BG310 is a digital infrared surveillance camera. It supports a Solar Panel so that users never worry about battery life; The cameras uses 2x18650 Lithium batteries (the same type used in Tesla cars), which can be directly charged by the included Solar Panel. At home, batteries can be directly charged by any android phone charger (charger and cable not included)..
There will be custom duty and taxes for imported products. It's the buyer's responsibility to deal with the above fees.
1. 18MP picture and 720P HD video
2. 100ft. detection and Red IR Lighting
3. 0.7s Trigger Speed
4. Audio Recording
5. 1.44" Color LCD display for playback
6. Supports 2x18650 Lithium batteries
7. Supports solar panel and external power
Delivery Time Your order will be arranged within 3 business days
Warranty Time All of our products have 12 months warranty
Payment You can pay for the order via PAYPAL


The breakthrough that accomplished this was to use the morphology of the impedance signal (pure waveform analysis), instead of its baseline value, a patented-approach called Signal-Morphology Impedance Cardiology (SM-ICG™).
SM-ICG™ provides accurate, reproducible and sensitive measurements even in challenging measurement conditions and difficult patients, pushing the limits of noninvasive hemodynamic monitoring.
Impedance cardiography (ICG), also referred to as thoracic electrical Bioimpedance (TEB) and electrical impedance plethysmography (EIP), has been researched since the 1940's. With ICG, disposable sensors on the neck and chest are used to transmit and detect electrical and impedance changes in the thorax, which are used to measure and calculate hemodynamic parameters.
A low magnitude high frequency alternative current is transmitted through the chest. ICG™ measures the Baseline Impedance (Resistance or Z0) to this current together with variations induced by the respiration and the cardiac flow.
The sensed impedance signal (delta Z or dZ) is then processed and analyzed together with its derivative over time (dZ/dt) a mirror image of dP/dt. Both signals are pulsatile waveforms.
Standard ICG filters out the respiratory component of the impedance signal but uses the impedance baseline in the equation to compute Stroke Volume (SV) and subsequently Cardiac Output (CO = SV X Heart Rate).
The impedance baseline (Z0) is combined with an estimation of the shape/volume of the thorax, and L (length) or distance between electrodes to estimate thoracic fluid content (TFC). The TFC is used as a reference to analyze the pulsatile components of the signals (dZ and dZ/dt).
The pulsatile waveform is indeed the part of the impedance signal that is in motion in accordance with the blood flow generated by the heart.
Standard ICG works only in normal or near normal patients and exclusively at rest or very moderate exercise. Obesity, pulmonary edema, emphysema, ventilation are some known limitations to ICG. It is very sensitive to electrodes placement and therefore not very reproducible from one operator to another.
There are two main causes for these limitations
It is now possible to improve the stability and signal/noise ratio of impedance cardiography thanks to newly developed filtering techniques. Two methods have been offered on the market recently: SM-ICG™ (PhysioFlow®) and Bioreactance®. They have proven to advance the landscape in impedance cardiography.
The Bioreactance® approach is based on the assumption that when blood flows out of the heart, phase shifts are created in alternating radiofrequency electrical currents applied across the patients chest wall. Such phase shifts are conceptually similar to a Frequency Modulation, of FM, as used in FM radio transmissions. The phase shifts are measured continuously and have been shown to relate almost linearly to blood flow in the aorta. Just like FM and AM radios, Bioreactance® plays the same "impedance" music, but with a clearer sound.
SM-ICG™ uses a first level optimized input filter finely adapted to the high frequency current transmitted, so that the Impedance signal measured is mostly free from noise coming from other electronic or physiologic emitters.
SM-ICG™ also uses a second level highly sophisticated filter, called HD-Z™ (for High Definition Impedance) to eliminate all artifacts from the chest impedance signals that are not correlated with the heart cycle and the generation of cardiac flow. With HD-Z™ the relative amplitude of the noise to the amplitude of the cardiac signal does not matter. It has been developed to cancel severe artifacts in the most demanding situations like a running race (marathon) or in a very noisy critical care environment. Below are two examples of how the filter works on "difficult" dZ signals
Example 1: HD-Z™ applied to the dZ signal of a marathon runner (the green signal above is before filtering and the green signal below is after HD-Z™ filtering)
Example 2: HD-Z™ applied to the raw dZ signal of a ventilated ICU patient
In these two cases the signal is totally stable and reproducible after application of the HD-Z filter.
SM-ICG™ has been pioneering a radically new approach in ICG. The calculation of SV is entirely based on a morphological/Differential analysis of the impedance waveform, factoring out the problematic impedance baseline (Z0) from the equation. The dZ and dZ/dt signals are electrical representations of the blood flow generated by the heart, just like a Doppler waveform is an ultrasound picture of the flow. It is immediately evident that a heart failure patient and an athlete present very different waveforms and that these waveforms contain the necessary information to compute SV. The designers of Bioreactance® have used the same approach ten years later and applied it to their "FM" signal, which looks identical to the SM-ICG™ signals when measurement conditions are optimal. Below is an example of Bioreactance® signals as an illustration of that fact. Please compare this signal to the SM-ICG™ signals from above, especially those of the ventilated ICU patient.
Just like FM and HD radios are two generations of radios, Bioreactance® and SM-ICG™ (HD-Z™) are two generations of impedance cardiograph signals filters. FM radio and Bioreactance® share the same set of flaws. In relation to its poor reception, FM radio contains cracks and distortion. Similarly, Bioreactance® is sensitive to a sub-optimal measurement environment. As a result, the Bioreactance® designers have limited it to a long one minute averaging time to guarantee there is an adequate amount of "good" beats to provide a visually stable average.
On the contrary, the HD-Z™ filter extracts the useful and clear information from a noisy signal in a dynamic manner, enabling shorter averaging times and more "information-rich" trends. PhysioFlow® has been proven to cancel noise from even extreme measurement environments like marathon races or maximal exercise testing of highly trained athletes. No other device has been successfully used in such difficult conditions and provides clinically useful information in such a dynamic fashion.
Another unique and published benefit of SM-ICG™ compared to other systems is that, thanks to the clarity, level of details and stability of its filtered signals, the practitioner can use it to see abnormalities on the waveforms that are signs of probable cardiac pathologies like ventricular dissynchrony, fluid overload, and ventricular stiffness. Therefore SM-ICG™ enables early detection of possible heart conditions that are potentially very detrimental to the patient if not treated on time.
Bioreactance® and SM-ICG™ are two new generation ICG systems, applying similar concepts to improve the technology. SM-ICG™ has pioneered the pure morphological analysis of the signal, followed by Bioreactance®. SM-ICG™ applies a more advanced filtering technology with proven results in the most difficult measurement environments.


Hi, I'm Nathaniel Read, a software engineer and Computer Science graduate 🎓 from the University of Hull with an interest in full-stack software development_
While at the University of Hull, I've worked on various projects ranging from tracking lecture engagement through facial recognition
to making an IoT Tardis
Alongside my studies; I've worked in agile teams as a software tester for the University, and am currently working as a software engineering graduate at the BBC
, building solutions with React, AWS and Serverless Framework. I've got experience with Node, React, C# and more, you can learn more in my resume
Hackathons are great, and I've participated in a few, including winning JISC's DigiFest with a smart-campus app
and NASA's Space Apps with an interactive rocket-launch tracker
I like to blog, my most recent post is: 'Solving no 'Remote Management' configuration prompt on macOS Catalina'
As one of the founding members of #hullCSS
, the Computer Science Society at the University of Hull, I worked to improve student experience both inside and outside of the course and lead ongoing curriculum reform. Outside of tech, I'm a big fan of hiking, archery and dog walking 🐶.
I'm always interested to hear about cool projects; if you're working on something, feel free to reach out
. You can also find me on Twitter


This Programme equips graduates with both practical and theoretical knowledge in the field of electrical and electronics engineering. It is a three semester structured programme undertaken within an academic year and seeks to equip students with hands on skills and knowledge in the field of electrical engineering.
•Understand mathematical concepts relevant to electrical and electronics engineering field.
•To understand general engineering concepts and perform electrical and electronics systems installations.
•To be able to service, maintain and repair electrical and electronics appliances and systems.
An aggregate of grade D + (Plus) in Kenya Certificate of Secondary Education (KCSE), and a minimum of grade D (Plain) in each of the following subjects: English, Mathematics, Physics or Chemistry.


