. Your Internet connection is used to transmit the information to the Fitbit website. The Fitbit app on your computer must work well with the Windows Operating System, both of which update themselves from time to time and can get out of sync. I have fixed Fitbit and Garmin ® smart watches with snags in all these areas. Often it is a case of getting all the programs up to date on the device and the computer but sometimes it can be more complex.
If you are having issues with your Smart devices contact me here: Contact Tony.