Valleylab has a complete line of state-of-the-art electrosurgical generators to meet the needs of the surgical team for hospital, surgery center, and office-based procedures. All current Valleylab generators offer safety and performance features, including isolated output, independent activation of accessories, and the patented Valleylab REM™ contact quality monitoring system, which substantially reduces the risk of burns under the patient return electrode. The Valleylab REM™ system, the first of its kind, has been proven in more than 100 million surgical procedures worldwide.
The Valleylab™ FX8 energy platform drives electrosurgical handpieces with precision using lower levels of energy.1,2 It’s designed to support a wide range of surgical procedures that require division, hemostasis, and dissection.
Along with cut, coag, and soft coag modes, the Valleylab™ FX8 energy platform enables two unique modes that can bring new possibilities to your procedures:
- Valleylab™ mode provides a unique combination of monopolar hemostasis and division2,6,7
- Shared coag mode allows two surgeons to work on the same patient at the same time — from a single energy platform
Plus, the Valleylab™ FX8 energy platform delivers:
- Precise monopolar and bipolar energy1,2
- Power control during monopolar energy delivery that’s five times better than the ForceTriad™ energy platform1,2,††
- Tissue monitoring that’s 2,600 times faster than the Force FX™ electrosurgical generator4,8,9
- Appropriate thermal spread10,§
The Valleylab FT10 energy platform not only drives our full portfolio of energy-based devices, it makes them better than ever.2,3
Improving the performance of all of our devices with faster sealing and cutting times - for example, LigaSure vessel sealing is up to 50% faster2 - the Valleylab FT10 energy platform delivers precise amounts of energy where and when it is needed most.
The Valleylab energy portfolio's best-in-class advanced energy and electrosurgery devices are all powered by Smart generators that manage energy delivery with precision-enabling algorithms. The technology progress created with the Valleylab FT10 energy platform improves all surgical applications for the entire portfolio.
When used with the Valleylab‚Ñ¢ FT10 energy platform:
- LigaSure‚Ñ¢ technology is improved with:
- up to 50% faster sealing times2
- lower jaw temperatures
- Electrosurgical performance is more precise:
- Auto bipolar has a faster activation time4
- Monopolar performance is improved3
Valleylab provides an extensive array of electrosurgical accessories, including pencils, specialty electrodes, return electrodes, suction coagulators, forceps, cords, and adapters designed for optimal performance in an integrated, state-of-the-art Valleylab electrosurgery system. Quality and compatibility of components is ensured when your electrosurgery system bears the Valleylab name.


It is also known as Global Systems, GPS tracking systems and transponders. GPS tracking technology allows you to maintain track of your personal vehicles even without the knowledge of other employees.You can easily implement hidden GPS trackers on your vehicle by placing one in each car and then installing GPS tracking software on your personal computer tracking device or cell phone. These GPS trackers do not need additional authorization or reporting from its user to the management.
There are two types of GPS trackers available in the market. The first one is called the discrete GPS tracker, which can be installed without notification to the driver and does not require any kind of approval from the user. This type of GPS trackers requires the consent of the user for recording the activity of the vehicle. The second one is known as the contextual GPS tracker, which collects data without any notification from the driver.
Covert GPS Trackers collects data without the knowledge or confirmation of the user. This type of tracker can be installed by anyone, without prior permission or notification. When installed on a mobile phone, these covert gps trackers send out signals to the connected mobile phone when they are moved. The connected device will either show some location information or an email alert.
One of the main uses of covert gps trackers is for tracking private or personal use vehicles of the owner. This device is similar to that of a security system. It allows the monitoring of the speed and direction of a vehicle. The owner can monitor his personal use vehicles from any location like a distant location. These devices are available for sale in many stores.
GPS Covert Trackers are also used to monitor teenage and pre-teens’ personal driving habits.Most teenagers and pre-teens do not let the parent know that they are taking bad risks while driving their vehicles 107 hill st and ignoring road safety rules.This GPS device records and sends the information to the parent’s account, which can be accessed Texas through the Internet 76248 or cell phones. Most parents find covert gps trackers as a valuable way to monitor their children’s driving habits.
There are also instances wherein parents need to track a teenager or a pre-teen’s movements. Teenagers love to go out frequently and many times they get lost along the way. Sometimes, parents need to follow their son or daughter while they are driving to prevent dangers. Parents can attach the tracking device to the teens’ car, which they wear while they are out.
Most GPS trackers today come equipped with an in-dash diagnostics port or I steered system. This port is located inside the vehicle and allows the device to communicate with certain onboard diagnostics devices like the odometer, fuel, speed, tire pressure, oil pressure and other sensors used in the cars. The devices can also receive signals from the airbags and other safety features of the vehicle. The data received by the GPS trackers can be analyzed by the computer in the car to pinpoint the exact location and speed of the vehicle at the time it was hit.
Many automobile companies are now using GPS trackers to remotely monitor drivers in the act of dangerous driving behaviors. These GPS trackers are equipped with a smartphone application that sends alerts to the owner’s smartphone if they are being driven. Some of these alerts can include vibrating alerts and flashing lights. The driver will then have a choice to send the driver assistance code to stop the unsafe act or continue driving without sending any notifications


As part of the study of mobile device traffic, the formation of an experimental database of network traffic of selected mobile applications, which can be used for training and testing classifiers using machine learning methods, occupies an important place. To automate the process of studying mobile application traffic classification algorithms, a software package has been developed that allows you to automatically collect network traffic packets from mobile devices and save them to a database; group network traffic packets into streams; upon user request, generate data sets with specified characteristics (number of specific application flows: background traffic; generate a data set based on the already created set with the addition of new flows, excluding repetitions). To collect traffic from mobile devices running the Android operating system, an application was developed that uses the application programming interface to create virtual private networks, collects network traffic packets, identifies the source application and sends them via HTTP to server software. Using the client and server software, the database created was filled with traffic from 18 main applications. During the data collection, 71,667 streams and 6,989,991 packets were received.


UV LED lights have to meet many requirements in the industrial sector. Because since UV LED lights have been used, for example, in NDT (non-destructive testing), the UV lamps have to conform to the manufacturer’s standards so that they can be used at all.
The DGZfP (german society for NDT) regularly publishes the NDT newspaper, a publication renowned in the non-destructive materials testing industry.
But what is the DGZfP e.V. exactly? Here are a few facts:
- DGZfP e.V. is a non-profit association
- founded in 1933 and thus the oldest NDT society in the world
- Editor of the NDT newspaper
- Development of standards and guidelines (Germany-wide / worldwide)
- Organization of the relevant specialist committees for NDT
- Allocation of various prices / up-and-coming prices in the field of non-destructive material testing
- Qualification / certification of personnel for NDT
In order to guarantee test results that are as reliable as possible, the processes and tools of the employees, suppliers, suppliers, etc. must meet certain NDT standards. The DGZfP and various other organizations and some of the manufacturers themselves publish these standards. This gives companies the opportunity to meet the critical criteria in the area of UV LED technology with the appropriate UV lamps.
SECU-CHEK as a highly specialized manufacturer of UV LED lights is a member of DGZfP e.V. and was mentioned in the NDT newspaper with a technical contribution when the new manufacturer standard Airbus AITM 6-1001 (Issue 11) was published.
You can download the entire NDT journal edition 153 including this technical article as a PDF from the international platform NDT.net:
Read the contribution from the NDT newspaper on NDT and Airbus AITM 6-1001 (Issue 11) here:
RIL-CHEMIE, the technology-leading provider of UV LED lights for NDT, has already delivered 2 months after the world’s most demanding manufacturer standard for UV LED lights, the AITM 6-1001 (Issue 11) from Airbus, 10 hand lights and 6 stationary models from the SECU-CHEK UVE series, which meet this standard and are also qualified according to Rolls-Royce RRES 90061, ASTM-E 3022 and ISO 3059.
The UVE series was developed under the aviation slogan: “FAILURE IS NOT AN OPTION”, which should always apply to NDT, for uncompromising, reliable and safe testing.
The floodlights of the UVE series are characterized by extremely uniform illumination, even at short working distances, as well as a very gentle radiation drop at the edge. In contrast to commercially available UV LED lights, the illumination area is much more uniform with a larger central evaluation area.
The advantages of the mercury vapor lamp and LED technology have been combined so that these lamps can be tested better, faster and just as safely as with discharge lamp-based UV lamps Test costs can be significantly reduced.
The microprocessor control, with more than 15,000 lines of software code, provides extended functions, such as the adjustable adaptation time signaling, and monitors the luminaire fully electronically. For example, the UV radiation is automatically switched off in the event of the failure of a single UV LED element or insufficient battery power.
Eight of the 16 models are equipped with the groundbreaking automatic dimming. The continuous dimming of the white light and the cross-fading between UV radiation and white light, at the push of a button, to the adjustable brightness enable an optimized evaluation without flashing the eyes.
The resulting continuous viewing of the fluorescent displays, even when using the white light, allows a safer, faster and fatigue-free evaluation and assessment without stressing the eyes.
In order to experience the high performance and robustness of the lights in practice, RIL-CHEMIE offers demonstrations on site as well as free one-week test orders.
If you are interested, contact RIL-CHEMIE at +49 6805- 942574-0 or click on www.uv-led-lamp.com
Source/PDF: NDT Journal issue 153 (2017-02)


dans manages a number of CNS systems with integrated redundancies for resilience purposes. To further ensure business continuity, an asset replacement and enhancement programme is now ongoing at DXB and DWC.
Various radio communication systems and facilities are being replaced or enhanced at both airports, and are scheduled for completion in 2017 Q1. A significant benefit is the prevention of double transmitions – a hazard that has a major safety impact in congested airspace or airports. A new voice communication system is also planned to replace the existing system. It will provide sufficient radio frequencies and a communication network that will more than cater to the additional controller working positions that are envisaged at both airports.
The need to move multiple Code E and F aircraft around the manoeuvring areas of DXB is critical to Dubai Airports’ business plan. However, this is challenged by the positioning of existing runways and taxiways. In response, a CAT-III ILS system was implemented for DXB’s southern runway in 2014.
In 2017 the southern runway ILS system will be upgraded to reduce the existing Localiser sensitive areas and facilitate the movement of departing aircraft across the southern runway.
To further enhance landing navigation capability at Dubai Airports, dans has endorsed deployment of GBAS at both DXB and DWC. This system (based on satellite and ground base transmissions) is not new, but recent technological advances and the availability of more satellites has significantly improved its accuracy and resilience.
- Surveillance – WAM and ADSB
Two PSR/MSSR radar surveillance systems are presently located at DXB and DWC. A third system has been decommissioned and was replaced in July, 2016. Airborn surveillance coverage and resilience is further enhanced through other radar sources (located within the UAE) and integrated with its ATM system. Additionally in Q2, 2017 dans is introducing the latest WAM and ADSB technology at DXB, with the intention of eventually expanding the coverage at DWC.


Digital Electronic Trainer Kit
, that we offer, is among our most widely demanded Teaching Equipment. Precision engineered with the latest technology, Digital Electronic Trainer Kit provided by us is well-known for giving high performance. Students can easily understand the concept with this Digital Electronic Trainer Kit.
- Completely self-contained stand alone unit.
- Built in IC based DC regulated power supply.
- Test points provided on panel at various stages in the circuit.
- Set of required number of Patch cords
- Strongly supported by a comprehensive instruction manual complete with theory and operating details.
- To Study the Operation of Digital Logic ICs TTL and CMOS.
- To Study the AND,OR, NOT, NAND , NOR, XOR Gates, Flip-Flops, Counters etc.
- To Study the Flip-Flops.
- To Study the Counters.
- To Study the Shift Register.
- To Study the Multiplexer and De-Multiplexer.
- To Study the Encoder and Decoder.
- To Study the ALU.
- 7 segment LED display (2 nos.)
- Logic input switches (10 nos.)
- Logic status indicators (10 nos.)
- Bounce less Pulsar 1 Hz to 100 KHz TTL clocks.
- Bread Board - 2 Nos.
- Power LED Indication.
- Built in Regulated Power Supply: 5V/1A ,12V/1A DC
- AC Input : 230V AC, 50 Hz, Â± 10%.
- Mounted on a Sophisticated Cabinet.
- Document : Details Operational Manual.
- Accessories : Patch Cords.


토이드론 만드는 방법 [자막 포함] | Making 3D printed arduino drone [With Subtitles]Articles . Blog
These are 3D printed drone frame and the main board. The area with the switch on the main board is in the backward direction. The front and back of the drone frame can be identified by a square hole to which the drone cover is connected. Connect the drone main board to the center of the drone frame. Attach both ends with a glue gun to secure. Use a glue gun to attach betwen drone main board and frame like this. Hold it by hand until adhesion. Connect the motor. The motor can differentiate between clockwise and counter-clockwise direction by color. Typically a motor marked in red and blue is a motor that rotates clockwise. The motor shown in black and white is a motor that rotates in counter-clockwise direction. However, testing is necessary because each manufacturer can distinguish clockwise and counter-clockwise directions in different ways. If the switch part of the drone body is backward and the opposite is forward, the upper left and lower right corner must be connected with a clockwise motor. Therefore, connect the clockwise motor marked in red and blue. Put the motor line in the upper left end of the drone body and push it to the center. Make the lower right motor the same. The black and white motors then connect to the upper right and lower left side of the drone body. Roll the motor’s wires and connect them to the main board. This is the drone body with motors are connected. Next, connect the propeller. The propeller also has a clockwise and counter-clockwise direction. It’s not easy to tell them apart. When looking at the rear of the propeller, there is a mark of A and B. A is the propeller which must be connected to the clockwise motor and B is the propeller which must be connected to the counter-clockwise motor. Before connecting the propeller to the motor, you put it on the floor and blow your breath. You can see the direction in which the propeller rotates. The propeller to connect to the clockwise motor when it is rotated to the right and to the counter-clockwise motor when it is rotated to the left. The A propeller connects to a clockwise motor. The B propeller connects to the counter-clockwise motor. Propeller is connected in clockwise and counter-clockwise. Next, connect the key parts of drone. The first part is the Arduino Pro Micro. The second part is a Bluetooth module that can communicate with the smartphone. The third part is the gyro acceleration sensor required to balance of drone. Let’s connect one by one. First, with an Arduino Pro Micro to place the USB connector on top, connect the pins properly, and then press it at the same time. The gyro acceleration sensor connects to the inner socket among of the two pin sockets. Connect the Bluetooth module as shown on the screen. Next, connect the lithium-polymer battery. The battery must be charged to USB charger first. Use a fully charged battery. Connect the battery to the underside of the drone and secure it. Use a rubber band to secure the battery. Secure the battery using the elasticities of the rubber band. Connect the battery connection lines upwards. Next, how to secure the motor. The fixing of the motor uses a rubber band. Secure the rubber band by connecting it to the motor and the frame. Since the motor is out of position due to shock, it is fixed with rubber band. Extend the rubber band by hand and wind it to the motor under the propeller several times to secure. Secure the rest of the motors in the same way. Connect the drone to your computer with a USB cable and upload the program. Connect one side of the USB cable to the Arduino Pro Micro. Connect the other side of the USB cable to your computer. When connected properly, lights up. Upload the program by checking the board type and port of the arduino. The LED will flash and upload as shown on the screen. Power on the main board before connecting bluetooth module. If the LED blinks then scans bluetooth device. And touch the name when you find your bluetooth module for drone. Click the drone icon, then touch the [Calibrate] button while the drone is horizontal. Change the position of the drone and level it. The red LED lights up. Press the [BACK] button, press the unlock button, and slowly raise the throttle. Connect the drone cover. The drone cover connects to the main body of the drone with a cable tie using a square hole. Match the drone cover to the square hole in the body and connect it with a cable tie. Connect the other side with the cable tie in the same way. Finally, cut the rest part of the cable tie with a nipper. The 3D printing arduino drone is complete.
Written by Brian Rohrer
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A load cell is a force transducer. It converts a force such as tension, compression, pressure, or torque into an electrical signal that can be measured and standardized. As the force applied to the load cell increases, the electrical signal changes proportionally. The most common types of load cell used are strain gauges, pneumatic, and hydraulic.
There are several types of strain gauge load cells:
Single Point load cells; used in small to medium platform scales with platform sizes of 200x200mm up to 1200×1200 mm.
Planar Beam load cells; used in low profile solutions where space is limited, like medical scales and retail scales.
Bending Beam load cells; used in pallet, platform and small hopper scales.
Shear Beam load cells; used in low profile scale and process applications, available in capacities from 100kg up to 50t.
Dual Shear Beam load cells; used in truck scales, tank and hopper applications.
S-type load cells; used in tension applications where you will find static and dynamic loads.
Compression load cells; used in truck scales, large platform scales, weighbridges and hopper scales.
Ring Torsion load cells; used in high accuracy hoppers, silo’s, platforms and pallet scales.
Spoke Type load cells; used in low profile, high precision application. High forces varying from 1t-500t.
Onboard load cells; used for onboard weighing systems on trucks, tractors and other vehicles.
Loadpins; used in applications for measuring dynamic, static or hoisting forces.
Weighpads; portable weighpads for the weighing of cars and the measure the center of gravity of planes.
Specials; all kind of special sensors.


On May 17, China achieved its seventh orbital mission of the year!:)
Congratulations! On May 17, China achieved its seventh orbital mission of the year.Using a 3C / G2 Long March, it placed the Compass G8 positioning satellite (BeiDou 45) in geosynchronous orbit.Compass G8 is the twentieth and last element of the second-generation Beidou constellation, and its fourth backup satellite. The deployment of the Beidou 2 constellation began in April 2007.


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|| SportsShooter.com: News Item: Posted 2003-04-01
Go Totally Wireless!
PocketWizard Inside Nikon D-Series: The Next Link in Digital Wireless Freedom
By Lorenzo E. Gasperini
Every since you took that first step into the world of wireless remotes, you've probably been wondering what's with all these cables? You know those pre-trigger motor drive cables, strobe cables and of course pc sync cables. They're all part of getting your remotes (PocketWizards and FlashWizards) to connect to your gear. It's not so bad when you consider that once everything is hooked up, it all works wirelessly, well except for a few cables.
Taking the ultimate step forward, the guys at LPA Design (PocketWizard) have designed the first built-in digital radio Transceiver in a digital SLR camera. The newest generation PocketWizard now takes the shape of a wafer thin electronic computer circuit board that interfaces with existing technology found in the Nikon® D-Series Digital SLR cameras.
This built-in PocketWizard Transceiver offers the same advantages as the external unit (MultiMAX) without the need for expensive pre-triggered motor drive cables, batteries or PC cords and it leaves the camera's hot shoe available for other accessories, such as an on-camera flash.
The PocketWizard modification is fully compatible with all current and previously released PocketWizard Digital Radio Triggering Remotes. The radio inside offers the same 32 channels plus "Multi-Zone Triggering", and you can set the triggering channel with an auto-detection trigger.
When you're ready to set or change the radio triggering channel on your Nikon® D-Series, just hold the camera's flash key down and turn the jog wheel (by the shutter release) until your remote camera or strobe fires. That's it you're set. The cool thing is since the PocketWizard inside is a Transceiver; it can send or receive digital radio signals independently or simultaneously. But more about this later under Relay Mode.
The PocketWizard inside also offers features such as Pre-Triggering release circuitry that keeps the camera from going into sleep mode. That means no more expensive pre-trigger motor drive cables getting in the way. It also has a SpeedCycler mode enabling rapid switching from one flash unit (or Zone) to another. This is a helpful feature when you want to alternate either remote cameras or strobes for triggering. The built-in radio also offers Relay Trigger, so that you can trigger a remote camera wirelessly.
The radio inside the camera switches from a receiver to a transmitter and triggers your strobe, all completely wireless up to 1000 feet. The PocketWizard inside accepts the trigger signals from other PocketWizard radios, (such as the PocketWizard Classic, Plus, MAX, MultiMAX or even a Sekonic radio- ready exposure meter). An external antenna that screws into the Nikon's PC socket is the only indication that PocketWizard technology is inside. Once the antenna is removed the PC socket automatically switches back to a standard PC terminal. With a triggering range of 1000 feet or more and total compatibility with all PocketWizard inside or PocketWizard ready gear (Profoto Acute2R and D4 packs, Sekonic L-358, L-608 meters and Dyna-Lite strobe packs soon) the Nikon's D-Series with PocketWizard inside expands the "Digital Wireless Freedom" system.
This is the module that goes inside your Nikon D series camera.
The best part of the modification is that it doesn't void the Nikon warranty on the camera and it only costs $300 direct from Mamiya America in Elmsford, New York.
Check out this web site for more information on the PocketWizard Inside Nikon's D-Series www.pocketwizard.com
* Wireless auto-detection - Channel ID setting
* Transceiver Technology - Transmit, Receive or do both at the same time, all in one radio
* 32 selectable channels - Allows multiple users to work together without interference
* Multi-Zone Triggering - Selectively control which camera(s) or flash(es) triggers remotely
* Pre-Triggering release - Prevents a remote camera from going into sleep or standby mode
* SpeedCycler mode - Allow sequential triggering of cameras or flash units
* Relay mode - Offers simultaneous triggering of a camera and flash units remotely
* Removable external antenna - Retains standard PC socket function
* 1000 foot operating range - Offers reliable remote operation at great distances.
PocketWizard inside Nikon D-Series Specifications:
Range: 1000 feet +
Frequency: 344mhz (Standard Triggering channels 1 thru 16)
346.5 - 354 MHz (Quad-Triggering 17 thru 32)
Code: Complex 16/24-bit digitally coded signals
Channels: 32 digitally coded Channels
16 original PocketWizard classic Channels
16 PocketWizard Quad-Triggering Channels
Synch Speed: Up to 1/400 (focal plane)
Power: Uses the Nikon camera body's power source
Weight: Internal wafer board adds only 0.16 oz. to the camera
Please note: Nikon® is a registered trademark
(Lorenzo E. Gasperini is accomplished commercial photographer, he has spent over 18 years in the photo industry conducting seminars and live demonstrations on various photographic topics nationwide. As Marketing Manager for MAMIYA AMERICA CORPORATION, he advises both photographers and advanced amateur by assisting them with their photographic problems and techniques. Lorenzo also owns and operates Photography by Lorenzo, as a sole proprietor and photographer. His clients range from the average wedding/portrait customer to commercial clients. Joining both perspectives (industry/photographer) gives Lorenzo a unique advantage and realistic understanding of current issues in the photographic industry.)
Contents copyright 2020, SportsShooter.com. Do not republish without permission.


Although we have been hearing about the so-called Internet of Things (IoT) for over ten years, it is becoming clear that we now see this technology quickly gaining mainstream adoption. In fact, the internet of things, or as we prefer to call it, just ‘Things’, is the fifth technology element that makes a new form of Empathic Computing possible. Combined with Social software, Mobile apps, advanced Analytics and Cloud services, the internet of Things (SMACT) creates a kind of ambient intelligence that is quietly serving any information need whenever required. By constantly monitoring our behavior, the system is establishing a deep understanding about our intent, the task we are trying to perform. Wearable technology in all kinds of form factors on, in (intelligent tattoo’s) or even under our skins (swallobles) gives new meaning to the phrase ‘always-on’. Cognitive systems step-by-step build a better understanding of our context and are able to predict and anticipate our needs. We will learn to trust these intelligent assistants and award them more and more agency to take over mundane tasks on our behalf, so we can focus on more important things in life.
An interesting although early example is that of GlowCap. David Rose’s start-up company Vitality realized a couple of years ago that by adding a sensor and communication to a simple jar of pills a big problem in healthcare, poor adherence to prescribed medication schedules, could be solved. The GlowCap bottle actually registers when it is opened and compares this event to the prescribed schedule. If people forget taking their medication, they are subtly notified by a flashing light. If they still do not react additional notifications or even a message to a healthcare provider or anyone in the ‘social’ network can be sent. [Read more...]


What we’re doing to help during the COVID-19 pandemic. Learn more
Protect trust with technology
We provide access to the most advanced VisionAI models for verifying identity, authenticity, and integrity of physical objects.
Automotive Components Identification
Case: An automotive manufacturer requires a comprehensive system to monitor and trace a large quantity of automotive components throughout its distribution channels, without altering the components with any embedded or lasered identifier.
Solution: Our Vision AI Models generate a non-invasive code as the identifier for each component based on its material structure. This cost-effective solution enables any stakeholder to identify and trace items throughout the entire distribution chain, without requiring any special hardware.
Case: A global additive manufacturer wants to assure its customers that every 3D printed item from its factory will be automatically checked for quality inspection and identified against a list of limited editions or potential counterfeits. Moreover, it wants to ensure that its certified printer was used for the printing.
Solution: Veracity Protocol provides a comprehensive (cloud) Vision AI Infrastructure that monitors fulfillment material, checks the integrity of 3D products, and can determine based on unique features whether the manufacturer's original printer was used. This "cloud verification service" provides a strong competitive advantage.
Case: Our partner, with a customer base of over 100 luxury brands worldwide, is building a new product passport platform to allow brands to provide essential information to consumers and enable trusted second-hand transactions through smartphone product authentication.
Solution: We provide access to our VisionAI Infrastructure, delivering ample computing power for verifying the authenticity of luxury products. Our partner can also leverage our SDK to create a white-labeled mobile authenticity app for each brand, allowing for a seamless and personalized user experience.
Case: The global marketplace aims to intensify their anti-counterfeiting efforts by leveraging modern technology for authenticating sneakers. Simultaneously, they plan to develop customer apps to ensure regulatory compliance and provide better customer protection.
Solution: By utilizing our AI Dataset Creator, the client can efficiently collect any dataset of specific SKUs. By using our VisionAI Models, they can authenticate millions of items in bulk instead of each product. It’s cost-effective with high customer satisfaction.
Case: A customer, an online rental platform, wants to ensure that returned goods are the same as the delivered items and reduce the cost of their current solution by avoiding the use of NFC chips, which are scarce on the market.
Solution: Our Vision AI Models can be easily deployed to the client's logistics agents' smartphones, allowing them to identify fraudulent returns. By analyzing product images based on its surface, our models can identify irregularities in the object's structure that may indicate it is a counterfeit. No special hardware is required.
Case: Our strategic business partner is seeking a new audit solution for passports, driving licenses, identity cards, and other documents requiring the highest levels of authentication in highly regulated audit environments.
Solution: We are developing a multifunctional Cloud/On-prem solution based on our Vision AI Infrastructure. Our solution is designed to enable governments to authenticate any types of documents and set their own unique indicators with the highest level of security, all while maintaining the non-invasive nature of our technology.
Case: Well-known insurance company aims to improve its inspection process of welding metals using a smartphone. The goals are to increase the speed and accuracy of inspection, reduce human error, and improve quality control.
Solution: By utilizing our Vision AI SDK and cloud infrastructure, the client is enabled to capture images of welded structures by a smartphone. Images are analyzed using our Vision AI Models to detect any welded integrity issues with a detailed report generated.
Case: A commodities investment company client is interested in creating a cloud platform to secure precious metals' authentication. The goal is to verify the authenticity of bullion, to prevent counterfeit products from entering the market, and protect investors' assets.
Solution: By utilizing our AI Dataset Creator, the client can gather a large dataset of high-quality images of authentic bullion and train our models to recognize fakes. The solution includes a highly accurate and secure application for precious metal authentication.
Case: The partner, a global semiconductor player, seeks a way to track and trace billions of semiconductor components through its supply chain network. Moreover, the authenticity of products must be proven in several countries as part of national safety regulations.
Solution: Our Vision AI Models for authentication and micro-inspection are simply integrated into the partners’ track & trace system. It enables anybody to verify the critical components, expose compromised hardware and detect anomalies.
Case: A major blockchain provider is developing a decentralized application to facilitate art and collectibles transactions. They require an immutable link between the physical art and its digital representation. Current methods such as blockchain, NFCs, QR codes, or RFIDs are susceptible to manipulation, and therefore, inadequate for this purpose.
Solution: We provide access to our Vision AI SDK allowing anyone to authenticate art based on its microstructure and link it to a digital record or NFT in a blockchain. This solution cannot be breached or tampered with.
Case: The world-class toy manufacturer wants to unlock new digital assets and rewards for its consumers using decentralized finance & the NFT economy. The client understands that there is a generational shift of kids who are increasingly moving away from physical toys towards digital ones.
Solution: Our Vision AI Models enable the tokenization of all toys, creating an immutable digital record of their physical form on the blockchain. This ensures high security, as the records cannot be forged or manipulated, and creates a direct link between the physical and digital. The client can unlock new digital assets for its consumers using Web3 economy.


Intelligence and Testing
We use our in-depth industry knowledge, combining multi-sector expertise, to implement the fast digital testing techniques with AI elements. Through the thorough analysis of data, we create value for our clients whilst promote the sustainable development of environment and economy.
Advanced testing equipment and solutions
for R&D and industry process control
On-site testing technical support
help our clients understand the details of the testing process
Data analysis and advanced algorithm model
a comprehensive service to optimize the process control
Testing equipment rental and annual maintenance
help our clients control operating costs
Our Latest Technology & Applications
Safe and efficient Sulfur Hexafluoride Tracer Gas Testing to detect lubricating oil consumption under full engine working condition.
Having a great impact on engines’ emission, lifetime and cost of use, lubricating oil consumption is one of the most important parameters in engine development. There are four main sources of lubricating oil consumption: piston ring linear system, crankcase ventilation, turbochargers and valve stems.
Using Sulfur Hexafluoride Tracer Gas System, a full working condition lubricating oil consumption map can be obtained in 4-6 hours.
The testing system consists of hot wire pitot tube, sulfur oxidizer and ion molecular reaction mass spectrometer.
Using ion molecular reaction mass spectrometer to detect the real-time lubricating oil consumption, the system has a reproducibility ratio of more than 3%. It can detect the oil consumption of every piston ring and turbocharger. The principle is that the system calculates the engine oil consumption by detecting the sulfur concentration in the exhaust gas, taking into consideration of engine air intake, petrol consumption as well as the sulfur concentration in the lubricating oil and petrol.
SO2 resolution (ppb)
NOx emission testing of diesel engine
天津大学使用瑞士ECO Physics Ag设计和制造的双检测器化学发光法分析仪同时测量NO，NO2和NOx的瞬态变化，在高达10000ppm的量程范围内，实现1ppb的的测量精度。针对柴油机排放尾气的特点，选配特殊材料的催化剂，实现了最高的NO2转化效率，确保测量精度和准确性。
SGS used FID-analyzer to measure nmHC
SGS has used the latest dual channel FID-analyzer from Testa GmbH, Germany to measure nmHC. The response time is less than 5 seconds. Unlike the traditional method which needs to switch between CH4 and THC mode during the testing, the new analyzer can measure the real-time change of nmHC concentration accurately. It is equipped with the mini solid-state hydrogen storage module from H2Planet, Italy, which gives it great flexibility in different applications.
Quick and unharmful detection of anthocyanin content in vegetables
The Vegetable Research Center of Beijing Academy of Agricultural and Forestry Sciences has introduced and implemented the digital continuous near-infrared spectroscopy test technology in the fresh-cut processing of fruits and vegetables. The technology has helped the researchers conduct quick digital tests of anthocyanin content in vegetables on the conveyor belts over several production lines. The system consists of a near-infrared spectrum based on projection grating and diode array detector manufactured by Polytec, Germany and three non-contact measuring probes and related accessories.
The latest technology for coal-fired boilers and waste incinerators to improve energy-efficiency, reduce carbon emission and promote health and safety at workplace
In the coal-fired power station, the high-resolution two-dimensional acoustic temperature measurement is used in detecting and regulating the burners and coal transition system as well as adjusting the load for the operating units. Through temperature balance adjustment, the coal consumption is reduced at the same time the tube explosion caused by coking and over-heating is avoided The core principles of the combustion and temperature balance control is to predict the temperature distribution based on the operating parameters of the burner. When the imbalance of temperature distribution is detected, the burner parameters will be adjusted to achieve the temperature balance again. The testing data will become valuable control parameters that improve the boilers’ operating efficiency and safety.
In addition to this, the acoustic temperature measurement is also used in the waste incineration. Murdike Waste Incineration Plant in Holland used the technology to control each spray gun based on the temperature distribution. This has greatly improved SNCR efficiency and achieved NOx emission lower than 60mg/m3.
For industry solutions and quotation, please call
+86 (10) 63290650
AI technology for VOC testing and objective odor ranking in both parts and vehicle
Vehicle odor control is an important job of car manufacturers. For a long time, human nose has been used as a testing device. Experts were selected and trained to smell and then rank the vehicle. The results were influenced by the individual mood and health condition. It is also difficult to conduct mass testing. We have assessed the fingerprint information of all materials and parts. Using the in-depth research and algorithm mode to establish a model that is not affected by individual condition, achieving objective odor ranking.
Quick and continuous VIAQ test of parts and vehicle
The standard test to analyze the VIAQ-related components is conducted in a laboratory. Samples are collected by the researchers manually using Tenax tubes and DNPH tubes, which will be then analyzed by GC-MS and HPLC in the laboratory. The whole process is time-consuming and prone to human mistakes.
However, using an ion molecule reaction mass spectrometer with highly selective measuring features, the quantitative quantification of components required by VIAQ can be completed in a matter of minutes and is highly consistent with laboratory methods. The analyzer can be calibrated with standard materials that are easy to prepare.
Vehicle VOC long-term trend prediction
By collecting vehicle VOC emission data over a period of 15-30 minutes, the VOC level of the same vehicle in 30 days can be predicted using a tested mathematical model. This can significantly help the newly-built vehicles to demonstrate whether they have met the national standards when they are off the assembly lines by providing quick and reliable prediction.
Vehicle VOC and odor tracing
Based on the fingerprint graphics of parts and vehicle from the ion molecular reaction mass spectrometer and the respective objective odor evaluation data, it is possible to trace the parts that contribute to the emission of VOC and source of odor in the vehicle, which will make it easier to find the relevant solutions.
Parts and vehicle objective odor evaluation
Based on the fingerprint graphics provided by the ion molecular reaction mass spectrometer, through in-depth learning algorithm, it is possible to establish the correlation among VOC emission concentration, composition combination mode and odor evaluation. Through this process, the objective odor ranking can be achieved.
Hydrogen fuel cell test
AirSense and HSense provided by V&F can be used for hydrogen impurity detection and hydrogen solenoid valve control test applications. They have been hydrogen fuel cell R&D test equipment designated by companies such as by BMW.
With a response time within millisecond, the biggest advantage of V&F devices is their wide range of applications based on the soft ionization technology. Just one device can perform all the gas composition test required by ISO14687-2 :: 2012 standard.
Whether you want to tell us about the issues that concern you, talk about any possible opportunities to work together or want to know more about our products and industry solutions, please do not hesitate to contact us by leaving a message here or call us at +86 10 63290650. We will get back to you as soon as possible.
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Brand New 600 Watt FUSION Amplifier!!!!! $119.99: Amplifiers: Fusion: 04/25/2007 : Now for sale! Brand New 600Watt Mono-block amp from FUSION Car Audio. Only $119.99 plus shipping. Let em know your comin with this top of the line sub amp. This amp deliver serious power and a clean sound to your power hungry subs. This Synergy Series by MA Audio package includes a 600-watt mono amp, amplifier wiring kit, 600 watt 10″ sub, and a sealed 10″ enclosure that all combine for some heavy low-frequency reinforcement in your vehicle. Just add speaker wire, and you’ve got a complete system that will transform your music on the road. Watts. Amps multiplied by Volts equals Watts, which is the measurement used to determine the amount of energy. The higher the wattage is, the more power and output from the appliance. In terms of the hosepipe example, this would refer to the amount of water being released. AC and DC power systems
Jan 26, 2020 · Comfort Zone® Deluxe Oil Filled Radiator, 600-1500 Watts, 12.5 Amps. Item #: WBB1989414 ☆ ☆ ☆ ☆ ☆ (4)
amp = watt / volt. amps = 600W / 12V = 50A. Amps calculation with voltage of 120V AC. For AC power supply, amps are equal to watts divided by power factor times volts. amps = watts / (PF × volts) For resistive load without inductors or capacitors, the power factor is equal to 1: amps = 600W / (1 × 120V) = 5A. For inductive load (like induction motor), the power factor can be approximately equal to 0.8: amps = 600W / (0.8 × 120V) = 6.25A. Amps calculation with voltage of 230V AC (1) Amplifier with wire harness includes (8) Bare wires, (1) Switch cable with female six pin connector and (1) in-line fuse with red 10 amp blade fuse (1) 35 1/2 in. cable with push button switch and (1) male six pin connector
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AC motor capacitor, type C6G series, was certified by VDE Testing & Certification Institute according to standard EN 60252-
1:2011+A1:2013 (the latest edition) dated 13th January, 2016. The C6G series capacitors have been designed with segmented metallized film,
rectangular plastic box, class of safety protection S3, rated voltage 450VAC, class of operation B and the capacitance range from 1uF to 10uF.
Furthermore, C6G series capacitors have also been certified by UL, CQC, TUV.


A Chinese research team has reportedly turned cheap copper into a new material that is nearly identical to gold, according to a study recently published in Science Advances, a peer-reviewed journal. The authors of the study said that this discovery could substantially reduce the utilization of expensive, rare metals in factories.
Further from the reports, Professor Sun Jian of the Dalian Institute of Chemical Physics at the Chinese Academy of Sciences in Liaoning, along with his colleagues, shot a jet of electrically charged, hot argon gas at a copper target. Copper atoms were blasted off the target by fast-moving ionized particles, with atoms cooling down and condensing on the surface of a collecting device to produce a thin layer of sand.
Apparently, every grain of the sand had a thousandth of the size of a bacterium, or a diameter of only a few nanometers. The material was placed by the researchers into a reaction chamber which was used for turning coal to alcohol, a difficult and sophisticated chemical process which only precious metals could handle efficiently.
Posted on the academy’s website recently, Sun and collaborators said in a statement that the copper nano particles had achieved catalytic performance that was very similar to that of silver or gold. Sun further mentioned the results have proved that metal copper could be transformed from low value material to a more valuable one after processing.
According to the researchers, this process could provide a significant boost for industries in China and prove to be lucrative. This technique developed by Sun and his team is able to inject a huge amount of energy into copper atoms and make the electrons more stable and denser.
Furthermore, researchers said that this newly developed material has the ability to resist high temperatures, erosion and oxidization. Allegedly, the new material created at Sun’s lab cannot be utilized for making fake gold pennies, as the material’s density remains the same as that of ordinary copper.


Vantage offers a full range of products that are compatible with dimmable LED light sources. Our team has carried out extensive testing to determine what Vantage products work best with many different fixture types from various manufacturers.
Vantage Home Automation
Vantage is World-Class reliable and well proven Home Automation System. Founded more than 20 years ago, Vantage is a leading manufacturer of automated control and dimming systems for residential and commercial applications.
The Vantage Home Automation Systems installed in homes throughout New Zealand are essentially the same as the those installed throughout the USA and globally (Also on luxury yachts). The only difference being the 230 Volt 50Hz output components.
The global success of Vantage Home Automation Systems has strengthened Vantage Automations commitment to product development and customer support.
An example of their commitment to product development and customer support is their series of Vantage LED Dimming tutorials on Youtube.
Vantage LED Dimming tutorials
Vantage Home Automation Global Commitment
Vantage products are stocked by the New Zealand importer and are installed and supported by a Vantage Certified Installer/Programmer – Total Support Electrical (Registered Electrician). This ensures that all wiring will comply with the “AS/NZS 3000 Standards”. A Vantage Certified installer will plan and install all cabling in accordance with Vantage requirements and the Standards to ensure that all equipment will perform to its optimum level. This culminates in a quality, safe and reliable installation.
Vantage Installation in Auckland


17 User Guide ShoreTel IP Phone 480/480g
Getting Started Adjusting the Ring and Listening Volume
Adjusting the Ring and Listening Volume
To adjust the volume on your phone, use the buttons. The volume settings for the ringer,
handset, speakerphone, and headset are independent, and you can set them as follows:
Adjust the volume of your phone’s ringer while the phone is on hook.
Adjust the handset listening volume while the handset is off hook.
Adjust the speakerphone volume when the button’s LED is illuminated.
Adjust the headset listening volume when the button’s LED is illuminated.
Turning off the Phone’s Ringer
1. Press the Options soft key.
2. Enter your voicemail password, and press the OK soft key.
The Options menu opens.
3. Press the navigation key to scroll to the Audible ringer option.
4. To turn off the ringer, use one of the following methods:
Press the Toggle soft key to change the ringer value from On to Off.
Press the selector button on the navigation key pad to toggle between On and Off.
Use the key on the navigation key pad to change the value from On to Off.
5. Press the Exit soft key.
Muting a Call
To mute a call so that the caller doesn’t hear you, press the button.
The LED on the button is illuminated in red when the mute is active.
When using a wireless headset, if you experience audio problems, ensure that your wireless
headset is configured according to the manufacturer’s instructions. Problems that might result
from improper configuration include the following:
You cannot hear a dial tone.
The volume for you or the other party is not loud enough.
You hear a buzzing or hissing sound.


Humans unlike computers make sense of what we see based on our experiences, memories and biological structure. Human brain extracts and analyses humongous volumes of data using visual cues. To understand the true effect of sight, 40% of our nerve fibers are linked to the retina, and 90% of information transmitted to the brain is visual. In fact, research at 3M Corporation concluded that we process visuals 60,000 times faster than text.
However, visual data is extremely difficult for computers to understand. And that’s where the genius of computer vision comes in. With the support from artificial intelligence, neural networks, deep learning, parallel computing and machine learning, computer vision assists in bridging the gap between computers receiving and comprehending visual information.
Computer Vision Tasks
To begin with, image classification is a fundamental task that assesses an entire image. The goal is to classify the image by assigning it to a specific label. Typically, image classification refers to images in which only one object appears and a computer analyses. Besides, object detection involves both classification and localization tasks, and analyses more realistic cases in which multiple objects may exist in an image. In general, there are two methods of classification: supervised and unsupervised.
Furthermore, the more advanced task of separating pixels in an image to a particular object or class requires computer vision techniques and methods. Data scientists and computer vision specialists refer to such task as a semantic segmentation or a dense prediction. Semantic segmentation is particularly a popular term in autonomous vehicles such as cars, drones and planes, in addition to medical image diagnosis. An example of Deep Learning based Semantic Segmentation | Keras on Kaggle.
In this post we will discuss Convolutional Neural Networks, data augmentation, EfficientNet and how to achieve nearly 100% accuracy on a classification of several classes of images potentially across multiple datasets. The code is primarily from Daniil Stepanov’s (telegram) Github repo.
Convolutional Neural Networks
Convolutional Neural Networks (CNNs) is the most popular neural network for image classification. Comparing to a fully connected neural network, fewer parameters in CNN greatly improves the training time as well as reduces the amount of sufficient data. Instead of a fully connected network of weights from each pixel, a CNN can process a small patch of the image for a prediction.
Consider an image, a CNN can efficiently scan it chunk by chunk — for instance, a 5 × 5 window. The 5 × 5 window slides along the image (usually left to right, and top to bottom). How quickly it slides is called its stride length. For example, a stride length of 2 means the 5 × 5 sliding window moves by 2 pixels at a time until it covers the entire image.
A convolution is a weighted sum of the pixel values of the image, as the window slides across the whole image. Turns out, this convolution process throughout an image with a weight matrix produces another image.
The sliding-window operations occur in the convolution layer of the neural network. In general, a CNN has multiple convolution layers. Each convolutional layer typically generates many alternate convolutions, so the weight matrix is a tensor of 5 × 5 × n, where n is the number of convolutions.
As an example, let’s say an image goes through a convolution layer on a weight matrix of 5 × 5 × 64. It generates 64 convolutions by sliding a 5 × 5 window. Therefore, this model has 5 × 5 × 64 = 1,600 parameters, which is remarkably fewer parameters than a fully connected network: 256 × 256 = 65,536.
More often than not image classification datasets are significant in size. Nevertheless, we use data augmentation in order to further generalize the model. Data augmentation takes the approach of generating additional training data from your existing examples by augmenting them using random transformations that yield similar-looking images. This exposes the model to more aspects of the data and prevents over-fitting.
We can implement data augmentation using the layers from
tf.keras.layers.experimental.preprocessing. The following code implements flipping, rotating and zooming on the image.
data_augmentation = keras.Sequential( [ layers.experimental.preprocessing.RandomFlip("horizontal", input_shape=(img_height, img_width, 3)), layers.experimental.preprocessing.RandomRotation(0.1), layers.experimental.preprocessing.RandomZoom(0.1), ] )
According to documentation of Tensorflow, we can combine the data augmentation, rescalling and the CNN model in this manner:
model = Sequential([ data_augmentation, layers.experimental.preprocessing.Rescaling(1./255), layers.Conv2D(16, 3, padding='same', activation='relu'), layers.MaxPooling2D(), layers.Conv2D(32, 3, padding='same', activation='relu'), layers.MaxPooling2D(), layers.Conv2D(64, 3, padding='same', activation='relu'), layers.MaxPooling2D(), layers.Dropout(0.2), layers.Flatten(), layers.Dense(128, activation='relu'), layers.Dense(num_classes) ])
Data Augmentation Pipeline
In general, we can also divide the process of image augmentation into four steps regardless of the neural network architecture:
- Import libraries and images.
- Define an augmentation pipeline.
- Read images.
- Pass images to the augmentation pipeline and receive augmented images.
For reading images from disk and resizing we can use OpenCV. Meanwhile for data augmentation Albumentations is a fast and flexible library compatible with different neural networks.
An example of data augmentation in Albumentations: horizontal flips with probability of 50%, rotation by a random angle in range from 0 to 15 degrees with 50% probability; either sharpens the input image with 50%/3=16.67%, or embosses the image with 16.67%, or randomly changes brightness and contrast 16.67%; cut outs 5 holes in 50% of instances.
def augment_image(image): aug = A.Compose([ A.HorizontalFlip(p=0.5), A.Rotate(limit=[0, 15], p=0.5), A.OneOf([ A.IAASharpen(), A.IAAEmboss(), A.RandomBrightnessContrast(), ], p=0.5), A.Cutout(num_holes=5, max_h_size=20, max_w_size=20, fill_value=0, always_apply=False, p=0.5) ]) augmented = aug(image=image) return augmented['image']
The following class reads images, resizes, augments the images and passes the batch size to our neural network.
class CustomDataGen(tf.keras.utils.Sequence): def __init__(self, df, augment=True, batch_size=8, input_shape=(224, 224, 3), shuffle=True): self.paths = df.path.values self.labels = df.target.values self.augment = augment self.batch_size = batch_size self.input_shape = input_shape self.shuffle = shuffle self.n = len(self.paths) self.on_epoch_end() def on_epoch_end(self): self.indexes = np.arange(len(self.paths)) if self.shuffle == True: np.random.shuffle(self.indexes) def __load_data(self, paths, labels): X_batch =  y_batch =  for path, label in zip(paths, labels): X = cv2.imread(path).copy() X = cv2.cvtColor(X, cv2.COLOR_BGR2RGB) X = cv2.resize(X, (self.input_shape, self.input_shape)) if self.augment: X = augment_image(X) X_batch.append(X / 255.) y = np.zeros((5)) y[label] = 1 y_batch.append(y) return np.array(X_batch, dtype=float), np.array(y_batch, dtype=float) def __getitem__(self, index): indexes = self.indexes[index*self.batch_size:(index+1)*self.batch_size] X, y = self.__load_data([self.paths[i] for i in indexes], [self.labels[i] for i in indexes]) return X, y def __len__(self): return int(np.floor(len(self.paths) / self.batch_size))
EfficientNets are state of the art convolutional neural networks that Google Brain released open source. A family of image classification models achieve state-of-the-art accuracy, yet are an order-of-magnitude smaller and faster than previous models such as ResNet-152 and ResNet-50.
def create_model(input_shape=(224, 224, 3)): inputs = Input(input_shape) base_model = EfficientNetB1(input_shape=input_shape, include_top=False, classes=5) x = base_model(inputs) x = GlobalAveragePooling2D()(x) x = Dense(256, activation='relu')(x) x = Dropout(0.1)(x) outputs = Dense(5, activation='softmax')(x) model = Model(inputs, outputs) return model model = create_model((224, 224, 3)) metrics = [ 'accuracy', 'AUC' ] model.compile(optimizer=Adam(), loss='categorical_crossentropy', metrics=metrics) model.summary()
Combining the functions and classes
Finally, we combine the augmentation pipeline, the data generator and our model to estimate the class of the image. On the fourth epoch the model reaches 100%. On the withheld dataset the model generated comparable 99.6%.
traingen_1 = CustomDataGen(train_df.iloc[train_indxs], input_shape=(224, 224, 3), batch_size=8) valgen = CustomDataGen(val_df, input_shape=(224, 224, 3), batch_size=8, augment=False) checkpoint_path = 'models/EfficientNetB1/model_224.h5' callbacks = [ EarlyStopping(monitor='val_loss', mode='min', patience=10, verbose=1), ReduceLROnPlateau(monitor='val_loss', mode='min', factor=0.1, patience=5, min_lr=0.000001, verbose=1), ModelCheckpoint(monitor='val_loss', mode='min', filepath=checkpoint_path, verbose=1, save_best_only=True, save_weights_only=False) ] results = model.fit(traingen_1, validation_data=valgen, epochs=50, callbacks=callbacks)
References and Useful Links
- Jeremy Jordan. 2018. An overview of semantic image segmentation.. [online] Available at: https://www.jeremyjordan.me/semantic-segmentation/ [Accessed 1 September 2021].
- Le, J., 2018. The 4 Convolutional Neural Network Models That Can Classify Your Fashion Images. [online] Medium. Available at: https://towardsdatascience.com/the-4-convolutional-neural-network-models-that-can-classify-your-fashion-images-9fe7f3e5399d [Accessed 1 September 2021].
- Tan, M. and Le, Q., 2020. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. [online] arXiv.org. Available at: https://arxiv.org/abs/1905.11946v5 [Accessed 30 August 2021].
- EfficentNet on Github: https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet.
- Papers with Code Image Classification: https://paperswithcode.com/task/image-classification.
- Studies Confirm the Power of Visuals to Engage Your Audience in eLearning: https://www.shiftelearning.com/blog/bid/350326/studies-confirm-the-power-of-visuals-in-elearning
- TensorFlow data augmentation: https://www.tensorflow.org/tutorials/images/classification#data_augmentation


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Integrating Software-Defined Wide Area Network (SD-WAN) and Secure Access Service Edge (SASE) is becoming increasingly popular as businesses look to improve their network security while maintaining the flexibility and cost savings of SD-WAN. Also, many SD WAN deployments started as cost saving replacements for traditional WAN networks with little focus on security integration. As security infrastructures age and licenses expire, it makes sense to leverage existing SD WAN network investments and add SASE to replace legacy security infrastructure. In many cases, simply shifting traffic to the SASE platform is a fast and effective way to enable enhanced security functionality.
SD-WAN is a network architecture that uses software to control the routing of network traffic, allowing businesses to easily manage and optimize their wide area networks. SASE, on the other hand, is a security architecture that combines many network security functions such as NG firewalls, Secure Web Gateways, Malware/Virus detection, DLP, VPNs, and zero-trust security with network connectivity.
Integrating SASE into existing SD-WAN deployments can be done in a number of ways, depending on the specific requirements of the organization and existing investments in SD WAN.
One approach is to use a SASE platform that is built on top of the existing SD-WAN infrastructure. This allows the organization to continue using the same SD-WAN management tools and policies, while adding the security benefits of SASE if the SD WAN platform doesn’t support SASE directly. An example of this would be implementing Zscaler or Palo Alto Prisma on top of an existing SD WAN Deployment.
Another approach is to use a SASE-enabled SD-WAN solution. This approach involves implementing the SASE functionality within an existing SD WAN deployment if that capability exists. This approach is often the least disruptive to the organization and generally can be implemented with little to no downtime. If the existing SD WAN platform doesn’t have SASE capabilities, replacing the existing SD-WAN platform with a new one that has SASE capabilities built-in is the way to go. This approach can be more disruptive, as it requires the organization to change its existing management and policies, but it can also provide a more integrated and streamlined security solution.
Regardless of the approach chosen, integrating SASE into existing SD-WAN deployments can provide significant benefits.
SASE can help organizations protect against cyber threats by providing secure access to cloud applications and services, while SD-WAN can optimize network performance and reduce costs.
Integrating SASE into existing SD-WAN deployments is a smart move for organizations looking to improve their network security while maintaining the flexibility and cost savings of SD-WAN. There are multiple ways to accomplish this, each with its own set of pros and cons. Configure Inc. can help you understand the specific requirements of your organization and choose the approach that best aligns with those requirements.
Written by Tim Barcus and Michael Brazeau


Never designed a Tesla coil before? Don't worry! TeslaMap makes Tesla coil design fast and easy. Simply enter your input values and TeslaMap will calculate the output parameters - that's it!
Select "File" then "Save As..." from the top menu to save your Tesla coil design. A dialog box will prompt you choose a name and location for the design. Once a design has been opened or saved you can re-save the design by selecting "File" then "Save".
Select "File" then "Open" from the top menu to open an existing Tesla coil design. A dialog box will prompt you to select the file you wish to open.
Selecting "File" then "New" from the top menu. This will clear all the input parameters and calculated Tesla coil parameters.
Selecting "File" then "Export To Text File..." or "Export To Web Page..." from the top menu to save the input and output parameters as a .txt file or HTML web page.
Select "Options" then "Standard" or "Metric" from the top menu to change between standard and metric measurements. When switching between metric and standard all the input values will automatically be converted.
The integrated MMC calculator will make designing your MMC fast and easy.
The TeslaMap program will check your input as you type and alert you by setting the input background to yellow if the input seems unusually large or small. The input background area turns pink if the input creates a design error.
Fixed incorrect NST Impedance output. Thank you Roberto in Italy for reporting the bug!
The calculators (Ohm's law, plate capacitance, peak=RMS and dV/dT) are back.
Redesigned the interface. It appears very similar to previous versions, but it's much more flexible and responsive now. Added a welcome message. Fixed a bug where the desired inductance highlight in the primary coil designer would highlight uH and mH. For example, if the desired inductance was 3uH, then 3uH and 3mH would be highlighted. Improved the design validation check.
Code and interface was converted from WinForms to WPF framework to significantly increase performance. The interface was updated. Several features were added, including design validation, update check and improved error checking. Some output fields were added to main form. The exported HTML page code was improved. The message log was improved. The additional calculators section was removed (it may return in future update). The number of displayed output fields in the calculators has been reduced to increase performance. Removed tooltips.
Redesigned the user interface. Added additional help images.
Redesigned the user interface. Enabled resizing and content stretching to the forms. Added additional help texts to several forms. Converted help text to rich text format to increase readability. Added additional help images. Added a new Primary Coil Incline Calculator. Primary Coil Calculator output table increased to 200 turns. Added a new Secondary Coil Calculator.
Added a "Desired Inductance" input to the Primary Coil Calculator to highlight the turns that will create whatever inductance you want.
Moved the primary coil parameter table from the main screen to it's own "Primary Coil Calculator" tab. Added a skin depth calculator. Made some cosmetic improvements. Updated the target .NET Framework to 4.6.
Fixed an error in the Ohm's Law calculator. When given Power and Voltage inputs, the Current output was incorrect.
Added the option to export the design summary to a web page in HTML format. The new web page format uses tables to make the summary layout much more user friendly. Alternate rows are colored, but all the color is removed when you print to save your insanely expensive ink.
Corrected a couple bugs. Corrected the "Optimum Topload Capacitance" output unit from kHz to pF. Entering "0" for "Primary Coil Incline Angle" no longer displays a warning message.
Added a message bar at the bottom of the main form that displays helpful information and error messages. Added small buttons next to the output fields that show helpful information in the message bar. Added an AWG to inch / mm conversion in the "Calculators" page. Also made some cosmetic improvements.
Fixed a bug that caused a error message to repeatedly appear if the user only enters a decimal point.
Several small improvements have been made and some new features have been added. The program now includes several helpful calculators. The interface has a more native look and feel. TeslaMap version 6 has been re-written in C#. Version 6 does not require the Java Runtime Environment (which can be an inconvenience for some users). However, version 6 does require the .NET Framework from Microsoft (which almost all Windows computers already have). Also, version 6 will only run on Windows.
What happened to versions 2-5? TeslaMap was originally written in VB for Windows only. This development path encompassed versions 1-5. At that point TeslaMap was re-written in JAVA for Windows, Mac and Linux. This version started at version 1 (by this time the VB version had progressed to version 5). The newest version of TeslaMap has been written for Windows only, so it resumes the original version path and has been designated version 6.
A Windows installer is now available so you don't have to manually extract the zip file. The installer will try to check for the Java Runtime Environment (JRE) on the computer. A message will alert you if the JRE is not found. The zip file is still available for Linux and Mac users.
Made some changes to the user interface. Replaced the primary coil output parameter list and MMC calculator list with tables. The tables show parameters for 100 primary coil turns, and 100 series caps with 9 parallel strings in the MMC calculator. Removed the "Optimum Resonate Sized Primary Capacitance" output, it shouldn't be used with NSTs. Added primary cap joules, secondary coil capacitance, and a few other parameters to the exported file. Added a lot of countries to the location list. Fixed an issue with keyboard shortcuts in the menus. Fixed a small issue with the "Save" and "Save As" process. Added a message log to the "About" screen to track errors and messages. Updated the MMC Help screen. Added a table to the AWG / inch / mm conversion screen. The conversion chart ranges from 1 to 40 AWG. Improved the splash screen.
June 11, 2011
Made some changes to the user interface to improve consistency across platforms. Changed default look and feel from system to Java. Added a splash screen.
June 3, 2011
TeslaMap now saves design files in an XML format. Saved design files created with previous versions of TeslaMap are not compatible with this version (sorry). Output boxes have been enlarged. MMC capacitor voltage warning has been increased to 3.6kV. Error messages have been improved.
May 30, 2011
Made some changes to the user interface to improve usability on particular platforms.
May 17, 2011
Improved integration and expanded the output options of the MMC calculator. Removed the magnet wire insulation thickness option (it does not have a significant effect on the coil design). Added metric measurements to the help text. Corrected an error on the MMC Help screen (total MMC capacitance changed from uF to nF).
May 1, 2011
Updated "Set Location" menu option, re-ordered optimum MMC capacitance outputs, improved "About" dialog window.
Jan 27, 2011
Updated input validation, input change events, MMC output formatting and export dialog.
June 17, 2010
Updated input validation and error dialogs.
June 12, 2010
Added support for international location specific number formatting. Thanks Jan for testing.
May 13, 2010
Corrected the "needed primary coil inductance" calculation. Thanks David for bringing it to my attention.
Feb 20, 2010
Added a magnet wire diameter AWG - mm conversion chart and graph.
Sept 25, 2009
Updated the interface to improve compatibility with Mac OS X. Thank you to William for bringing the issue to my attention and helping to correct the issue.
Aug 7, 2009
Updated the MMC help screen. Fixed a feature that caused the program to display "Open" in the "Save" dialog box. Added primary coil parameters at tap turn back to the Export file (they were accidentally deleted in the last revision).
July 15, 2009
I've continued to updated the interface by consolidating several tab panels. All the outputs are now visible on a single tab. I also fixed a small featured that could show a slightly incorrect number of turns required to tune the coil when only odd turns were displayed.
May 12, 2009
I updated the interface by consolidating several tab panels. Hopefully it's a bit easier to use now.
April 29, 2009
I managed to get the primary coil inductance calculation with the incline angle working. I sacrificed quite a few brain cells fighting with it.
April 8, 2009
I added options for flat or vertical primary coil. The conical angle input is still disabled. I updated the interface a bit.
Feb 27, 2009
I added an Export feature so the Tesla coil design can be exported to a .txt file. The exported file contains most of the input and calculated output parameters.


|Title||Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions.|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Zhang S, Nguyen TD, Zhao Y, Gauthier SA, Wang Y, Gupta A|
Purpose: To evaluate the diagnostic accuracy of a novel non-contrast brain MRI method based on semiautomatic lesion detection using T2w FLAIR subtraction image, the statistical detection of change (SDC) algorithm (T2w + SDC), and quantitative susceptibility mapping (QSM). This method identifies new lesions and discriminates between enhancing and nonenhancing lesions in multiple sclerosis (MS).
Methods: Thirty three MS patients who had MRIs at two different time points with at least one new Gd-enhancing lesion on the 2nd MRI were included in the study. For a reference standard, new lesions were identified by two neuroradiologists on T2w and post-Gd T1w images with the help of T2w + SDC. The diagnostic accuracy of the proposed method based on QSM and T2w + SDC lesion detection (T2w + SDC + QSM) for assessing lesion enhancement status was determined. Receiver operating characteristic (ROC) analysis was performed to compute the optimal lesion susceptibility cutoff value.
Results: A total of 165 new lesions (54 enhancing, 111 nonenhancing) were identified. The sensitivity and specificity of T2w + SDC + QSM in predicting lesion enhancement status were 90.7% and 85.6%, respectively. For lesions ≥50 mm3, ROC analysis showed an optimal QSM cutoff value of 13.5 ppb with a sensitivity of 88.4% and specificity of 88.6% (0.93, 95% CI, 0.87-0.99). For lesions ≥15 mm3, the optimal QSM cutoff was 15.4 ppb with a sensitivity of 77.9% and specificity of 94.0% (0.93, 95% CI, 0.89-0.97).
Conclusion: The proposed T2w + SDC + QSM method is highly accurate for identifying and predicting the enhancement status of new MS lesions without the use of Gd injection.
|Alternate Journal||Neuroimage Clin|
|PubMed Central ID||PMC5790036|


A new era of innovation in the field of research has been sparked by the rise of artificial intelligence (AI). AI is revolutionizing the way we conduct research, enhancing decision-making processes and enhancing data analysis accuracy and efficiency. But just like any new technology, AI has advantages and disadvantages that should be carefully weighed.
AI’s advantages for Design Thinkers who research into innovation include:
1. Enhanced Efficiency:
One of the biggest advantages of AI in research is the improved efficiency it offers. Large amounts of data can be quickly analyzed by AI-powered tools, which can also spot patterns and make inferences that could take human researchers days, weeks, or even months to make. While this can help in the brainstorming process, it needs to be verified by the human researcher. Thus, the overall process can be reduced using AI, still the researcher must spend about the same time and effort for editing.
2. Better Accuracy:
AI models can be trained to identify intricate patterns and correlations that human researchers may miss. Results are improved in accuracy and dependability as a result. Again this needs to be verified by the human researcher.
3. Enhanced Creativity:
AI has the capacity to come up with fresh concepts and perceptions that human researchers might not have thought of. This cannot simply be used as is but may trigger wild new ideas and enrich the diverging process. Researchers and designers will need to evaluate, prioritize, and converge those ideas. In the end this can result in new innovations and breakthroughs that might not have been possible without the use of AI.
4. Cost Savings:
By automating labor-intensive tasks, AI can save researchers a significant amount of time and money, in the process that was used to be called secondary research. See what information is already available as a basis to decide what needs to be proofed and what needs to be researched primarily. In the end, AI allows the researcher more time to concentrate on more crucial tasks.
With all the hype and excitement about AI there are still risks to be considered, but they can be minimized by an experienced human research consultant:
1. Absence of Human Judgment:
AI models are only as good as the data they are trained on. If the data is lacking, inaccurate, or skewed, this may result in biased findings. When using AI, consultants should exercise caution and make sure to still interpret and edit the findings using human judgment.
2. Security Risks:
There is a chance that private data will be compromised as AI is used in research more and more. To safeguard their data and prevent unauthorized access, researchers must make sure that the necessary security measures are in place. Though this should be a given for all researcher and will become even more crucial.
As AI advances, there are ethical questions about how it will affect society. AI algorithms are only as good as the data they are trained on, and if the data contains bias, the insights generated by the AI will also be biased. This can result in unfair and inaccurate conclusions that can have negative consequences for individuals or groups.
To address this, it is important for market researchers to carefully select the data used in their AI models and ensure that it is diverse and representative of the target population. The researcher needs to pay close attention to any ethical conflicts that may be triggered.
4. Over-Reliance on AI:
Researchers could rely too heavily on AI and neglect their unique capabilities for analytical processes. Human critical thinking paired with experience and knowledge should be the basis of all analysis. Making sure AI is utilized as a tool to assist researchers rather than as a substitute for human discretion is crucial.
In conclusion, AI has significant advantages for innovation research, but it’s critical to balance those advantages with any associated risks. When using AI, consultants must exercise caution and make sure that human judgment is still applied to the results’ interpretation. Researchers can make new discoveries that might not have been possible without AI by using the technology responsibly and ethically.
This article has been written with the help of AI!
While AI was a big help in the research process and structuring, human experience and knowledge validate and add to the content and take it to the next level.